Seismic performance of iron-based shape memory alloy shear panel damper Jiale Li; Samadi Jamshid; Arthur Ramandalina; Taisuke Kawakami; Ji Dang
Journal of Constructional Steel Research,
Volume：227,
First page：109410,
Last page：109410, Apr. 2025,
[Reviewed]Elsevier BV, Scientific journal
DOI：https://doi.org/10.1016/j.jcsr.2025.109410DOI ID：10.1016/j.jcsr.2025.109410,
ISSN：0143-974X Experimental Investigation on the Mechanical Properties of Silicone Elastomers Filled with Fumed Silica for Seismic Isolation BearingsArthur Ramandalina; Ji Dang
Journal of Building Material Science,
Volume：7,
Number：1,
First page：44,
Last page：61, Mar. 2025,
[Reviewed],
[Last]Laminated elastomeric bearings used in seismic isolation rely on the mechanical properties of their constituent elastomers to ensure effective performance. However, despite their resistance to temperature fluctuations and environmental aggressors, silicone elastomers exhibit relatively low stiffness, limiting their direct applicability in seismic isolation. This study investigates the effect of fumed silica as a reinforcing filler to enhance the mechanical properties of laminated silicone elastomeric bearings. Elastomeric samples were fabricated with varying fumed silica proportions and subjected to Shore A hardness, uniaxial tensile, and lap shear tests to assess the influence of filler content. Additionally, quasi-static tests were conducted on reduced-scale bearing prototypes under combined vertical compression and cyclic horizontal shear to evaluate their seismic isolation performance. The results demonstrate that fumed silica reinforcement significantly increases stiffness, as evidenced by higher Shore A hardness values. However, a trade-off was observed in tensile properties, with reductions in tensile strength and elongation at break. Despite this, the equivalent elastic modulus did not show substantial variation up to large deformations, indicating that stiffness is preserved under most working conditions. Lap shear tests showed that fumed silica improves shear resistance, while quasi-static tests revealed inelastic behavior with small increases in equivalent shear coefficients but no substantial loss in damping ratios. These findings suggest that fumed silica reinforcement enhances silicone elastomers’ stiffness and shear resistance while maintaining moderate damping properties, making it a promising approach for improving the mechanical performance of elastomeric bearings in seismic isolation applications.
Bilingual Publishing Group, English, Scientific journal
DOI：https://doi.org/10.30564/jbms.v7i1.8472DOI ID：10.30564/jbms.v7i1.8472,
eISSN：2630-5216 Enhanced inferable capability in state estimation of dynamic systems exhibiting hysteresis/inelastic behavior under the limit of minimal sensor Xinhao He; Dan Li; Jiancheng Gu; Ji Dang; Shigeki Unjoh
Mechanical Systems and Signal Processing,
Volume：225,
First page：112282,
Last page：112282, Feb. 2025,
[Reviewed]Elsevier BV, English, Scientific journal
DOI：https://doi.org/10.1016/j.ymssp.2024.112282DOI ID：10.1016/j.ymssp.2024.112282,
ISSN：0888-3270 SCSHM benchmark study on bridge in-service structural monitoringMaria Pina Limongelli; Doug Thomson; Sreenivas Alampalli; Aftab Mufti; Thomas Schumacher; Luca Martinelli; Othmane Lasri; Harry Shenton; Genda Chen; Mohammad Noori; Farnaz Raeisi; Ahmed Silik; Ji Dang; Ray Hoemsen; Hui Li; Naiwei Lu; Yi-Qing Ni; Ian Smith; Zhishen Wu
Journal of Civil Structural Health Monitoring, Sep. 2024,
[Reviewed]Abstract
The mission of the Society of Civil Structural Health Monitoring (SCSHM, previously known as ISHMII) is to advance the understanding and application of structural monitoring methodologies for the management of civil infrastructure systems. To enable comparative and contrasting studies of various monitoring issues and technologies, the SCSHM Committee on Data-Enhanced Infrastructures Management (DEIMC) identified the need for benchmark problems in the areas of bridge and building structural monitoring. This article reports and briefly discusses the first benchmark study on in-service structural monitoring of bridges that was developed in collaboration with the University of Manitoba, and presents the structure details, study goals, data made available to the engineering community, and other relevant details. This paper has been submitted to the JCSHM as the outcome of the work of the DEIMC Committee of the SCSHM. However, since JCSHM does not publish at present papers without original experimental and or field monitoring components, data from this work cannot be used for publications in JCSHM.
Springer Science and Business Media LLC, Scientific journal
DOI：https://doi.org/10.1007/s13349-024-00846-1DOI ID：10.1007/s13349-024-00846-1,
ISSN：2190-5452,
eISSN：2190-5479 Quantum‐enhanced machine learning technique for rapid post‐earthquake assessment of building safetySanjeev Bhatta; Ji Dang
Computer-Aided Civil and Infrastructure Engineering,
Volume：39,
Number：21,
First page：3188,
Last page：3205, Jun. 2024,
[Reviewed]Abstract
Fast, accurate damage assessment of numerous buildings for large areas is vital for saving lives, enhancing decision‐making, and expediting recovery, thereby increasing urban resilience. The traditional methods, relying on expert mobilization, are slow and unsafe. Recent advances in machine learning (ML) have improved assessments; however, quantum‐enhanced ML (QML), a rapidly advancing field, offers greater advantages over classical ML (CML) for large‐scale data, enhancing the speed and accuracy of damage assessments. This study explores the viability of leveraging QML to evaluate the safety of reinforced concrete buildings after earthquakes, focusing on classification accuracy only. A QML algorithm is trained using simulation datasets and tested on real‐world damaged datasets, with its performance compared to various CML algorithms. The classification results demonstrate the potential of QML to revolutionize seismic damage assessments, offering a promising direction for future research and practical applications.
Wiley, Scientific journal
DOI：https://doi.org/10.1111/mice.13291DOI ID：10.1111/mice.13291,
ISSN：1093-9687,
eISSN：1467-8667 Real-time and pseudo dynamic hybrid experiments on isolation bearings in low-temperature environments (in Japanese) Nobuyuki NABESHIMA; Ji DANG; Yuki HAMADA; Takehiko HIMENO; Yutaka SHINMYOU; Akira IGARASHI; Jie SHEN
Japanese Journal of JSCE,
Volume：80,
Number：13,
First page：23-13151, Jun. 2024,
[Reviewed],
［Domestic magazine］JSCE, Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejj.23-13151DOI ID：10.2208/jscejj.23-13151 A fast survey report about bridge damages by the 2024 Noto Peninsula Earthquake Chisato Mizuno; Xin Wang; Ji Dang
Earthquake Research Advances,
First page：100312,
Last page：100312, May 2024
Elsevier BV, Scientific journal
DOI：https://doi.org/10.1016/j.eqrea.2024.100312DOI ID：10.1016/j.eqrea.2024.100312,
ISSN：2772-4670 Stress-softening behavior of high-damping rubber bearings at low temperatures Yuqing Tan; Yanhui Liu; Ji Dang; Akira Igarashi; Takehiko Himeno; Yuki Hamada
ASCE Journal of Structural Engineering,
Volume：150,
Number：6,
First page：04024050-1,
Last page：04024050-13, Mar. 2024,
[Reviewed],
［Internationally co-authored］,
［International magazine］American Society of Civil Engineers (ASCE), English, Scientific journal
DOI：https://doi.org/10.1061/JSENDH.STENG-13253DOI ID：10.1061/JSENDH.STENG-13253 Machine learning prediction models for ground motion parameters and seismic damage assessment of buildings at a regional scale Sanjeev Bhatta; Xiandong Kang; Ji Dang
Resilient Cities and Structures,
Volume：3,
Number：1,
First page：84,
Last page：102, Mar. 2024,
[Reviewed]Elsevier BV, Scientific journal
DOI：https://doi.org/10.1016/j.rcns.2024.03.001DOI ID：10.1016/j.rcns.2024.03.001,
ISSN：2772-7416 CNN‐based damage detection of buildings from wave propagation between two adjacent floorsAijia Zhang; Xin Wang; Ji Dang
Earthquake Engineering and Resilience,
Volume：2,
Number：4,
First page：479,
Last page：492, Dec. 2023
Abstract
Structural damages are expected to be detected from the changes in shear‐wave propagation in the vertical direction of the building. In the previous study, we constructed a convolutional neural network (CNN) model to recognize the changes in impulse responses at the inter‐floor with the virtual source at the top. However, it is difficult to tell the exact damaged stories, because it contains the information of all the stories between the virtual source and the receiver. In this study, to perform the story‐by‐story damage detection, wave propagation between two adjacent floors was proposed. The virtual source of the impulse response was changed from the top floor to the determined inter‐floor of the building. By recognizing the changes in the wavefield between the determined floor where the virtual source is located and its upper and lower adjacent floor, damages between two adjacent stories can be identified. The CNN model was used to automatically recognize the changes in the visualized impulse responses over time and validated using the data of a shake‐table test on a one‐third scaled 18‐story steel frame building.
Wiley, Scientific journal
DOI：https://doi.org/10.1002/eer2.62DOI ID：10.1002/eer2.62,
ISSN：2770-5706,
eISSN：2770-5706 Hybrid simulation tests evaluating the seismic performance of lead high-damping rubber bearings at low temperatures Yuqing Tan; Ji Dang; Akira Igarashi; Takehiko Himeno; Yuki Hamada
Structure and Infrastructure Engineering,
Number：online,
First page：1,
Last page：16, Dec. 2023,
[Reviewed],
［Internationally co-authored］,
［International magazine］ISSN: 1573-2479, 1744-8980
Taylor & Francis, English, Scientific journal
DOI：https://doi.org/10.1080/15732479.2023.2292757DOI ID：10.1080/15732479.2023.2292757 A multi‐layer thermo‐mechanical coupling hysteretic model for high damping rubber bearings at low temperatureJie Shen; Igarashi Akira; Ji Dang; Yuki Hamada; Takehiko Himeno
Earthquake Engineering and Structural Dynamics, Dec. 2023
Abstract
High damping rubber (HDR) bearings have been widely applied in seismic isolation of structures. However, the complex behavior of HDR bearings is influenced by thermal mechanism coupled with the seismic response of the structure, particularly at low ambient temperatures. In order to express the hysteretic restoring force behavior of HDR bearings involving temperature dependence, heating effect, and heat transfer with an improved accuracy, a multi‐layer thermo‐mechanical coupling model was developed. The thermal mechanism was illustrated by considering the heating effect and heat transfer in the multi‐layer thermal‐coupled model. A nonlinear hysteretic model including the temperature dependence of the stress‐strain relationship of rubber was incorporated. Quasi‐static cyclic loading was conducted for parameter identification and real‐time hybrid simulation tests were carried out for model validation. The model accurately represented the time‐dependent thermal mechanism within the bearing, considering the non‐uniform distribution of internal temperature. Numerical results exhibited good agreement with the experimental results, including the hysteresis curve, temperature history, and temperature distribution. The model demonstrated improved accuracy in computing the hysteretic behavior compared with an existing simple model.
Wiley, Scientific journal
DOI：https://doi.org/10.1002/eqe.4054DOI ID：10.1002/eqe.4054,
ISSN：0098-8847,
eISSN：1096-9845 Using image captioning for automatic post-disaster damage detection and identification
Osama ABBAS; Ji DANG
Intelligence, Informatics and Infrastructure, Volume：4, Number：2, First page：27, Last page：34, Nov. 2023, [Reviewed], [Last]
English, Scientific journal
Multiclass seismic damage detection of buildings using quantum convolutional neural networkSanjeev Bhatta; Ji Dang
Computer-Aided Civil and Infrastructure Engineering,
Volume：39,
Number：3,
First page：406,
Last page：423, Aug. 2023,
[Reviewed],
[Last]Abstract
The traditional visual inspection technique for damage assessment of buildings immediately after an earthquake can be time‐consuming, labor‐intensive, and risky. Numerous studies have been carried out using deep learning techniques, particularly convolutional neural network (CNN), to evaluate the damage to building structures after an earthquake using buildings’ damage images. Quantum computing, on the other hand, is a computing environment that can exploit superposition and entanglement, which are not available in classical computing environments, to achieve higher performance using parallelism between qubits. This paper presents a novel quantum CNN (QCNN) approach to detect damage to reinforced concrete (RC) buildings from images after the earthquake. The QCNN model is developed and trained using the RC building damaged images collected from past earthquakes. The performance of this model is evaluated based on the multiclass damage detection ability of the real‐world RC building damaged images collected from the recent earthquake in Turkey in February 2023. Furthermore, the seismic damage detection accuracy obtained from the QCNN model is compared with various CNN architecture results.
