Embedded Files
JS Chen
Belytschko, T., *Chen, J. S., Hillman, M., “Meshfree and Particle Methods: Fundamentals and Applications”, Wiley, 2023 (ISBN: 9780470848005).
Baek, J., *Chen, J. S., Susuki, K., “Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations,” International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, 2022. (https://doi.org/10.1002/nme.7040)
He, X., *Chen, J. S., “Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials, Computer Methods in Applied Mechanics and Engineering, Vol. 402, 115348, 2022. (https://doi.org/10.1016/j.cma.2022.115348)
Huang, T. H., *Chen, J. S., Tupek, M. R., Beckwith, F. N., Fang, H. El., “A Variational Multiscale Immersed Meshfree Method for Fluid Structure Interactive Systems involving Shock Waves,” Computer Methods in Applied Mechanics and Engineering, Vol. 389, 114396, 2022. (https://doi.org/10.1016/j.cma.2021.114396)
Schlinkman, R. T., Baek, J., Beckwith, F. N., Nelson, S. M., *Chen, J. S., “A Quasi-Conforming Embedded Reproducing Kernel Particle Method for Heterogeneous Materials,” Computer Methods in Applied Mechanics and Engineering, Vol. 416, 116363, 2023. (https://doi.org/10.1016/j.cma.2023.116363)
He, X., Choi, Y., Fries, W. D., Belof, J. L., *Chen, J. S., “Glasdi: Parametric physics-informed greedy latent space dynamics identification,” Journal of Computational Physics, Vol. 489, 112267, 2023. (https://doi.org/10.1016/j.jcp.2023.112267)
Wang, Y., Baek, J., Tang, Y., Du, J., Hillman, M., *Chen, J. S., “Support Vector Machine Guided Reproducing Kernel Particle Method for Image-Based Modeling of Microstructures,” Computational Mechanics, Vol. 73, pp 907-942, 2024. (https://doi.org/10.1007/s00466-023-02394-9)
Tanej, K., He, X., He, Q., *Chen, J. S., “A Multi-Resolution Physics-Informed Recurrent Neural Network: Formulation and Application to Musculoskeletal Systems,” Computational Mechanics, Vol. 73, pp 1125-1145, 2024. (https://link.springer.com/article/10.1007/s00466-023-02403-x)
Baek, J., *Chen, J. S., “A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture”, Computer Methods in Applied Mechanics and Engineering, Vol. 410, 116590, 2024. (https://doi.org/10.1016/j.cma.2023.116590)
Baek, J., Wang, Y., *Chen, J. S., "N-Adaptive Ritz Method: A Neural Network Enriched Partition of Unity for Boundary Value Problems," Computer Methods in Applied Mechanics and Engineering, Vol. 428, 117070, 2024.. (https://doi.org/10.1016/j.cma.2024.117070)
TY Chen
a list of recent publications (less than 10) related to the Yushan project
W.-H. Huang, Z-Y Lin, T. Chen*, Energy attenuation of seismic metamaterials composed of a periodic array of coated elliptical cylinders. Journal of Mechanics, Special issue in memory of Professor C.C. Ma, DOI: 10.1093/jom/ufae044, 2024.
Y.-C. Sun, P.-T. Chen and T. Chen*, Wave amplitudes and contour profiles of surface Rayleigh waves in a layered half-space with transversely isotropic materials, Acta Mechanica, 234, 5709–5724, 2023.
T. Chen*, and J.H. Lin, Novel connections and physical implications of thermal meta-materials with imperfect interfaces. Scientific Reports 12, 2734, 2022.
CC Hung
Bo-Jun Huang and Chung-Chan Hung* (2024, Jul). Post-Fire Seismic Responses of High-Strength RC Columns: Experiments and Simulations. Journal of Structural Engineering, STENG-13727.
Chung-Chan Hung*, Anggun Tri Atmajayanti, Valentine Chronica Domaria Meiji, Terry YP Yuen, Doo-Yeol Yoo (2024, Jul). Impact of Aluminate Cements on the Durability and Mechanical Performance of Strain-hardening Cementitious Composites. Journal of Building Engineering, 89, 109416.
Shack Yee Hiew, Keat Bin Teoh, Sudharshan N Raman, Chung-Chan Hung, Ya Xuan Chaen, Daniel Kong, Milad Hafezolghorani (2024, Jul). A unified tensile constitutive model for mono/hybrid fibre-reinforced ultra-high-performance concrete (UHPC). Cement and Concrete Composites, 150, 105553.