Wiley, Scientific journal
DOI：https://doi.org/10.1111/mice.13084DOI ID：10.1111/mice.13084,
ISSN：1093-9687,
eISSN：1467-8667 Seismic damage prediction of RC buildings using machine learningSanjeev Bhatta; Ji Dang
Earthquake Engineering & Structural Dynamics,
Volume：52,
Number：11,
First page：3504,
Last page：3527, May 2023,
[Reviewed],
[Last]Abstract
Decision‐makers and stakeholders require a rapid assessment of potential damage after earthquake events in order to develop and implement disaster risk reduction strategies and to respond systematically in post‐disaster situations. The damage investigated manually after an earthquake are complicated, labor‐intensive, time‐consuming, and error prone process. The development of fragility curves is time consuming and unable to predict the damage for wide classes of structures since it considers few structural properties and only one seismic characteristic. Furthermore, the nonlinear finite element method cannot be utilized for numerous buildings because it involves more time and money. This paper presents the machine learning (ML)‐based seismic damage prediction of RC buildings. It is found that some of the research works only considered seismic parameters or structural parameters to train the ML models and predict the structural damage assessment. However, these ML models may not fully reveal the underlying complexity of the relationship between input parameters and building performance. As a result, their applicability will be limited. This paper evaluates the feasibility of using ML techniques such as K‐nearest neighbor, random forest, decision tree, support vector machine, and artificial neural network to rapidly predict earthquake‐induced reinforced concrete building damage considering both the structural properties and ground motion characteristics. The machine learning models are trained using the simulation results. Due to lack of real earthquake damage datasets or limited access, most of the research works used Scikit Learn train_test_split function to randomly split the entire datasets into training and testing datasets and the performance of the proposed ML technique are evaluated using the testing datasets. However, in this study, the performances of different ML models are evaluated using real earthquake damage datasets of RC buildings collected after 2015 Nepal earthquake. The overall accuracy on testing datasets suggests the capability of machine learning algorithms in successfully predicting the seismic damage of reinforced concrete buildings in quick time with reasonable accuracy. This study is beneficial in emergency response and recovery planning after an earthquake.
Wiley, Scientific journal
DOI：https://doi.org/10.1002/eqe.3907DOI ID：10.1002/eqe.3907,
ISSN：0098-8847,
eISSN：1096-9845 Hysteretic restoring force model of high damping rubber bearings including thermo-mechanical coupled effect Yuqing Tan; Ji Dang; Akira Igarashi; Takehiko Himeno; Yuki Hamada
Engineering Structures,
Volume：277,
First page：115449,
Last page：115449, Feb. 2023
Elsevier BV, Scientific journal
DOI：https://doi.org/10.1016/j.engstruct.2022.115449DOI ID：10.1016/j.engstruct.2022.115449,
ISSN：0141-0296 Structure from segmented motion for bridge 3D damage detection using UAV, AI, and MR MONTES Katrina; LIU Jiaming; DANG Ji; CHUN Pang-jo
Intelligence, Informatics and Infrastructure,
Volume：4,
Number：2,
First page：27,
Last page：34, 2023
Periodical bridge inspection is essential to monitor the deterioration and maintenance progress. However, traditional inspection method requires a lot of works, expensive equipments, and time costly, and its difficult to implement periodically specially in developing countries. Therefore, this study proposed a Structure-from-Segmented-Motion (SfSM) method to enhance the bridge vision based inspection process. This method can localize and visualize the damage location in the bridge by utilizing various technologies such as UAV for data gathering, deep learning methods for damage segmentation, and Mixed Reality (MR) for digital transformation (DX). Firstly, optimal flight path for a single span I-girder bridge using UAV was proposed. This helps to fasten the visual bridge inspection, reduce workforce, and inspect some difficult to access parts without the use of expensive equipments. Then, the trained Deeplabv3+ was used to segment the corrosion damages of the images gathered. Finally, the 3D bridge model with and without the segmented corrosion were reconstructred using SfM and SfSM to visualize the location of damage in the whole bridge and viewed in a mixed reality (MR) platform. The proposed method will help the engineers to evaluate the bridge condition remotely which will save time and makes it safer.
Japan Society of Civil Engineers, English
DOI：https://doi.org/10.11532/jsceiiai.4.2_27DOI ID：10.11532/jsceiiai.4.2_27,
eISSN：2758-5816 Bridge multiple damage segmentation and 3D damage model generation using background images additional learning FUJISHIMA Tonan; DANG Ji; CHUN Pang-jo
Artificial Intelligence and Data Science,
Volume：4,
Number：3,
First page：705,
Last page：714, 2023
Visual inspection is important for the maintenance of bridges. However, the decrease in the working population in the construction industry has become an issue in Japan. In addition, visual inspection is time consuming and dangerous in some cases. Therefore, the efficiency, rationalization, and safety of inspection work are required. The current inspection content need decision making based on the experience of the inspector. This can lead to serious accidents due to human mistakes. Inspection methods that utilize AI and UAV can solve these problems. In this study, we performed automatic multi damage detection of UAV images using the Deeplabv3+ model. The problem that UAV images have a large proportion of background and are prone to false positives was improved by background reinforced training. This method is to train a Deeplabv3+ or other semantic segmentation models by standard damage annotated image data, and training it again before use it to real bridge UAV videos by a few background non annotated images to let the background looked familiar to the model. The background reinforced training of UAV images resulted in improved detection accuracy. It is considered that this is because the model learned the characteristics of the bridge and the information around the bridge from the UAV image. After that, by creating a 3D damage model using the image that the damage detection was performed, we proposed a new utilization method of the 3D model.
Japan Society of Civil Engineers, Japanese
DOI：https://doi.org/10.11532/jsceiii.4.3_705DOI ID：10.11532/jsceiii.4.3_705,
eISSN：2435-9262 ADDITIONAL LEARNING OF SEGUMENTATION MODELS USING BACKGROUND IMAGES OF INSPECTED BRIDGES FUJISHIMA Tonan; DANG Ji; CHUN Pang-jo
Intelligence, Informatics and Infrastructure,
Volume：3,
Number：J2,
First page：994,
Last page：1002, 2022
Visual inspection is important for the maintenance of bridges. However, the decrease in the working population in the construction industry has become an issue in Japan. In addition, visual inspection is time consuming and dangerous in some cases. Therefore, the efficiency, rationalization, and safety of inspection work are required. The current inspection content need decision making based on the experience of the inspector. This can lead to serious accidents due to human mistakes. Inspection methods that utilize AI and UAV can solve these problems. In this study, we performed automatic damage detection of UAV images using the U-Net model. The balance of the dataset was ensured by focusing only on corrosion. The problem that UAV images have a large proportion of background and are prone to false positives was improved by background reinforced training. This method is to train a U-Net or other semantic segmentation models by standard damage annotated image data, and training it again before use it to real bridge UAV videos by a few background non annotated images to let the background looked familiar to the model. The background reinforced training of UAV images resulted in improved detection accuracy. It is considered that this is because the model learned the characteristics of the bridge and the information around the bridge from the UAV image.
Japan Society of Civil Engineers, Japanese
DOI：https://doi.org/10.11532/jsceiii.3.j2_994DOI ID：10.11532/jsceiii.3.j2_994,
eISSN：2435-9262 BRIDGE CORROSION DAMAGE DETECTION USING DEEPLABV3+ MODEL AND PERFORMANCE BOOSTING LIU Jiaming; DANG Ji; CHUN Pang-jo
Intelligence, Informatics and Infrastructure,
Volume：3,
Number：J2,
First page：802,
Last page：810, 2022
In recent years, the deterioration of bridges has become a major problem in many countries. Specially in Japan, the infrastructures are required to be inspected at least once per five years, so that they can to be maintained properly. However, the number of civil engineers is continuously decreasing, and conventional inspection methods require a lot of skilled manpower, equipment, and time. Nowadays, an improved approach has been proposed to use UAV for data gathering and different AI techniques for bridge damage detection. The AI detection of multiple damages is not sufficiently accurate, and the accuracy decreases when the number of damage types increases. In this study, DeepLabv3+ model was used to detect a single damage that focused on corrosion. Transfer learning was used to improve the accuracy of the boundaries. The effect of annotation's quality on the trained model, improvement of accuracy by finding the optimum hyperparameters, and the reduction of false positives by adding background photos were discussed in this study.
Japan Society of Civil Engineers, Japanese
DOI：https://doi.org/10.11532/jsceiii.3.j2_802DOI ID：10.11532/jsceiii.3.j2_802,
eISSN：2435-9262 A RATIONALIZED SEISMIC DESIGN METHOD FOR BUILDINGS IN EARTHQUAKE-PRONE DEVELOPING COUNTRIESTint Lwin; Takeshi Koike; Ji Dang
ASEAN Engineering Journal,
Volume：11,
Number：4,
First page：266,
Last page：279, Dec. 2021
In general, the US codes such as the UBC-97 and ASCE-7 are widely used in developing countries including Myanmar, Syria, Philippines and so on. When the current seismic design guideline based on the UBC-97 and ACI 318-99 in Myanmar is assessed, several problems can be found in the following items: firstly, the fundamental period is not checked in modeling; secondly, reduction factor R is introduced a priori for the base shear estimation. And finally, a limit state assessment is done only for Design Basic Earthquake (DBE) but not for other design earthquakes. As a result, adequate yield strength is not checked for Maximum Operational Earthquake (MOE). Then there is no way to assess the seismic safety of the ultimate limit state for Maximum Considered Earthquake (MCE). In order to solve these problems, a rationalized seismic design method for earthquake prone developing countries is proposed. A new seismic design method is developed for MOE and MCE with adequate yield acceleration and typical period of the building estimated by using pushover analysis. A simplified procedure to estimate the inelastic response for a given design spectrum is also proposed. Finally, this design procedure can provide a rational method to assess the seismic safety for the ultimate limit of the building.
Penerbit UTM Press, English, Scientific journal
DOI：https://doi.org/10.11113/aej.v11.18101DOI ID：10.11113/aej.v11.18101,
eISSN：2586-9159 Multi-Type Bridge Damage Detection Method Based on YOLO
Ji DANG; Pang-jo ChunPang-jo Chun; Taiga MIZUMOTO; Jiaming LIU; Tonan FUJISHIMA
Intelligence, Informatics and Infrastructure, Volume：Vol.2, Number：Iss.J2, First page：447, Last page：456, Nov. 2021, [Reviewed]
Japanese, Symposium
Comparison of semantic segmentation and instance segmentation based on pixel-level damage detection
Jiyuan SHI; Sal Saad AL; DEEN TAHER; Ji DANG
Intelligence, Informatics and Infrastructure, Volume：Vol.2, Number：Iss.2, First page：46, Last page：53, Nov. 2021, [Reviewed]
English, Symposium
Semi-autopilot UAV flight path control for bridge structural health monitoring under GNSS-denied environment
Katrina Montes; Sal Saad Al Deen Taher; Ji Dang; Pang-Jo Chun
Intelligence, Informatics and Infrastructure, Volume：Vol.2, Number：Iss.2, First page：19, Last page：26, Nov. 2021, [Reviewed]
English, Symposium
Geometric Attention Regularization Enhancing Convolutional Neural Networks for Bridge Rubber Bearing Damage Assessment Mida Cui; Gang Wu; Zhiqiang Chen; Ji Dang; Minghua Zhou; Dongming Feng
Journal of Performance of Constructed Facilities,
Volume：35,
Number：5, Oct. 2021
Rubber bearing condition evaluation is crucial for bridge inspection, and the current practice heavily relies on human-vision inspection. Convolutional neural networks (CNNs) have shown great potential for structured damage recognition tasks in recent years
however, this method usually requires a large training data set, which is difficult to collect in practice for rubber bearings. Therefore, methods to improve the performance of CNN for condition classification for elastomeric bearings are necessary. In this paper, a geometric attention regularization (GAR) method is proposed to enhance the performance of CNN for the condition evaluation of rubber bearings. Firstly, the data set of bearings contains different damages that are collected and labeled where the location of the rubber bearing is presented as a bounding box. Then, the location information is utilized to enhance the loss function of CNN in two aspects. On one hand, the bearing location worked as an attention mechanism to indicate the important part of the input image. Besides, it worked as a regularization method to mitigate the effect of overfitting. Experiments using two CNN architectures, including VGG-11 and ResNet-18 trained with transfer learning techniques, are used to evaluate the efficacy of the proposed method. The results show the proposed method is effective to enhance the performance of the CNN model.
American Society of Civil Engineers (ASCE), English, Scientific journal
DOI：https://doi.org/10.1061/(ASCE)CF.1943-5509.0001634DOI ID：10.1061/(ASCE)CF.1943-5509.0001634,
ISSN：1943-5509,
SCOPUS ID：85111376923 A modified curve-approximated hysteretic model for partially concrete-filled steel tube bridge piers Hui-hui Yuan; Ji Dang; Qing-xiong Wu; Tetsuhiko Aoki
Journal of Constructional Steel Research,
Volume：185,
First page：106861,
Last page：106861, Oct. 2021,
[Reviewed]Elsevier BV, Scientific journal
DOI：https://doi.org/10.1016/j.jcsr.2021.106861DOI ID：10.1016/j.jcsr.2021.106861,
ISSN：0143-974X Waveform‐based fracture identification of steel beam ends using convolutional neural networksLuyao Wang; Ji Dang; Xin Wang; Ashish Shrestha
Structural Control and Health Monitoring,
Volume：Vol.28,
Number：Iss.9,
First page：1,
Last page：23, Jun. 2021,
[Reviewed]Wiley, English, Scientific journal
DOI：https://doi.org/10.1002/stc.2777DOI ID：10.1002/stc.2777,
ISSN：1545-2255,
eISSN：1545-2263 Preliminary Report of the Damage by the 2021 Off Fukushima Prefecture Earthquake Mj7.3, Japan
Kazuma INOUE; Takashi KIYOTA; Masataka SHIGA; Ji Dang; Xin Wang
JSCE Journal of Disaster FactSheets, Volume：FS2021, Number：E-0001, First page：pp.1, Last page：8, May 2021, [Reviewed]
English, Scientific journal
Optimum wavelet selection for nonparametric analysis toward structural health monitoring for processing big data from sensor network: A comparative studyAhmed Silik; Mohammad Noori; Wael A Altabey; Ji Dang; Ramin Ghiasi; Zhishen Wu
Structural Health Monitoring,
Volume：21,
Number：3,
First page：147592172110102,
Last page：147592172110102, May 2021,
[Reviewed]A critical problem encountered in structural health monitoring of civil engineering structures, and other structures such as mechanical or aircraft structures, is how to convincingly analyze the nonstationary data that is coming online, how to reduce the high-dimensional features, and how to extract informative features associated with damage to infer structural conditions. Wavelet transform among other techniques has proven to be an effective technique for processing and analyzing nonstationary data due to its unique characteristics. However, the biggest challenge frequently encountered in assuring the effectiveness of wavelet transform in analyzing massive nonstationary data from civil engineering structures, and in structural health diagnosis, is how to select the right wavelet. The question of which wavelet function is appropriate for processing and analyzing the nonstationary data in civil engineering structures has not been clearly addressed, and no clear guidelines or rules have been reported in the literature to show how the right wavelet is chosen. Therefore, this study aims to address an important question in this regard by proposing a new framework for choosing a proper wavelet that can be customized for massive nonstationary data analysis, disturbances separation, and extraction of informative features associated with damage. The proposed method takes into account data type, data and wavelet characteristics, similarity, sharing information, and data recovery accuracy. The novelty of this study lies in integrating multi-criteria which are associated directly with features that correlated well with change in structures due to damage, including common criteria such as energy, entropy, linear correlation index, and variance. Also, it introduces and considers new proposed measures, such as wavelet-based nonlinear correlation such as cosh spectral distance and mutual information, wavelet-based energy fluctuation, measures-based recovery accuracy, such as sensitive feature extraction, noise reduction, and others to evaluate various base wavelets’ function capabilities for appropriate decomposition and reconstruction of structural dynamic responses. The proposed method is verified by experimental and simulated data. The results revealed that the proposed method has a satisfactory performance for base wavelet selection and the small order of Daubechies and Symlet provide the best results, especially order 3. The idea behind our proposed framework can be applied to other structural applications.
SAGE Publications, English, Scientific journal
DOI：https://doi.org/10.1177/14759217211010261DOI ID：10.1177/14759217211010261,
ISSN：1475-9217,
eISSN：1741-3168 Improvement of Damage Segmentation Based on Pixel-Level Data Balance Using VGG-Unet
Jiyuan Shi; Ji Dang; Mida Cui; Rongzhi Zuo; Kazuhiro Shimizu; Akira Tsunoda; Yasuhiro Suzuki
Applied Science, Volume：11, Number：2, First page：pp.518.1, Last page：17, Jan. 2021, [Reviewed]
English, Scientific journal
Utilization of Unmanned Aerial Vehicle, Artificial Intelligence, and Remote Measurement Technology for Bridge InspectionsPang-jo Chun; Ji Dang; Shunsuke Hamasaki; Ryosuke Yajima; Toshihiro Kameda; Hideki Wada; Tatsuro Yamane; Shota Izumi; Keiji Nagatani
Journal of Robotics and Mechatronics,
Volume：32,
Number：6,
First page：1244,
Last page：1258, Dec. 2020
In recent years, aging of bridges has become a growing concern, and the danger of bridge collapse is increasing. To appropriately maintain bridges, it is necessary to perform inspections to accurately understand their current state. Until now, bridge inspections have involved a visual inspection in which inspection personnel come close to the bridges to perform inspection and hammering tests to investigate abnormal noises by hammering the bridges with an inspection hammer. Meanwhile, as there are a large number of bridges (for example, 730,000 bridges in Japan), and many of these are constructed at elevated spots; the issue is that the visual inspections are laborious and require huge cost. Another issue is the wide disparity in the quality of visual inspections due to the experience, knowledge, and competence of inspectors. Accordingly, the authors are trying to resolve or ameliorate these issues using unmanned aerial vehicle (UAV) technology, artificial intelligence (AI) technology, and telecommunications technology. This is discussed first in this paper. Next, the authors discuss the future prospects of bridge inspection using robot technology such as a 3-D model of bridges. The goal of this paper is to show the areas in which deployment of the UAV, robots, telecommunications, and AI is beneficial and the requirements of these technologies.
Fuji Technology Press Ltd., Scientific journal
DOI：https://doi.org/10.20965/jrm.2020.p1244DOI ID：10.20965/jrm.2020.p1244,
ISSN：0915-3942,
eISSN：1883-8049 AIを活用した鋼構造物の腐食損傷の点検・診断の現状及び展望
全 邦釘; 党 紀; 佐野 泰如; 杉崎 光一; 宮本 崇; 阿部 雅人; 清水 隆史
Volume：64, Number：6, First page：193, Last page：200, Jun. 2020, [Reviewed], [Invited]
Japanese, Scientific journal
ISSN：0520-6340, J-Global ID：202002273819003890
Deep Learning-Based Real-Time Auto Classification of Smartphone Measured Bridge Vibration DataAshish Shrestha; Ji Dang
Sensors,
Volume：20,
Number：9,
First page：2710,
Last page：2710, May 2020,
[Reviewed],
[Last, Corresponding]In this study, a simple and customizable convolution neural network framework was used to train a vibration classification model that can be integrated into the measurement application in order to realize accurate and real-time bridge vibration status on mobile platforms. The inputs for the network model are basically the multichannel time-series signals acquired from the built-in accelerometer sensor of smartphones, while the outputs are the predefined vibration categories. To verify the effectiveness of the proposed framework, data collected from long-term monitoring of bridge were used for training a model, and its classification performance was evaluated on the test set constituting the data collected from the same bridge but not used previously for training. An iOS application program was developed on the smartphone for incorporating the trained model with predefined classification labels so that it can classify vibration datasets measured on any other bridges in real-time. The results justify the practical feasibility of using a low-latency, high-accuracy smartphone-based system amid which bottlenecks of processing large amounts of data will be eliminated, and stable observation of structural conditions can be promoted.
MDPI AG, Scientific journal
DOI：https://doi.org/10.3390/s20092710DOI ID：10.3390/s20092710,
eISSN：1424-8220 Smartphone-Based Bridge Seismic Monitoring System and Long-Term Field Application TestsAshish Shrestha; Ji Dang; Xin Wang; Shogo Matsunaga
Journal of Structural Engineering, ASCE,
Volume：146,
Number：2,
First page：04019208-1,
Last page：04019208-14, Feb. 2020,
[Reviewed],
[Corresponding]American Society of Civil Engineers (ASCE), Scientific journal
DOI：https://doi.org/10.1061/(asce)st.1943-541x.0002513DOI ID：10.1061/(asce)st.1943-541x.0002513,
ISSN：0733-9445,
eISSN：1943-541X Image processing–based real‐time displacement monitoring methods using smart devicesAshish Shrestha; Ji Dang; Keisuke Nakajima; Xin Wang
Structural Control and Health Monitoring,
Volume：27,
Number：2,
First page：e2473.1,
Last page：18, Feb. 2020,
[Reviewed],
[Corresponding]Wiley, English, Scientific journal
DOI：https://doi.org/10.1002/stc.2473DOI ID：10.1002/stc.2473,
ISSN：1545-2255,
eISSN：1545-2263 DEEP CONVOLUTIONAL NEURAL NETWORKS FOR BRIDGE DETERIORATION DETECTION BY UAV INSPECTION
Ji DANG; Toya MATSUYAMA; Pang-Jo CHUN; Jiyuan SHI; Shogo MATSUNAGA
JSCE, Intelligence, Informatics and Infrastructure, Volume：1, Number：1, First page：596, Last page：605, 2020, [Reviewed], [Lead]
Japanese, Scientific journal
DEMONSTRATION EXPERIMENT ON BRIDGE INSPECTION UTILIZING UAV AUTONOMOUS CONTROL
Ji DANG; Takahiro KIKUCHI; Pang-Jo CHUN; Jiyuan SHI
Intelligence, Informatics and Infrastructure, Volume：1, Number：1, First page：623, Last page：633, 2020, [Reviewed], [Lead]
Japanese, Scientific journal
STRUCTURE CONTEXT BASED PIXEL-LEVEL DAMAGE DETECTION FOR RUBBER BEARING
Jiyuan SHI; Ji DANG; Rongzhi ZUO; Kazuhiro SHIMIZU; Akira TSUNODA; Yasuhiro SUZUKI
JSCE, Intelligence, Informatics and Infrastructure, Volume：1, Number：1, First page：18, Last page：24, 2020, [Reviewed]
Japanese, Scientific journal
Development of Tactile Imaging for Underwater Structural Damage DetectionChen; Wu; Hou; Fan; Dang; Chen
Sensors,
Volume：19,
Number：18,
First page：3925,
Last page：3925, Sep. 2019,
[Reviewed]Underwater structural damage inspection has mainly relied on diver-based visual inspection, and emerging technologies include the use of remotely operated vehicles (ROVs) for improved efficiency. With the goal of performing an autonomous and robotic underwater inspection, a novel Tactile Imaging System for Underwater Inspection (TISUE) is designed, prototyped, and tested in this paper. The system has two major components, including the imaging subsystem and the manipulation subsystem. The novelty lies in the imaging subsystem, which consists of an elastomer-enabled contact-based optical sensor with specifically designed artificial lighting. The completed TISUE system, including optical imaging, data storage, display analytics, and a mechanical support subsystem, is further tested in a laboratory experiment. The experiment demonstrates that high-resolution and high-quality images of structural surface damage can be obtained using tactile ‘touch-and-sense’ imaging, even in a turbid water environment. A deep learning-based damage detection framework is developed and trained. The detection results demonstrate the similar detectability of five damage types in the obtained tactile images to images obtained from regular (land-based) structural inspection.
MDPI AG, English, Scientific journal
DOI：https://doi.org/10.3390/s19183925DOI ID：10.3390/s19183925,
eISSN：1424-8220 Implications of bidirectional interaction on nonlinear seismic response of steel piers Yanyan Liu; Ji Dang; Akira Igarashi
Journal of Constructional Steel Research,
Volume：160,
First page：289,
Last page：300, Jun. 2019,
[Reviewed]DOI: 10.1016/j.jcsr.2019.05.044
English, Scientific journal
DOI：https://doi.org/10.1016/j.jcsr.2019.05.044DOI ID：10.1016/j.jcsr.2019.05.044,
ISSN：0143-974X Development of a smart-device-based vibration-measurement system: Effectiveness examination and application cases to existing structure Ashish Shrestha; Ji Dang; Xin Wang
Structural Control and Health Monitoring,
Volume：25,
Number：3, Mar. 2018,
[Reviewed]After the 2011 Great East Japan Earthquake, long-term vibration measurement using high-density instruments is one of the most critical issues for structural-health-monitoring owing to increasing deterioration and threat of future large earthquakes. Because of the high initial and running costs of traditional monitoring systems, smart-device-based measurement system is considered as a simple and easy solution. In this paper, the effectiveness of in-built sensor, data transfer via wireless local area network, data acquisition to a synchronize cloud server, and trigger function using shaking table tests were firstly examined. A measurement system including a group of sensors has been established successfully based on the “control center” from which the trigger command can be send to other sensors immediately as any sensor/sensors is/are triggered. Then, the system is applied to seismic-response and environment-vibration measurement at existing structures. Results show that the observable acceleration level of smart devices is more than 5 gal in the frequency range of 0.1 to 10 Hz. The possible sampling rate is 100 Hz. Though it is unstable, correction methods have been proposed. Continuous measurement and data transfer is possible without data loss. Dynamic properties extracted from smart-device-based system is very similar to those extracted from high-quality-sensor-based system.
John Wiley and Sons Ltd, English, Scientific journal
DOI：https://doi.org/10.1002/stc.2120DOI ID：10.1002/stc.2120,
ISSN：1545-2263,
SCOPUS ID：85041672737 PERFORMANCE EVALUATION OF UUMANNED AERIAL VEHICLE FOR EMERGENCY BRIDGE INSPECTION AFTER EARTHQUAKEKodai ENDO; Ji DANG; Daijiro HARUTA
Journal of Japan Society of Civil Engineers, Ser. F4 (Construction and Management),
Volume：74,
Number：2,
First page：I_50,
Last page：I_61, 2018,
[Reviewed],
[Corresponding]Japan Society of Civil Engineers, Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejcm.74.i_50DOI ID：10.2208/jscejcm.74.i_50,
eISSN：2185-6605 RISK MITIGATION EFFECT OF FUNCTION SEPARATED BRIDGES UNDER DESIGN LIMITATION EXCEEDED EARTHQUAKESYuka AKIIKE; Ji DANG; Nobuhiro YAMAZAKI; Masayuki ISHIYAMA; Yuta SOMEYA
Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)),
Volume：74,
Number：4,
First page：I_955,
Last page：I_963, 2018,
[Reviewed]Japan Society of Civil Engineers, Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.74.i_955DOI ID：10.2208/jscejseee.74.i_955,
eISSN：2185-4653,
共同研究・競争的資金等ID：31687534 UNMANED INSPECTION ORIENTATED UAV BRIDGE INSPECTION AND DAMAGE DETECTION USING DEEP LEARNINGYu TABATA; Ji DANG; Daijiro HARUTA; Ashish SHRESTHA; CHUN
Journal of Japan Society of Civil Engineers, Ser. F4 (Construction and Management),
Volume：74,
Number：2,
First page：I_62,
Last page：I_74, 2018,
[Reviewed],
[Corresponding]Japan Society of Civil Engineers, Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejcm.74.i_62DOI ID：10.2208/jscejcm.74.i_62,
eISSN：2185-6605 Building damage concentrated in Longtoushan town during the 2014 Ms. 6.5 Ludian earthquake, Yunnan, China: examination of cause and implications based on ground motion and vulnerability analyses Xin Wang; Susumu Kurahashi; Hao Wu; Hongjun Si; Qiang Ma; Ji Dang; Dongwang Tao; Jiwei Feng; Kojiro Irikura
JOURNAL OF SEISMOLOGY,
Volume：21,
Number：5,
First page：1185,
Last page：1200, Sep. 2017,
[Reviewed]Though the 2014 Ludian Earthquake had only a moderate magnitude (Ms 6.5), high-level ground motions of almost 1g occurred at Longtoushan Town (seismic station 53LLT), which located near the intersection of a conjugate-shaped seismogenic fault. The building damages on the pluvial fan and the river terrace at Longtoushan was clearly different. In order to examine the generation of the large acceleration at 53LLT, the focal mechanisms and the rupture processes of the conjugate-shaped seismogenic fault were determined. We found that there were two continuous impulsive waves in the records of 53LLT that were generated from two different faults, the Baogunao fault and the Xiaohe fault, respectively. Site effects on the pluvial fan and the river terrace at Longtoushan Town and their relations to different building damages were examined. We found that the predominant period at the pluvial fan was about 0.25 s, close to the fundamental natural period of multi-story confined masonry buildings. Ground motions on the pluvial fan and the river terrace were simulated through convolving synthesized bedrock motions with the transfer functions, which were analyzed using the one-dimensional underground velocity structures identified from H/V spectral ratios of ambient noise. Building collapse ratios (CRs) are estimated based on the vulnerability function of the 2008 Wenchuan Earthquake and are compared with the observed values. We found that the observed building CRs on the pluvial fan are much higher than the estimated values. High-level ground shaking that is far beyond the design level was a reason for serious building damage.