Chung-Chan Hung*, Sohit Agrawal, Hsin-Jui Hsiao (2024, May). Rehabilitation of seismically-damaged RC beam-column joints with UHPC and high-strength steel mesh reinforcement. Journal of Building Engineering, 84, 108667.
CC Hung*, TYP Yuen, KM Mosalam (2024, Apr). Full-scale cyclic testing of slender RC columns bent in double curvature under high axial load. Journal of Building Engineering, 82, 108186.
Chung-Chan Hung*, Hsin-Jui Hsiao (2024, Mar). Retrofitting RC beam-column joint subassemblies using UHPC jackets reinforced with high-strength steel mesh" in the journal. Engineering Structures, 305, 117688.
Manuel Bermudez, Chung-Chan Hung* (2024, Mar). Shear Strength Equation and Database for High-Strength HPFRC and UHPC Beams Without Stirrups. ACI Structural Journal, 10.14359/51740716.
CM Lin, YW Chang, CC Chou, SJ Jhuang, Z Lee, CL Wu, SH Chao,JY Huang, HC Yang, CY Chang, G Mosqueda, Chung-Chan Hung (2024, Feb). Reconnaissance of the 2022 Guanshan and Chihshang earthquakes in eastern Taiwan. Earthquake Spectra, 40(1), 531-565.
Tzu-Ming Hung, Cheng-Che Wu, Chung-Chan Hung, Sheng-Heng Chung (2024, Feb). Cement/Sulfur for Lithium–Sulfur Cells. Nanomaterials, 14(4), 384. (SCI, Q2, Chemistry, Multidisciplinary).
Chung-Chan Hung*, Tuong Dat Dinh Do (2024, Jan). Sprayed high-strength strain-hardening cementitious composite: Anisotropic mechanical properties and fiber distribution characteristics. Construction and Building Materials, 412, 134862.
HC Kan
Pei-Hsin Pai, Heng-Chuan Kan*, Hock-Kiet Wong, and Yih-Chin Tai*. “A neural particle method with interface tracking and adaptive particle refinement for free surface flows”. Communications in Computational Physics (Accepted, I.F.=3.8), 2024.
Adhika Satyadharma, Ming-Jyh Chern, Heng-Chuan Kan*, Harinaldi, and James Julian. “Assessing Physics Informed Neural Network Performance with Sparse Noisy Velocity Data”. Physics of Fluids (Accepted, I.F.=4.1), 2024.
Pei-Hsin Pai, Heng-Chuan Kan*, and Yih-Chin Tai. “Evaluate Computational Efficiency of Adaptive Particle Neural Particle Method (NPM-A) for Modeling Fluid Flow Problems”. Conference Proceedings, The 12th International Conference on Computational Fluid Dynamics (ICCFD12), Kobe, Japan, July 14-19, 2024.
A. Satyadharma, M.J. Chern, H.-C. Kan, and W.Y. Chiang. “Resolving weak flow interaction on an array of cylinders with PINN”. Conference Proceedings, The 12th International Conference on Computational Fluid Dynamics (ICCFD12), Kobe, Japan, July 14-19, 2024.
Pei-Hsin Pai, Heng-Chuan Kan*, Hock-Kiet Wong, and Yih-Chin Tai. “A Neural Particle Method for Simulating Complex Flow Geometry”. Conference Proceedings, The 1st Annual Meeting and Conference of Association of Computational Mechanics Taiwan (ACMT 2023), Keelung, Taiwan, Oct. 28-29, 2024.
Adhika Satyadharma, Ming-Jyh Chern, and Heng-Chuan Kan. “Simulating High Re Flow Fields using Data Assisted PINN”. Conference Proceedings, The 1st Annual Meeting and Conference of Association of Computational Mechanics Taiwan (ACMT 2023), Keelung, Taiwan, Oct. 28-29, 2024.
Adhika Satyadharma, Ming-Jyh Chern, and Heng-Chuan Kan. “A Parametric Study of Data Assimilation PINN on a 2-Dimensional Lid-Driven Cavity Flow”. Conference Proceedings, The ASME-JSME-KSME Joint Fluids Engineering Conference 2023 (AJK FED2023), Osaka, Japan, July 9-13, 2023.