SPRINGER, English, Scientific journal
DOI：https://doi.org/10.1007/s10950-017-9659-zDOI ID：10.1007/s10950-017-9659-z,
ISSN：1383-4649,
eISSN：1573-157X,
Web of Science ID：WOS:000407951900011 Multiple-Spring Model for Square-Section Steel Bridge Columns under Bidirectional Seismic Load Ji Dang; Huihui Yuan; Akira Igarashi; Tetsuhiko Aoki
JOURNAL OF STRUCTURAL ENGINEERING,
Volume：143,
Number：5,
First page：04017005-1,
Last page：16, May 2017,
[Reviewed]In this study, the multiple-spring (MS) model with the curve-approximated hysteresis rule is proposed for the nonlinear seismic response simulation of bidirectionally loaded hollow square-section steel columns such as cantilever type steel piers. To represent the nonlinear hysteresis behavior of the column, an effective and simple optimization procedure is introduced to identify the free parameters of the model. A parameter determination approach for approximate modeling in preliminary design calculations is also introduced. The results of quasi-static and pseudodynamic tests using bidirectional loading are compared with the simulation results to verify the accuracy of the proposed model. The proposed method is shown to be advantageous in achieving accurate simulation of the seismic response of a bridge model involving bidirectionally loaded steel columns, especially the hysteretic force-displacement relationship and time history of the dynamic response. (C) 2017 American Society of Civil Engineers.
ASCE-AMER SOC CIVIL ENGINEERS, English, Scientific journal
DOI：https://doi.org/10.1061/(ASCE)ST.1943-541X.0001735DOI ID：10.1061/(ASCE)ST.1943-541X.0001735,
ISSN：0733-9445,
eISSN：1943-541X,
Web of Science ID：WOS:000399650600019 Seismic performance estimation for bridges with aging deteriorated rubber bearings (ring shoe) by Bayesian probability inference and incremental dynamic analysis (in Japanese) Ji DANG; Taku SATO; Akira IGARASHI; Kunihiro HAYASHI; Yukio ADACHI
J. Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)),
Volume：72,
Number：4,
First page：I_542,
Last page：I_554, May 2016,
[Reviewed]DOI: 10.2208/jscejseee.72.I_542
Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.72.I_542DOI ID：10.2208/jscejseee.72.I_542,
ISSN：2185-4653 Incremental dynamic analysis for seismic response behavior of isolated bridges under bidirectional earthquake loading (in Japanese) Ji DANG; Yuki EBISAWA; Akira IGARASHI
J. Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)),
Volume：72,
Number：4,
First page：I_719,
Last page：I_732, May 2016,
[Reviewed]DOI: 10.2208/jscejseee.72.I_719
Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.72.I_719DOI ID：10.2208/jscejseee.72.I_719,
ISSN：2185-4653 DEVELOPMENT OF HYSTERETIC MODEL FOR HIGH-DAMPING RUBBER BEARINGS UNDER BI-DIRECTIONAL AND LARGE STRAIN DOMAIN LOADING Ji DANG; Akira IGARASHI; Yuta MURAKOSHI
Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)),
Volume：72,
Number：1,
First page：250,
Last page：262, 2016,
[Reviewed],
[Lead]In this study, the hysteretic behavior of High Damping Rubber (HDR) bearings under bi-directional loading condition is discussed and a new numerical model is proposed for accurate seismic response simulation of isolated bridges. The difference of hysteretic behavior of HDR under horizontal uni- and bi-directional loading was analyzed based on results of loading tests. Representative simple numerical models, such as the orthogonal combination of bi-linear hysteretic models, Multiple Shearing Spring (MSS) model and the Park-Wen model were found having significant different in simulating the tests results. As a consequence of discussion on the source of the difference of numerical and test results, a modified version of Park-Wen model is developed and proposed. The modified Park-Wen model allows effective representation of effect of the bi-directional shear strain components to the increase of hysteretic energy dissipation at high strain levels, with a minimal number of model parameters. Validity of the modified Park-Wen model is shown by comparison with bi-directional static loading test results, as well as pseudo-dynamic tests of high-damping rubber bearings.
Japan Society of Civil Engineers, Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.72.250DOI ID：10.2208/jscejseee.72.250,
ISSN：2185-4653,
eISSN：2185-4653,
CiNii Articles ID：130005148044,
共同研究・競争的資金等ID：31687538 An improved rheology model for the description of the rate-dependent cyclic behavior of high damping rubber bearings D. A. Nguyen; J. Dang; Y. Okui; A. F. M. S. Amin; S. Okada; T. Imai
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING,
Volume：77,
First page：416,
Last page：431, Oct. 2015,
[Reviewed]An improved rheology model, inspired from explicit experiments is conceived to represent rate-dependent cyclic shear behavior of high damping rubber bearings at subzero and room temperatures. Total stress has been decomposed into nonlinear rate independent elasto-plastic stress, nonlinear elastic stress and nonlinear visco-elasto-plastic overstress branches. To represent nonlinear viscosity behavior, 'overstress branch' has been generalized by putting linear elastic spring in parallel to nonlinear elasto-plastic model, placed in series with nonlinear dashpot. Constitutive relations for model elements have been designated for respective fundamental phenomenon observed in constant strain rate experiments. An optimum calculation approach is developed to determine a unique set of overstress parameters capable not only of representing constant strain rate cyclic tests but also sinusoidal tests with variable input strain rates. Essential abilities of the proposed model and adequacy of estimated parameters have been confirmed by comparing numerical simulation results with experiments conducted at -30 degrees C, -10 degrees C and 23 degrees C. (C) 2015 Elsevier Ltd. All rights reserved.
ELSEVIER SCI LTD, English, Scientific journal
DOI：https://doi.org/10.1016/j.soildyn.2015.06.001DOI ID：10.1016/j.soildyn.2015.06.001,
ISSN：0267-7261,
eISSN：1879-341X,
Web of Science ID：WOS:000360420000039 Fundamental analysis for identifying deterioration mechanism of lead rubber bearings Kunihiro HAYASHI; Yukio ADACHI; Naota SAKAMOTO; Akira IGARASHI; Ji DANG; Osamu OTANI; Toshinori SHIMOIKE
Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)),
Volume：71,
Number：4,
First page：I_525,
Last page：I_536, Sep. 2015,
[Reviewed]DOI: 10.2208/jscejseee.71.I_525
Japan Society of Civil Engineers, Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.71.I_525DOI ID：10.2208/jscejseee.71.I_525,
ISSN：2185-4653,
CiNii Articles ID：130005100262 Dynamic analysis to investigate the effect of aging deterioration of lead rubber bearings on the seismic performance of bridges Ji DANG; Tomohiro HIGASHIDE; Akira IGARASHI; Yukio ADACHI; Tomohiro HAYASHI
Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)),
Volume：71,
Number：4,
First page：I_713,
Last page：I_724, Sep. 2015,
[Reviewed]DOI: 10.2208/jscejseee.71.I_713
Japan Society of Civil Engineers, Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.71.I_713DOI ID：10.2208/jscejseee.71.I_713,
ISSN：2185-4653,
CiNii Articles ID：130005100243 Curve-Approximated Hysteresis Model for Steel Bridge Columns Ji Dang; Huihui Yuan; Akira Igarashi; Tetsuhiko Aoki
JOURNAL OF STRUCTURAL ENGINEERING,
Volume：140,
Number：9,
First page：04014058-1,
Last page：04014058-14, Sep. 2014,
[Reviewed]A curve-approximated hysteresis model of the lateral load-displacement behavior of steel bridge columns is proposed for nonlinear seismic response assessment of single-column-type bridges using single-degree-of-freedom (SDOF) analysis. Instead of multiple straight lines, a series of curves are adopted to precisely describe complicated force-displacement hysteresis behavior of the column. The P-delta effect, hardening effect in unloading-reloading hysteresis loops, deterioration of strength, and stiffness are taken into account. Parameters of proposed hysteresis model for three types of steel column specimens used in this study are calibrated by six quasi-static cyclic tests. To verify the accuracy of the proposed model, eleven pseudodynamic tests are conducted. By comparing the simulation and the test results, the differences between the predicted nonlinear seismic response using the proposed model and pseudodynamic tests are found to be, on average, 5% in maximum response displacement, 22% in residual displacement, and 4% in the amount of energy dissipation. (C) 2014 American Society of Civil Engineers.
ASCE-AMER SOC CIVIL ENGINEERS, English, Scientific journal
DOI：https://doi.org/10.1061/(ASCE)ST.1943-541X.0000970DOI ID：10.1061/(ASCE)ST.1943-541X.0000970,
ISSN：0733-9445,
eISSN：1943-541X,
Web of Science ID：WOS:000342834800014 Experimental verification for remaining performance of lead rubber bearings with aging deterioration K.Hayashi; Y.Adachi; K.Komoto; H.Yatsumoto; A.Igarashi; J.Dang; T.Higashide
Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering & Earthquake Engineering (SE/EE)),
Volume：70,
Number：4,
First page：I_1032,
Last page：I_1042, Jul. 2014,
[Reviewed]Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.70.I_1032DOI ID：10.2208/jscejseee.70.I_1032 Behavior of partially concrete-filled steel tube bridge piers under bi-directional seismic excitations Huihui Yuan; Ji Dang; Tetsuhiko Aoki
JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH,
Volume：93,
First page：44,
Last page：54, Feb. 2014,
[Reviewed]During the past decades, amounts of research efforts have been concentrated to investigate basic characteristics of the seismic response of steel bridge piers by cyclic bi-directional loading tests or finite element analysis. However, dynamic test results on partially concrete-filled steel tube (PCFST) bridge piers under coupled ground motions in two horizontal directions are insufficient. To investigate the behavior of PCFST bridge piers under bidirectional seismic excitations, a series of cyclic static loading tests and single- and bi-directional hybrid (pseudo-dynamic) loading tests for circular-section test specimens with three different concrete-filled ratios were performed in this study. The failure patterns were observed after the tests. The experimental results showed that the restoring force of PCFST bridge piers obtained in bi-directional loading tests was almost the same as that obtained in single-directional loading tests. However, deformation capacity deteriorated considerably when subjected to bi-directional dynamic loadings. This study also shows that the seismic behavior of PCFST bridge piers can be effectively improved if the concrete fill height is significantly increased. (C) 2013 Elsevier Ltd. All rights reserved.
ELSEVIER SCI LTD, English, Scientific journal
DOI：https://doi.org/10.1016/j.jcsr.2013.10.022DOI ID：10.1016/j.jcsr.2013.10.022,
ISSN：0143-974X,
eISSN：1873-5983,
Web of Science ID：WOS:000331348400005 Pseudo-dynamic testing for seismic performance assessment of buildings with seismic isolation system using scrap tire rubber pad isolators
H.K. Mishra; A. Igarashi; J. Dang; H. Matsushima
Journal of Civil Engineering and Architecture, Volume：8, Number：1, First page：73, Last page：80, Jan. 2014, [Reviewed]
English, Scientific journal
A Curves Approximated Multiple-Spring Model for Bi-Directional Seismic Response Simulation of Steel Bridge Piers Ji Dang; Huihui Yuan; Akira Igarashi; Tetsuhiko Aoki
Journal of Japan Society of Civil Engineers A2 (Applied Mechanics (AM)),
Volume：69,
Number：2,
First page：391,
Last page：402, Aug. 2013,
[Reviewed]Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejam.69.I_391DOI ID：10.2208/jscejam.69.I_391 Influence of loading direction on the seismic performance of rectangular STRP isolators Akira Igarashi; Hiroshi Matsushima; Ji Dang
Journal of Japan Society of Civil Engineers A2 (Applied Mechanics),
Volume：69,
Number：2,
First page：425,
Last page：433, Aug. 2013,
[Reviewed]Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejam.69.I_425DOI ID：10.2208/jscejam.69.I_425 Bidirectional loading hybrid tests of square cross-sections of steel bridge piers Ji Dang; Tetsuhiko Aoki
EARTHQUAKE ENGINEERING & STRUCTURAL DYNAMICS,
Volume：42,
Number：8,
First page：1111,
Last page：1130, Jul. 2013,
[Reviewed]Steel rectangular section columns with stiffened plates are commonly used for elevated highway bridges in the urban areas of Japan. The seismic design of bridge piers is usually performed by dynamic analysis in the horizontal direction using various independent directional seismic acceleration data. However, this simple treatment does not reflect the effect of bilateral loading as a structural response to inelastic interaction. In this study, unidirectional and bidirectional loading hybrid tests were conducted to examine the seismic response and performance of square cross-sections of steel bridge piers subjected to bidirectional seismic accelerations. Comparison of the results of unidirectional and bidirectional loading tests revealed that the maximum load is the same as the average of unidirectional loading in the NS and EW directions; however, the maximum response displacement and residual displacement increase in proportion with hard to soft ground types. Moreover, a modified seismic design is proposed considering these bidirectional loading effects. Copyright (c) 2012 John Wiley & Sons, Ltd.
WILEY-BLACKWELL, English, Scientific journal
DOI：https://doi.org/10.1002/eqe.2262DOI ID：10.1002/eqe.2262,
ISSN：0098-8847,
Web of Science ID：WOS:000318912700001 Experimental study of the seismic behavior of partially concrete-filled steel bridge piers under bidirectional dynamic loading Huihui Yuan; Ji Dang; Tetsuhiko Aoki
Earthquake Engineering and Structural Dynamics,
Volume：42,
Number：15,
First page：2197,
Last page：2216, 2013,
[Reviewed]SUMMARY: The seismic behavior of steel bridge piers partially filled with concrete under actual earthquake conditions was investigated by using 20 square section specimens subjected to static cyclic loading tests and single-directional and bidirectional hybrid loading tests. Acceleration records of two horizontal NS and EW directional components for hard (GT1), medium (GT2), and soft grounds (GT3), obtained during the 1995 Kobe earthquake, were adopted in dynamic tests. Experimental results clearly showed that maximum and residual displacements under actual earthquake conditions cannot be accurately estimated by conventional single-directional loading tests, especially for GT2 and GT3. A modified admissible displacement was proposed on the basis of bidirectional loading test results. The concrete fill can effectively improve the seismic resistance performance if the concrete inside the steel bridge piers is sufficiently high in quantity. © 2013 John Wiley &
Sons, Ltd.
John Wiley and Sons Ltd, English, Scientific journal
DOI：https://doi.org/10.1002/eqe.2320DOI ID：10.1002/eqe.2320,
ISSN：1096-9845,
SCOPUS ID：84887134505 LOADING TESTS AND INVESTIGATION OF ANALYTICAL MODELS FOR BI-DIRECTIONAL RESTORING FORCE RESPONSE OF ELASTOMERIC BEARINGS Akira IGARASHI; Ji DANG; Yuta MURAKOSHI; Toshihiko ITO
Journal of JSCE,
Volume：Vol.69,
Number：No.4, 2013,
[Reviewed]Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.69.I_311DOI ID：10.2208/jscejseee.69.I_311 A Framework for Performance-Based Seismic Design Approach for Developing Countries, A Case study of Syria Ahmed ALHOURANI; Ji DANG; Takeshi KOIKE
Journal of Japan Society of Civil Engineers, Ser. A1 (Structural Engineering ^|^ Earthquake Engineering (SE/EE)),
Volume：69,
Number：4,
First page：I_195,
Last page：I_206, 2013
Japan Society of Civil Engineers, English, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.69.i_195DOI ID：10.2208/jscejseee.69.i_195,
eISSN：2185-4653 An Approximated Curve Hysteretic Restoring Force Model for Steel Bridge Piers and Experimental Verification
Ji Dang; Tetsuhiko Aoki
Journal of Japan Society of Civil Engineers A2 (Applied Mechanics), Volume：Vol.68, Number：No.2, First page：I-495, Last page：I-504, Aug. 2012, [Reviewed]
Japanese, Scientific journal
DOI ID：10.2208/jscejam.68.I_495, CiNii Articles ID：40019809028, CiNii Books ID：AA12446272
EXPERIMENTAL STUDY FOR SEISMIC SECURITY OF STEEL BRIDGE PIERS UNDER BIDIRECTIONAL GROUND MOTION EXCITATION Ji Dang; Tetsuhiko Aoki; Akira Igarashi
Journal of Japan Society of Civil Engineers A1S (Earthquake Engineering),
Volume：Vol.68,
Number：No.4,
First page：p.627,
Last page：641, Aug. 2012,
[Reviewed]Japanese, Scientific journal
DOI：https://doi.org/10.2208/jscejseee.68.I_627DOI ID：10.2208/jscejseee.68.I_627 Bi-directional loading hybrid test of square section steel piers Ji Dang; Tarou Nakamura; Tetsuhiko Aoki; Moriaki Suzuki
Journal of Structural Engineering, JSCE,
Volume：Vol.56A,
First page：367,
Last page：380, Mar. 2010,
[Reviewed]Japanese, Scientific journal
DOI：https://doi.org/10.11532/structcivil.56A.367DOI ID：10.11532/structcivil.56A.367,
CiNii Articles ID：40017447583
A Multi-Layer Thermal Coupling Hysteric Model for High Damping Rubber Bearings at Low Temperature
Jie Shen; Akira Igarashi; Ji Dang; Yuki Hamada; Takehiko Himeno; Hiroshi Shinmyo
Proceeding of 18th World Conference on Earthquake Engineering (18th WCEE), Volume：18, Sep. 2024, [Reviewed]
English, Introduction international proceedings
Hybrid Quantum-Classical Convolutional Neural Network for Multiclass Damage Prediction of Buildings
Sanjeev Bhatta; Ji Dang
Proceeding of 18th World Conference on Earthquake Engineering (18th WCEE), Volume：18, Sep. 2024, [Reviewed], [Last]
English, Introduction international proceedings
Experimental Studies for Silicone Rubber Based Seismic Isolation Bearing Performance Assessment
Arthur Ramandalina; Ji Dang; Yohei Suzuki
Proceeding of 18th World Conference on Earthquake Engineering (18th WCEE), Volume：18, Sep. 2024, [Reviewed]
English, Introduction international proceedings
Heating and Thermal Conductivity Effect Inside High Damping Rubber Bearing at Low Temperature
Jie Shen; Akira Igarashi; Ji Dang; Yuki Hamada; Takehiko Himeno; Hiroshi Shinmyo
Proceeding of IABSE Symposium Manchester 2024, First page：904, Last page：912, Apr. 2024, [Reviewed]
English, Introduction international proceedings
Bridge Damage Cause Estimation Using Multiple Images Based on Visual Question Answering. Tatsuro Yamane; Pang-jo Chun; Ji Dang; Takayuki Okatani
arXiv,
Volume：abs/2302.09208, 2023
English
DOI：https://doi.org/10.48550/arXiv.2302.09208DOI ID：10.48550/arXiv.2302.09208,
DBLP ID：journals/corr/abs-2302-09208 Bridge Status Realization and Management Enhanced by UAV, SfM, and Deep Learning Katrina Mae Montes; Ji Dang; Jiaming Liu; Pang jo Chun
Lecture Notes in Civil Engineering (Proc. EVACES 2023), 2023
The next generation of bridge structure status management system can be implemented by integrating small size unmanned aerial vehicle (UAV) to easily access some parts of the bridge and cut the cost of expensive equipment’s, 3D model reconstruction using Structure from Motion (SfM) photogrammetry, and Deep Learning methods for damage detection. These techniques were integrated in this study to construct a seamlessly enhanced bridge visual inspection system. A preliminary discussion was conducted to detect visual damages using DeepLabv3+ in a 2-dimensional bridge inspection images captured by the UAV video and incorporate it into the generated bridge 3D model. A benchmark case study was conducted for a two-span steel bridge with severe corrosion damage, and the result shows the bridge 3D model with corrosion damages. A mixed reality platform was also demonstrated to view and save the 3D model virtually which can be used for easily deterioration assessment and maintenance evaluation.
English, Introduction international proceedings
Scopus：https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85132993255&origin=inwardScopus Citedby：https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85132993255&origin=inward Prediction of Damage State of Rc Buildings Using Machine Learning
Sanjeev BHATTA; Ji DANG
8th World Conference on Structural Control and Monitoring, Jun. 2022
English
Digital Transformation Bridge Inspection Platform With AI, UAV, MR, And SfM For An Advance Structural Health Monitoring
Katrina Mae; MONTES; Ji DANG; Pang-Jo CHUN; Jiaming LIU
8th World Conference on Structural Control and Monitoring (8WCSCM), Jun. 2022
English
Nonlinear behavior identification of HDR-S bearing using neural network for seismic structural design
Katrina Montes; Ji Dang; Akira Igarashi; Yuqing Tan; Takehiko Himeno
IABSE Symposium Prague 2022 - Challenges for Existing and Oncoming Structures, May 2022
English
A thermo-mechanical coupled model of hysteresis behavior of HDR bearings Yuqing Tan; Akira Igarashi; Ji Dang; Takehiko Himeno; Yuki Hamada
IABSE Symposium Prague 2022 - Challenges for Existing and Oncoming Structures, May 2022
Springer International Publishing, English
DOI：https://doi.org/10.1007/978-3-030-93236-7_27 Hybrid Simulation for Seismic Isolation Effectiveness Assessment of HDR Bearings at Low Temperature
Yuqing Tan; Ji Dang; Akira Igarashi; Takehiko Himeno; Yuki Hamada; Yoshifumi Uno
Lecture Notes in Civil Engineering (Proc. EVACES 2021), Jul. 2021
Springer International Publishing, English, Introduction international proceedings
Probability distribution of ultimate strain for aging deteriorated rubber bearings by Bayesian estimation J. Dang; A. Igarashi; K. Hayashi
Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations, Proceedings of the Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020),
First page：1008,
Last page：1013, 26 Mar. 2021
CRC Press, English, Introduction international proceedings
DOI：https://doi.org/10.1201/9780429279119-136DOI ID：10.1201/9780429279119-136 Mixed training of deep convolutional neural network for bridge deterioration detection with UAV and inspection report sourced images J. Dang; P. Chun
Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations Proceedings of the Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020),
First page：308,
Last page：312, 26 Mar. 2021
CRC Press, English, Introduction international proceedings
DOI：https://doi.org/10.1201/9780429279119-38DOI ID：10.1201/9780429279119-38 Bridge damage cropping-and-stitching segmentation using fully convolutional network based on images from UAVs Jiyuan Shi; Ji Dang; Rongzhi Zuo
Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations Proceedings of the Tenth International Conference on Bridge Maintenance, Safety and Management (IABMAS 2020),
First page：264,
Last page：270, 26 Mar. 2021
CRC Press
DOI：https://doi.org/10.1201/9780429279119-32DOI ID：10.1201/9780429279119-32 Bridge Damage Detection and Segmentation by Deep Learning for Bridge UAV Insepction
Jiyuan Shi; Mida Cui; Rongzhi Zuo; Ji Dang
Proceeding of 17 WCEE, Volume：17, First page：9c-0027-1, Last page：9, Sep. 2020, [Reviewed], [Last, Corresponding]
English
Artificial Neural Network Based Structural Seismic Damage Detection from Monitoring Acceleration Data
Nikesh Maharjan; Ji Dang; Ashish Shrestha
Proceeding of 17 WCEE, Volume：17, First page：9c-0012-1, Last page：12, Sep. 2020, [Reviewed], [Corresponding]
English
Smartphones and Deep Learning Integrated System for Low-Cost Real-Time Bridge Vibration Status Realization
Ashsih Shretha; Ji Dang
Proceeding of 17 WCEE, Volume：17, First page：9c-0005-1, Last page：12, Sep. 2020, [Reviewed], [Last]
English
Fracture Identification of Steel Structures from Waveforms Using A Convolutional Neural Networks
Xin Wang; Luyao Wang; Ji Dang
Proceeding of 17 WCEE, Volume：17, First page：9c-0004-1, Last page：10, Sep. 2020, [Reviewed], [Last]
English
Time Control and Experimental Verification of IoT based Structural Seismic Monitoring
Ji Dang; Rongzhi Zuo
Proceeding of 17 WCEE, Volume：17, First page：9a-0003-1, Last page：12, Sep. 2020, [Reviewed], [Lead, Corresponding]
English
Real-time Hybrid Experiment of “CaSS” for Function Separate
N. Yamazaki; J. Dang; Y. Akiike; M. Ishiyama; Y. Someya
Proceeding of 17 WCEE, Volume：17, First page：2g-0186-1, Last page：12, Sep. 2020, [Reviewed]
English
Bridge Damage Classification and Detection Using Fully Convolutional Neural Network Based on Images From UAVs
Jiyuan Shi; Rongzhi Zuo; Ji Dang
Proceedings of 8th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES 2019), Volume：8, Number：1, First page：1, Last page：7, Sep. 2019, [Reviewed], [Last]
English, Introduction international proceedings
Pseudo Damage Training for Seismic Fracture Detection Machine
Luyao Wang; Ji Dang; Xin Wang
Proceeding of the 8th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES 2019), Volume：8, Number：1, First page：1, Last page：7, Sep. 2019, [Reviewed]
English, Introduction international proceedings
Development and Experimental Verification of IoT Sensing Based Structural Seismic Monitoring System
Rongzhi. Zuo; Ji Dang; Chandra.S. Goi
Proceeding of the 8th International Conference on Experimental Vibration Analysis for Civil Engineering Structures (EVACES 2019), Volume：8, Number：1, First page：1, Last page：8, Sep. 2019, [Reviewed]
English, Introduction international proceedings
Bridge Damage Detection Using Unmanned Arial Vehicle and Deep Convolutional Neural Network
Ji Dang; Ashish Shrestha; Pong-Jo Chun
Proceedings of the 7th Asia Conference on Earthquake Engineering, Volume：7, Number：1, First page：1, Last page：8, Nov. 2018, [Reviewed], [Lead]
English, Introduction international proceedings
Site Verification Tests for UAV Bridge Inspection and Damage Image Detection Based on Deep Learning
Ji Dang; Ashish Shrestha; Daijiro Haruta; Yu Tabata; Pong-Jo Chun; Kazuaki Okubo
Proceeding of the 7th World Conference on Structural Control and Monitoring, Volume：7, Number：1, First page：1548, Last page：1557, Jul. 2018, [Reviewed], [Lead]
English, Introduction international proceedings
Field Implementation of Image Process Based Real-Time Bridge Displacement Monitoring using Smart Devices
Ashish Shrestha; Ji Dang; Keisuke Nakajima; Xin Wang
Proceeding of the 7th World Conference on Structural Control and Monitoring, Volume：7, Number：1, First page：2122, Last page：2129, Jul. 2018, [Reviewed]
English, Introduction international proceedings
LOW COST BRIDGE SEISMIC MONITORING APPLYING USED SMART PHONES AND CLOUD SERVER
Ji Dang; Ashish Shrestha; Xin Wang; Shogo Matsunaga; Pang-jo Chun; Shingo Asamoto
Proceedings of Eleventh U.S. National Conference on Earthquake Engineering, First page：1124, 2018, [Reviewed]
English
Smart Seismic Response and Health Monitoring System for Takamatsu Bridge
Ashish Shrestha; Ji Dang; Xin Wang; Shogo Matsunaga; Pang-jo Chun
Proceedings of The 13th International Workshop on Advanced Smart Materials and Smart Structures Technology, Jun. 2017
English
Performance Evaluation of Unmanned Aerial Vehicle for Bridge Inspection and Application in 2016 Kumamoto Earthquake
Ji Dang; Kodai Endo; Shogo Matsunaga; Akira Kasai
Proceedings of the 3rd Huixian International Forum on Earthquake Engineering for Young Researchers, Volume：3, Number：247, First page：1, Last page：8, 2017, [Reviewed], [Lead]
English, Introduction international proceedings
Experimental Evaluation of Seismic Residual Performance for Deteriorated Rubber Bearings in Highway Bridges
Kunihiro Hayashi; Yukio Adachi; Naota Sakamoto; Akira Igarashi; Ji Dang
Proc. Joint 6th International Conference on Advances in Experimental Structural Engineering (6AESE) and 11th International Workshop on Advanced Smart Materials and Smart Structures Technology (11ANCRiSST), Volume：11, Number：220, First page：1, Last page：8, Aug. 2015
Urbana, USA, 8/1-2, University of Illinois at Urbana-Champaign
English
Rate Dependent Behavior of High Damping Rubber Bearings in Low Temperature and Rheology Model
Ji Dang; Nguyen Dung; Yoshiaki Okui; Takashi Imai; Shinya Okata
Proceedings of IABSE Conference Elegance in Structures, Volume：NS21, First page：1, Last page：7, 2015, [Reviewed], [Lead]
English, Introduction international proceedings
A statistical study for bi-directional seismic interaction effect in isolated bridges
Ji Dang; Yuki Ebisawa; Akira Igarashi
Proc. 13th International Symposium on New Technologies for Urban Safety of Mega Cities in Asia (USMCA 2014), Nov. 2014
English
Incremental Dynamic Analysis for Bi-directional Seismic Performance of Isolated Bridges
Yuki Ebisawa; Ji Dang; Akira Igarashi
Proceedings of the 5th Asia Conference on Earthquake Engineering (5ACEE), Volume：5, Number：19-003, First page：1, Last page：7, Oct. 2014
English, Introduction international proceedings
Experimental Evaluation of Aging Deterioration of Rubber Bearings in Highway Bridges
Kunihiro HAYASHI; Yukio ADACHI; Akira IGARASHI; Ji DANG
Proc. 2nd European Conference on Earthquake Engineering and Seismology (2ECEES), Aug. 2014
English
Incremental dynamic analysis and statistical evaluation for bi-directional seismic interaction of isolated structures
J. Dang; Y. Ebisawa; A. Igarashi
1st Huixian International Forum on Earthquake Engineering for Young Researchers, Aug. 2014
English
Multiple-spring model analysis for square-sectional steel bridge columns J. Dang; H. Yuan; T. Aoki; A. Igarashi
Proc. 10th Pacific Structural Steel Conference (PSSC2013), Oct. 2013
DOI: 10.3850/978-981-07-7137-9_099
Singapore, 10/8-11, ISBN:978-981-07-7137-9
English
DOI：https://doi.org/10.3850/978-981-07-7137-9_099 Simplified Performance-Based Seismic Design Approach for Developing Countries, Syria as Case Study
Ahmed Alhourani; Mahiro Onuki; Ji Dang; Takeshi Koike
Proceedings of the 13th East Asia-Pacific Conference on Structural Engineering, Volume：13, Number：D-1-4, First page：1, Last page：8, 2013
English, Introduction international proceedings
Nonlinear numerical hysteresis model for bidirectionally loaded elastomeric isolation bearings
Ji Dang; Akira Igarashi; Yuta Murakoshi
Proc. 2nd International Symposium on Earthquake Engineering, 2013
English
Experimental validation of bi-directional numerical modeling for elastomeric isolation bearings
Ji Dang; Akira Igarashi; Yuta Murakoshi
Proc. 1st International Symposium on Earthquake Engineering, JAEE, Nov. 2012
English
Bi-directional experimental hybrid simulations of elastomeric isolation bearings for validation of hysteretic modeling
Yuta Murakoshi; Akira Igarashi; Dang Ji; Toshihiko Ito
Proc. 15th World Conference on Earthquake Engineering (15WCEE), Volume：15, Sep. 2012, [Reviewed]
English
A curves approximated multiple-spring model seismic response simulation for square-section steel bridge piers
Ji Dang; Akira Igarashi; Tetsuhiko Aoki
Proc. 15th World Conference on Earthquake Engineering (15WCEE), Volume：15, First page：77, Last page：86, Sep. 2012, [Reviewed]
English
CiNii Articles ID：40019808995, CiNii Books ID：AA12446272
Bi-directional Loading Hybrid Test of Square Section Steel Piers
Tetsuhiko Aoki; Ji Dang; Moriaki Suzuki
Proceedings of the 14th European Conference on Earthquake Engineering, Volume：14, First page：13, Last page：20, 2010, [Reviewed]
English, Introduction international proceedings
The Cubic Curves Hysteresis Model of Steel Bridge Piers for Seismic Response Simulation
Ji Dang; Tetsuhiko Aoki
Proceedings of the 9th Pacific Structure Steel Conference, Volume：9, First page：1139, Last page：1151, 2010, [Reviewed], [Invited], [Lead]
English, Introduction international proceedings
Dynamic Shear Tests of Low-yield Steel Panel Dampers for Bridge Bearing Tetsuhiko Aoki; Ji Dang; Chaofeng Zhang; Tatsumasa Takaku; Yushi Fukumoto
Proceedings of the 6th International Conference on Behavior of Steel Structures in Seismic Areas (STESSA 2009),
Volume：6,
Number：1,
First page：27,
Last page：31, 03 Dec. 2009,
[Reviewed]CRC Press, English, Introduction international proceedings
DOI：https://doi.org/10.1201/9780203861592DOI ID：10.1201/9780203861592
A Rate-Dependent Thermo-Mechanical Coupling Hysteretic Model for Lead High Damping Rubber Bearings At Low Temperature
Jie SHEN; Ji DANG; Akira IGARASHI; Yuki HAMADA; Takehiko HIMENO
15th Infrastructure Lifeline Disaster Mitigation Symposium, Jan. 2025
English
能登半島地震における橋梁等 構造物被害調査におけるUAV と紐カメラの活用
水野 千里; 松永 昭吾; 渡辺 学歩; 鵜木 和博; 荒; 木 和幸
Sep. 2024
Japanese
Timoshenko Beam モデルに基づく波動干渉法による超高層 建物の上部構造の同定
王欣; Aijia ZHANG; 党紀
Sep. 2024
Japanese, Oral presentation
UAV の広域航空画像による珠洲市鵜飼地区における建物 の全壊率および瓦礫量の推定
段布賀; 王欣; 党紀; 仁田佳宏
Sep. 2024
Japanese, Oral presentation
System Identification of High-rise Buildings Based on Timoshenko Beam model: Application to a Shake-table Test of an 18-story Steel Building
Aijia ZHANG; Xin WANG; Ji DANG
AIJ Annual Meeting 2024, Sep. 2024
English, Oral presentation
EXPERIMENTAL STUDY ON SILICONE RUBBER BEARING FOR BRIDGE ISOLATION
Arthur Miharivo; RAMANDALINA; Ji DANG
Sep. 2024
English, Oral presentation
Bridge Bearings Traffic Deformation Waveform Extraction using Consensus Motif Search
RONGZHI ZUO; Ji Dang; Kazuhiro Shimizu; Akira Tsunoda; Wataru Fujita
JSCE Annual Meeting 2024 International Session (Summer Symposium), Sep. 2024
English, Oral presentation
小数実橋写真による再学習を用いた損傷認識AIの精度向上の検討
吉田 健人; 藤嶋 斗南; 党 紀
Sep. 2024
Japanese, Oral presentation
FMS合金を用いたせん断パネルダンパーの制振性能実験
川上 泰佑; 党 紀; Jiale Li
Sep. 2024
Japanese, Oral presentation
建設産業における海外出身技術者の働く実態に関する調査研究～その４アンケート調査結果～
ティ ハ; シャリスタ アシシ; 党 紀; 劉 翠平; 大浦 雅幸
Sep. 2024
Japanese, Oral presentation
能登半島地震における橋梁等構造物被害調査における UAV と紐カメラの活用
水野千里; 党紀; 王欣; 松永昭吾; 渡辺学歩; 鵜木和博; 荒木和幸
Jul. 2024
Japanese, Oral presentation
低温環境下の SPR-S 支承のための Double-Target モデルおよび実時間ハイブリッド実験を用いた検証
鍋島信幸; 党紀; 濱田由記; 姫野岳彦; 新名裕; 五十嵐晃; 沈捷
Jul. 2024
Japanese, Oral presentation
Human-AI interaction for bridge damage detection in UAV image and 3D Model
Ji Dang
The First International Symposium on Urban Lifeline, Jul. 2024, [Invited]
English, Invited oral presentation
BRIDGE 3D MODEL RECONSTRUCTION FROM UA V VIDEOS AND DAMAGE SEGMENTATION PROJECTION
Ji Dang
Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC 2024), May 2024
English, Oral presentation
BRIDGE STRUCTURE MAINTENANCE AND DISASTER MITIGATION USING UA V AND AI-HUMAN INTERACTION
Ji Dang; Tonan Fujishima; Pang-jo Chun
Engineering Mechanics Institute Conference and Probabilistic Mechanics & Reliability Conference (EMI/PMC 2024), May 2024
English, Oral presentation
MULTI-HAZARD MONITORING AND WARNING SYSTEM BASED ON LOW-COST IOT DEVICES
Sanjeev BHATTA; Ji DANG
The 16th Japan Earthquake Engineering Symposium, Nov. 2023
English, Oral presentation
RECOGNITION OF DAMAGES FROM WAVE PROPAGATION BETWEEN TWO ADJACENT FLOORS USING CNN
Aijia ZHANG; Xin W ANG; Ji DANG
The 16th Japan Earthquake Engineering Symposium, Nov. 2023
English, Oral presentation
MACHINE LEARNING-BASED SEISMIC DAMAGE PREDICTION OF BUILDINGS AT A REGIONAL SCALE
Sanjeev BHATTA; Xiandong KANG; Ji DANG
The 16th Japan Earthquake Engineering Symposium, Nov. 2023
English, Oral presentation
EXPERIMENTAL STUDY ON SILICONE RUBBER BASED SEISMIC ISOLATION BEARING
Arthur RAMANDALINA; Ji DANG; Yōhei SUZUKI
The 16th Japan Earthquake Engineering Symposium, Nov. 2023
English, Poster presentation
低温環境下での免震支承を対象とした実時間ハイブリッド実験
鍋島 信幸; 党; 紀; 濱田 由記; 姫野 岳彦; 新名 裕; 五十嵐; 沈 捷
Sep. 2023
Japanese, Oral presentation
Experimental study on seismic isolation bearings made from silicone rubber
Arthur RAMANDALINA; Ji DANG; Yohei SUZUKI
43rd Earthquake Engineering Symposium JSCE, Sep. 2023
English, Oral presentation
Utilizing Image Captioning for Earthquake Damage Assessment
Osama ABBAS; Ji DANG
43rd Earthquake Engineering Symposium JSCE, Sep. 2023
English, Oral presentation
シリコーンゴムを用いた次世代免震ゴム支承の性能実験
鈴木陽平; 党紀
Sep. 2023
Japanese, Oral presentation
Wave Field Changes in Buildings Due to Damages and Automatic Recognition Using CNN Models -Part II: CNN model construction and validation with shake table data-
Aijia ZHANG; Xin WANG; Ji DANG
AIJ Annual Meeting 2023, Sep. 2023
English, Oral presentation
被害により建物の波動場変化および CNN モデルを用いた自動認識 －その１ 波動場の再構築および各階での経時変化－
王 欣; Zhang Aijia; 党 紀
Sep. 2023
Japanese, Oral presentation
CNN を用いた外観画像による建物情報の自動識別モデルの構築
杉永 萌夏; 会員外 党
Sep. 2023
Japanese, Oral presentation
YOLO による建物屋内のひび割れ検知
仁田 佳宏; 王 欣; 会員外 稲村; 党 紀
Sep. 2023
Japanese, Oral presentation
Effective data pre-processing methods of anomaly detection for bridge bearings
Rongzhi Zuo; Ji Dang
JSCE Annual Meeting 2023 International Session (Summer Symposium), Sep. 2023
English, Oral presentation
A Multi-Layer Thermal Coupled Hysteretic Model for High Damping Rubber Bearings at Low Temperature
Jie Shen; Akira Igarashi; Ji Dang; Yuki Hamada; Takehiko Himeno; Hiroshi Shinmyo; Nobuyuki Nabeshima
JSCE Annual Meeting 2023 International Session (Summer Symposium), Sep. 2023
English, Oral presentation
AN APPROACH TO RAPID POST-EARTHQUAKE DAMAGE PREDICTION USING MACHINE LEARNING AND IOT DEVICES
BHATTA SANJEEV; Ji Dang
JSCE Annual Meeting 2023 International Session (Summer Symposium), Sep. 2023
English, Oral presentation
複数画像に基づく検出結果のばらつきを考慮した損傷の3Dマッピング
山根 達郎; 全 邦釘; 党 紀; 本田 利器
Sep. 2023
Japanese, Oral presentation
UAV画像における橋梁複数損傷セグメンテーション
藤嶋 斗南; 党 紀
Sep. 2023
Japanese, Oral presentation
YOLOv7を用いた橋梁のリアルタイム損傷認識
稲村 啓; 党 紀
Sep. 2023
Japanese, Oral presentation
UAVを活用した橋梁 3Dモデルの作成
劉 佳明; 党 紀; 藤嶋 斗南; 中島 隆志; 松永 昭吾; 林 訓裕
Sep. 2023
Japanese, Oral presentation
低温環境下でのスプリング拘束型鉛プラグ入り高減衰積層ゴム支承の実時間ハイブリッド実験
鍋島 信幸; 党 紀; 濱田 由記; 姫野 岳彦; 新名 裕; 五十嵐 晃; 沈 捷
Sep. 2023
Japanese, Oral presentation
低温環境下でのスプリング拘束型鉛プラグ入り高減衰積層ゴム支承の実時間ハイブリッド実験
鍋島信幸; 党紀; 濱田由記; 姫野岳彦; 新名裕; 五十嵐晃; 沈捷
Jul. 2023
Japanese, Oral presentation
低温時高減衰ゴム支承を用いた免震橋のハイブリッド実験
党紀; 談雨晴; 五十嵐晃; 姫野岳彦; 濱田由記; 鵜野禎史
第23回橋梁等の耐震設計シンポジウム講演論文集, Jan. 2021
Jan. 2021 - Jan. 2021, Japanese
Low temperature hybrid simulations for high damping rubber bearings
Yuqing TAN; Ji DANG; Akira IGARASHI; Takehiko HIMENO; Yuki HAMADA; Yoshifumi UNO
第11回インフラ・ライフライン減災対策シンポジウム講演集, Jan. 2021
Jan. 2021 - Jan. 2021, English
Nonlinearity Recognition Using 2-Layer Neural Network for Design of New Type of Rubber Bearings
Katrina MONTES; Ji DANG
第11回インフラ・ライフライン減災対策シンポジウム講演集, Jan. 2021
Jan. 2021 - Jan. 2021, English
IoT センシングによる橋梁支承の変位モニタリング手法の開発
Zuo Rongzhi, 党紀, 鵜野禎史, 清水和弘, 鈴木康寛
第11回インフラ・ライフライン減災対策シンポジウム講演集, Jan. 2021
Jan. 2021 - Jan. 2021, Japanese
Seismic Risk Analysis and Hybrid Simulation for Function Separation Bridge
J. Dang; Y. Akiike; N. Yamazaki
The Third International Bridge Seismic Workshop, Oct. 2019
Oct. 2019 - Oct. 2019, English
共同研究・競争的資金等ID：31687534
Real-time Hybrid Simulation for Seismic Performance of “CaSS” Dampers
党 紀; 秋池 佑香; 山崎 信宏
第 22 回橋梁等の耐震設計シンポジウム, Jul. 2019
Jul. 2019 - Jul. 2019, Japanese
共同研究・競争的資金等ID：31687534
複合型免震支承(SPRS)の復元力特性に関する実大ハイブリッド実験
党紀; 高橋良和; 五十嵐晃; 鵜野禎史; 高井博之; 秋池佑香; 宇津木太一
Jul. 2019
Jul. 2019 - Jul. 2019, Japanese
21085 Development of a Low-cost Building Damage Detection System Using Smart Devices
Xin WANG; Luyao Wang; Ji Dang
AIJ Annual meeting, Jul. 2018
Jul. 2018 - Jul. 2018, English
経年劣化ＬＲＢを有する高架道路橋の地震リスク評価
林訓裕; 五十嵐晃; 足立幸郎; 党紀
Sep. 2017
Sep. 2017 - Sep. 2017, Japanese
九州大学，9/11-13
Seismic Response and Health Monitoring System for Takamatsu Bridge using Smart Devices
Ashish Shrestha; Ji Dang; Xin Wang; Shogo Matsunaga; Pang-jo Chun
Jul. 2017
Jul. 2017 - Jul. 2017, English
Bridge Health Monitoring System Based on Smart Devices in Takamatsu Bridge
Ashish Shrestha; Ji Dang; Xin Wang; Shogo Matsunaga; Shingo Asamoto; Okubo Kazuaki; Pang-jo Chun
Proceedings of 2nd JSCE-CICHE Joint Workshop, 2017
2017 - 2017, English
Bi-directional seismic fragility curves of steel bridge piers based on incremental dynamic analysis
Yanyan Liu; Ji Dang; Akira Igarashi
Proc. 29th KKHTCNN Symposium on Civil Engineering, Dec. 2016
Dec. 2016 - Dec. 2016, English
Hong Kong, China, 12/3-5
経年劣化免震ゴム支承の耐震性能評価に関する解析的検討
林訓裕; 五十嵐晃; 党紀; 足立幸郎
Sep. 2016
Sep. 2016 - Sep. 2016, Japanese
東北大学，9/7-9，土木学会
LRBの経年劣化を考慮した地震リスク評価に基づく道路橋の耐震性能評価
林訓裕; 五十嵐晃; 党紀; 足立幸郎
Jul. 2016
Jul. 2016 - Jul. 2016, Japanese
土木学会，7/12-13，土木学会地震工学委員会
Uncertainty of aging deteriorated rubber bearingand its Bayesian probability estimation
Ji Dang; Taku Sato; Akira Igarashi; Kunihiro Hayashi; Yukio Adachi
JAEE Annual Conference and International Symposium on Earthquake Engineering 2015, Nov. 2015
Nov. 2015 - Nov. 2015, English
Tokyo, Japan, 11/19-20, JAEE
Incremental Dynamic Analysis for bi-directional seismic performance of isolated bridge
Ji Dang; Yuki EBISAWA; Akira IGARASHI
Proc. 35th JSCE Earthquake Engineering Symposium, Oct. 2015
Oct. 2015 - Oct. 2015, Japanese
Probability estimation of ultimate strain of aging deteriorated rubber bearing (ring shoe) by Beysian method (in Japanese)
Ji DANG; Taku SATO; Akira IGARASHI; Kunihiro HAYASHI; Yukio ADACHI
Proc. 35th JSCE Earthquake Engineering Symposium, Oct. 2015
Oct. 2015 - Oct. 2015, Japanese
スマートデバイスを用いた構造の地震応答計測のための性能確認実験
党紀; 菊池友介; Ashish SHRESTHA
第 18 回性能に基づく橋梁等の耐震設計に関するシンポジウム, Jul. 2015
Jul. 2015 - Jul. 2015, Japanese
ベイズ法に基づいた劣化支承の終局ひずみの確率分布推定
党紀; 佐藤拓; 五十嵐晃; 足立幸郎; 林訓裕
第18回性能に基づく橋梁等の耐震設計に関するシンポジウム講演論文集, Jul. 2015
Jul. 2015 - Jul. 2015, Japanese
Low Price Seismic and Structural Response Measurement Method Using Smart Devices
Ji Dang; Xin Wang; Ashish Shrestha; Yusuke Kikuchi
2015 Annual Meeting Seismological Society of America (SSA), Apr. 2015
Apr. 2015 - Apr. 2015, English
Statistical evaluation of dynamic response for isolated bridges under bi-directional seismic loading
Ji DANG; Yuki EBISAWA; Akira IGARASHI
Proc. 14th Japan Earthquake Engineering Symposium (14JEES), Dec. 2014
Dec. 2014 - Dec. 2014, English
Experimental evaluation of remaining performance and aging deterioration of elastomeric bridge bearings with natural rubber
Masaaki Hamano; Akira Igarashi; Kunihiro Hayashi; Yukio Adachi; Ji Dang
Proc. 27th KKHTCNN Symposium on Civil Engineering, Nov. 2014
Nov. 2014 - Nov. 2014, English
Shanghai, China, 11/10-12
漸増動的解析(IDA)による経年劣化されたゴム支承（LRB）を有する橋梁構造の性能評価
党紀; 東出知大; 五十嵐晃; 足立幸郎; 林訓裕
第34回地震工学研究発表会講演論文集, Oct. 2014
Oct. 2014 - Oct. 2014, Japanese
ゴム支承の損傷メカニズムに関する基礎的検証
林訓裕; 足立幸郎; 坂本直太; 五十嵐晃; 党紀; 大谷修; 下池利孝
第34回地震工学研究発表会講演論文集, Oct. 2014
Oct. 2014 - Oct. 2014, Japanese
免震橋の水平2方向耐震性能に関する漸増動的解析
党紀; 蛯沢佑紀; 五十嵐晃; 奥井義昭
土木学会第69回年次学術講演会, Sep. 2014
Sep. 2014 - Sep. 2014, Japanese
経年劣化ゴム支承の載荷試験による残存性能の調査
濱野真彰; 五十嵐晃; 党紀; 足立幸郎; 林訓裕
土木学会第69回年次学術講演会, Sep. 2014
Sep. 2014 - Sep. 2014, Japanese
鉛プラグ入り積層ゴム支承の経年劣化による減衰性能低下モデル
東出知大; 五十嵐晃; 党紀; 足立幸郎; 林訓裕
土木学会第69回年次学術講演会, Sep. 2014
Sep. 2014 - Sep. 2014, Japanese
鉛プラグ入り積層ゴム支承の損傷メカニズム検証
林訓裕; 足立幸郎; 五十嵐晃; 党紀; 東出知大
土木学会第69回年次学術講演会, Sep. 2014
Sep. 2014 - Sep. 2014, Japanese
経年劣化されたゴム支承（LRB）を用いる橋梁構造の耐震性能に関する解析検討
Ji Dang
第17回性能に基づく橋梁等の耐震設計に関するシンポジウム講演論文集, Jul. 2014
Jul. 2014 - Jul. 2014, Japanese
積層ゴム支承の経年劣化損傷が残存性能に与える影響検討
林訓裕; 足立幸郎; 五十嵐晃; 党紀; 濱野真彰; 東出知大
第17回性能に基づく橋梁等の耐震設計に関するシンポジウム講演論文集, Jul. 2014
Jul. 2014 - Jul. 2014, Japanese
橋梁用天然ゴム支承の経年劣化と残存性能の実験的評価
濱野真彰; 五十嵐晃; 党紀; 東出知大; 足立幸郎; 林訓裕
平成26年度土木学会関西支部年次学術講演会, May 2014
May 2014 - May 2014, Japanese
Experimental verification for remaining performance of lead rubber bearing with aged deterioration (in Japanese)
K.Hayashi; Y.Adachi; K.Komoto; H.Yatsumoto; A.Igarashi; J.Dang; T.Higashide
Proc. 33rd JSCE Earthquake Engineering Symposium, Oct. 2013
Oct. 2013 - Oct. 2013, Japanese
10/24-25, Tokyo, Japan, JSCE
矩形廃タイヤゴムパッド免震材におけるせん断限界性能の載荷方向依存性
松島弘; 五十嵐晃; 党紀
土木学会第68回年次学術講演会, Sep. 2013
Sep. 2013 - Sep. 2013, Japanese
水平2方向のひずみ依存性を考慮したゴム支承の非線形履歴復元力モデル
村越雄太; 五十嵐晃; 党紀
土木学会第68回年次学術講演会, Sep. 2013
Sep. 2013 - Sep. 2013, Japanese
ゴム支承（LRB）の経年劣化と地震時残存性能試験
林訓裕; 足立幸郎; 甲元克明; 五十嵐晃; 党紀; 東出知大
土木学会第68回年次学術講演会, Sep. 2013
Sep. 2013 - Sep. 2013, Japanese
ゴム支承（LRB）の経年劣化と終局変形性能および常時性能試験
党紀; 五十嵐晃; 東出知大; 足立幸郎; 林訓裕; 甲元克明
土木学会第68回年次学術講演会, Sep. 2013
Sep. 2013 - Sep. 2013, Japanese
ゴム支承（LRB）の経年劣化と残存性能に関する解析的検討
東出知大; 五十嵐晃; 党紀; 足立幸郎; 林訓裕; 甲元克明
土木学会第68回年次学術講演会, Sep. 2013
Sep. 2013 - Sep. 2013, Japanese
経年劣化したゴム支承（LRB）の残存性能に関する実験的考察
林訓裕; 足立幸郎; 甲元克明; 八ツ元仁; 五十嵐晃; 党紀; 東出知大
Jul. 2013
Jul. 2013 - Jul. 2013, Japanese
土木会館，7/17-18，土木学会
矩形廃タイヤゴムパッド免震材のせん断限界性能の載荷方向依存性
松島弘; 五十嵐晃; 党紀
平成25年度土木学会関西支部年次学術講演会, Jun. 2013
Jun. 2013 - Jun. 2013, Japanese
Experimental Validation of Numerical Modeling for Elastomeric Isolation Bearings under Bi-Directional Loading
Ji Dang; Akira Igarashi; Yuta Murakoshi
Proc. 25th KKCNN Symposium on Civil Engineering, Oct. 2012
Oct. 2012 - Oct. 2012, English
Pseudo-dynamic test of seismic isolation system using scrap tire rubber pad for seismic performance verification
Akira Igarashi; Mishra Huma Kanta; Dang Ji; Hiroshi Matsushima
Proc. 25th KKCNN Symposium on Civil Engineering, Oct. 2012
Oct. 2012 - Oct. 2012, English
EXPERIMENTAL STUDY ON BIDIRECTIONAL RESTORING FORCE OF RUBBER BEARINGS UNDER BIDIRECTIONAL LOADING AND COMPARISON OF HYSTERETIC MODELS
Akira IGARASHI; Ji DANG; Yuta MURAKOSHI; Toshihiko ITO
Proc. 32th JSCE Earthquake Engineering Symposium, Oct. 2012
Oct. 2012 - Oct. 2012, Japanese
EXPERIMENTAL STUDY FOR SEISMIC PERFORMANCE OF CONCRETE FILLED SQUARE SECTION STEEL BRIDGE PIERS UNDER BI-LATERAL GROUND EXCITATION
Huihui YUAN; Ji DANG; Tetsuhiko AOKI
Proceedings of the 32nd Conference on Earthquake Engineering, Oct. 2012
Oct. 2012 - Oct. 2012, Japanese
A Discussion about the Hysteresis Behavior of Rubber Bearings under Bi-Directional Loading and the Numerical Method for this Issue
Ji Dang; Akira Igarashi; Hitohiko Itho; Yuta Murakoshi
67th Annual Meeting of JSCE, Sep. 2012
Sep. 2012 - Sep. 2012, Japanese
Experimental Study for Hysteresis Model of Laminated Rubber Bearings under Bidirectional Loading
Hitohiko Itho; Akira Igarashi; Ji Dang; Yuta Murakoshi
Heisei 24th Year Annual Meeting of Kansai Branch of JSCE, Jun. 2012
Jun. 2012 - Jun. 2012, Japanese
A Curves Approximated Multiple Springs Model for Bi-Directional Seismic Response Simulation of Steel Bridge Piers
党 紀; 袁 輝輝; 五十嵐 晃
2012
2012 - 2012, Japanese
Improvement of Seismic Performance of Steel Bridge Piers by Concrete-Filling and Bidirectional Loading Tests
Tatsuya Ozawa; Ji Dang; Hikari Kishita; Tetsuhiko Aoki
66th Annual Meeting of JSCE, Sep. 2011
Sep. 2011 - Sep. 2011, Japanese
Experimental Study for Seismic Performance of Concrete Filled Steel Bridge Piers under Bidirectional Ground Motion Excitation
Hikari Kishita; Ji Dang; Tatsuya Ozawa; Tetsuhiko Aoki
66th Annual Meeting of JSCE, Sep. 2011
Sep. 2011 - Sep. 2011, Japanese
Multiple-Spring Model Analysis Method for Steel Bridge Piers under Bi-Directional Earthquake Loading
Ji Dang; Tetsuhiko Aoki; Kiki Yuan
66th Annual Meeting of JSCE, Sep. 2011
Sep. 2011 - Sep. 2011, Japanese
An Experimental Study for Box Sectional Steel Bridge Columns under Bi-Directional Loading
Takashi Watanabe; Ji Dang; Tatsuya Ozawa; Tetsuhiko Aoki
65th Annual Meeting of JSCE, Sep. 2010
Sep. 2010 - Sep. 2010, Japanese
The Cubic Curves Hysteresis Model of Steel Bridge Piers for Seismic Response Simulation
Ji Dang; Tetsuhiko Aoki
9th Pacific Structure Steel Conference, 2010
2010 - 2010, English
Bi-directional Loading Hybrid Test of Square Section Steel Piers
Tetsuhiko Aoki; Ji Dang
Proceedings of the 14th European Conference on Earthquake Engineering, 2010
2010 - 2010, English
Dynamic Loading Tests forLow-Yield-Strength Steel Shear Panel Damper
Chaofeng Zhang; Ji Dang; Takashi Watanabe; Tetsuhiko Aoki
64th Annual Meeting of JSCE, Sep. 2009
Sep. 2009 - Sep. 2009, Japanese
Bi-Directional Hybrid Tests for Steel Piers
Tetsuhiko Aoki; Taro Nakamura; Ji Dang; Shinya Moritai; Moriaki Suzuki
64th Annual Meeting of JSCE, Sep. 2009
Sep. 2009 - Sep. 2009, Japanese
A Curve Hysteresis Model for Quasi-Hybrid Test Approach of Steel Bridge Piers
Ji Dang; Shinya Morita; Tetsuhiko Aoki; Moriaki Suzuki
64th Annual Meeting of JSCE, Sep. 2009
Sep. 2009 - Sep. 2009, Japanese
Dynamic shear tests of low-yield steel panel dampers for bridge bearing
T. Aoki; J. Dang; C. Zhang; T. Takaku; Y. Fukumoto
STESSA 2009 - BEHAVIOUR OF STEEL STRUCTURES IN SEISMIC AREAS, 2009, CRC PRESS-TAYLOR & FRANCIS GROUP
2009 - 2009, English
The dynamic behavior of low-yield point steel shear panel dampers under action of high speed loading is investigated experimentally in this paper. Horizontal displacement is applied by a 25tf hydraulic actuator at the panel top under the displacement control. Three patterns of sine wave vibration having a fixed displacement amplitude of +/- 18 mm are applied to the panel top for the three different periods of T = 0.5, 1.0 and 2.0 sec. The effects of applied displacement velocity of loading on the load-displacement hysteresis loops approximately rectangular and practically rate independent of the shear damper are examined.
簡易3次元計測技術を活用した構造物管理に関する研究
Apr. 2024 - Mar. 2026
Principal investigator
人間と AI 協働型画像損傷セグメンテーションの開発
Apr. 2022 - Mar. 2025
Principal investigator
Grant amount(Total)：1500
Competitive research funding
橋梁点検の自動化のための UAV 撮影と3D 損傷認識手法の開発
Oct. 2022 - Sep. 2024
Principal investigator
A New AI Method for Bridge Inspection and Diagnosis that Combines CNN with Highly Accurate Damage Detection and Expertises
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), 01 Apr. 2021 - 31 Mar. 2024
The University of Tokyo
Grant amount(Total)：17420000, Direct funding：13400000, Indirect funding：4020000
Grant number：21H01417
Development of an existing bridge management method based on load rating
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), 01 Apr. 2021 - 31 Mar. 2024
Saitama University
Grant amount(Total)：15340000, Direct funding：11800000, Indirect funding：3540000
Grant number：21H01415
ケニアにおける橋梁維持管理のためのUAVとAI損傷認識の実装
Apr. 2021 - Mar. 2024
Principal investigator
Grant amount(Total)：4000000
Development of Auto-Detection AI for Structure Corrosion Monitoring by Optical Fiber
JSPS, Bilateral Collaborations, Joint Research, Apr. 2021 - Mar. 2023
Saitama University, Dalian University of Technology, Principal investigator
Grant amount(Total)：4470000
Competitive research funding, ［Internationally co-authored］, Grant number：JPJSBP120217401
招へい研究者：Associate Professor Chen Zhiqing University of Missouri Kansas City
Apr. 2021 - Mar. 2022
Grant number：S21046
Real Time Hybrid Simulation for Function Separated Seismic Isolation Bridge
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), 01 Apr. 2018 - 31 Mar. 2021
Dang Ji, Saitama University
Grant amount(Total)：4290000, Direct funding：3300000, Indirect funding：990000
Considering that seismic isolation bearings may be broken due to the large earthquake that exceeds design level, the function-sperated seismic isolation system have been proposed to distribute the functions that were previously concentrated on rubber bearings to multiple devices. Seismic response analysis compared to conventional seismic structures confirmed that seismic response was suppressed and rupture was concentrated in SPDs. In this study, the real-time hybrid simulations were conducted to verify the function separated bridge in which the cylinder damper and SPD in series absorb small and large shaking, respectively.
Grant number：18K04319
論文ID：32756967, 講演・口頭発表等ID：32757770
Development of a seismic design framwork based on incremental dynamic analysis using spectrum-compatible multi-dimentional seismic ground motions
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B), Grant-in-Aid for Scientific Research (B), 01 Apr. 2016 - 31 Mar. 2019
Igarashi Akira, Kyoto University
Grant amount(Total)：18070000, Direct funding：13900000, Indirect funding：4170000
Incremental dynamic analysis of historical masonry buildings in Patan, Nepal and Tsujun Bridge in Kumamoto revealed the validity of the assessment of damage level and the relationship with the level of earthquake motion, under the 2015 Gorka and 2016 Kumamoto earthquake ground motions that each structure actually experienced. Also, incremental dynamic analysis of structural models of a curved girder bridges was performed taking the bi-directional input and rotation due to collision of girder / abutment into account to obtain seismic performance assessment in the form of fragility curves. It is quantitatively shown that the seismic risk due to the bidirectional action significantly increases for the case of curved girder bridges.
Based on these results, seismic performance assessment and design method of the structure using two-direction ground motion and incremental dynamic analysis were summarized.
Grant number：16H04399
Collapse Analysis and Anti-Catastrophe Assessment Method for Isolated Bridges with Steel Piers
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Young Scientists (B), Grant-in-Aid for Young Scientists (B), 01 Apr. 2016 - 31 Mar. 2018
DANG Ji, Saitama University
Grant amount(Total)：4160000, Direct funding：3200000, Indirect funding：960000
In this study, the proposed Modified Park-Wen Model is verified by quasi-static loading test and Sub-Structure Pseudo-Dynamic Simulations with Kobe Earthquake and scaled High-Damping Rubber (HDR) bearings. Seismic response simulation for highway viaduct bridges were conducted. As its numerical model, a simplified Two-Degree-Of-Freedom model is used in Incremental Dynamic Analysis (IDA) to evaluated the Anti-Catastrophe Performance of this kind of structures under Design-Level-exceeded earthquakes, and to cumulate basic data about structural collapsing pattern and their probabilities. Using the fragility curves from result of IDA, though, the collapse probability is low for design level earthquake, most possible collapsing pattern under design exceeded earthquakes is the broken of rubber bearings.
Grant number：16K18136
Development of design procedure for high damping rubber bearings under low temperatures and modeling of Mullins' effect
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B), Grant-in-Aid for Scientific Research (B), 01 Apr. 2014 - 31 Mar. 2017
OKUI Yoshiaki; IMAI Takashi, Saitama University
Grant amount(Total)：15470000, Direct funding：11900000, Indirect funding：3570000
The temperature dependence of mechanical characteristics of high damping rubber bearings (HDRBs) was investigated through cyclic loading tests under different ambient temperatures, especially sub-zero environment. The ambient temperatures and temperatures inside HDRBs during cyclic loading were
different due to self hating, and it is found that mechanical behavior of HDRBs is governed by the inside temperatures. A simple method to estimate the inside temperature was developed on the basis of the cyclic loading tests and thermal conductivity analyses results. Previous cyclic loading tests results at different ambient temperatures were reexamined based on the inside temperatures to estimate temperature dependence of HDRBs.
Grant number：26289140
Development of design method for bridges with seismic response modification devices on the basis of bi-directional seismic action
Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B), Grant-in-Aid for Scientific Research (B), 01 Apr. 2013 - 31 Mar. 2016
Igarashi Akira; FURUKAWA Aiko; DANG Ji, Kyoto University
Grant amount(Total)：17160000, Direct funding：13200000, Indirect funding：3960000
The purpose of the present research is to establish effective design procedures for bridges with seismic response modification techniques, namely seismic isolation and energy dissipation device application. Firstly, the bi-directional character of input seismic ground motion acceleorograms is analyzed and efficient numerical procedures to generate spectrum-compatible bi-directional input accelerograms are developed. Secondly, methods for modeling of the bi-directional nonlinear restoring force characteristics and bi-directional dynamic response behavior are proposed. The combination of these two findings and methodologies are demonstrated to be applicable to seismic performance assessment and damage evaluation of structures with seismic protective measures.
Grant number：25289136
論文ID：18981931