白佩鑫,甘恆全,戴義欽. “以機器學習為基礎之數值模擬方法 - Physics-Informed Neural Networks (PINNs) 之 Neural Particle Method (NPM) 方 法 初 步 探 討 ”. Conference Proceedings, The 46th National Conference on Theoretical and Applied Mechanics, New Taipei, Taiwan, Nov. 18-19, 2022.
Yu-Ching Lin, Chih-Min Yao, Heng-Chuan Kan, Jian Ming Lu, Min-Fu Hsieh, Chun Hui Chung, and Mi Ching Tsai. “The Intelligent Diagnosis System Design for Electric Motors based on the Cloud AIoT Platform”. Conference Proceedings, The 10th International Multi-Conference on Engineering and Technology Innovation 2021 (IMETI2021), Taoyuan, Taiwan, Oct. 29–Nov. 2, 2021.
YY Ko
Ko, Y.Y., Wang, H.W., Jheng, K.Y. (2023) “An Experimental Study of the Impact of Liquefaction-Induced Displacement on Buried Pipelines for Buildings,” Earthquake Engineering and Structural Dynamics, 52(12), 3529-3913.
Ko, Y.Y., Tsai, C.C., Hwang, J.H., Hwang, Y.W, Ge, L., Chu, M.C. (2023) “Failure of Engineering Structures and Associated Geotechnical Problems during the 2022 ML 6.8 Chihshang Earthquake, Taiwan,” Nature Hazards. https://doi.org/10.1007/s11069-023-05993-0.
Ko, Y.Y., Tasi, T.Y., Jheng, K.Y. (2023) “Full-Scale Shaking Table Tests on Soil Liquefaction-Induced Uplift of Buried Pipelines for Buildings,” Earthquake Engineering and Structural Dynamics, 52(5), 1486-1510.
Ko, Y.Y., Li, Y.T., Chen, C.H., Yeh, S.Y., Hsu, S.Y. (2021) “Influences of Repeated Liquefaction and Pulse-Like Ground Motion on the Seismic Response of Liquefiable Ground Observed in Shaking Table Tests, Engineering Geology, 291, 106234. (SCI, EI)
YC Tai
H.K. Wong, Y.C. Tai*, H. Tsunetaka and N. Hotta (2024). Two-Phase Approach to Modeling the Grain-Fluid Flows with De- position and Entrainment over Rugged Topography, Advances in Water Resources, 188, 104691, https://doi.org/10.1016/j.advwatres.2024.104691. (SCI) June 2024
Pei-Hsin Pai, Heng-Chuan Kan*, Hock-Kiet Wong, and Yih-Chin Tai* (2024). A Neural Particle Method with Interface Tracking and Adaptive Particle Refinement for Free Surface Flows, Communications in Computational Physics, (SCI, accepted on Jan. 08. 2024)
Ma, C.Y., Ko, C.J., Wong, H.K., and Tai, Y.C.* (2022). Modeling three-phase debris flows in terrain-following coordinate system and its GPU computation with CUDA structure. Journal of the Chinese Institute of Civil and Hydraulic Engineering, 34(7), 597--604. (in Chinese) Dec. 2022
L. Sarno, Y. Wang, Y.-C. Tai, M. N. Papa, P. Villani, and M. Oberlack (2022). A well-posed multilayer model for granular avalanches: comparisons with laboratory experiments. Physics of Fluids, 34, 113307. https://doi.org/10.1063/5.0106908. (SCI) Nov. 2022, (Highlighted by SciLight)
Wang, C.-L.; Ko, C.-J., Wong, H.-K., Pai, P.-H., and Tai, Y.-C.* (2022). An Approach for Preliminary Landslide Scarp Assessment with Genetic Algorithm (GA). Water, 14, 2400. https://doi. org/10.3390/w14152400. (SCI) Aug. 2022
Ko, C-J, Wang, C-L, Wong, H-K, Lai, W-C, Kuo, C-Y and Tai, Y-C* (2021). Landslide Scarp Assessments by Means of an Ellipse-Referenced Idealized Curved Surface. Front. Earth Sci., 9: 733413. doi: 10.3389/feart.2021.733413 (SCI) Sep. 2021
L. Sarno*, Y.-C. Tai and Y. Wang (2021). A well-posed multilayer model for granular avalanches with μ(I) rheology. Phys. Fluids, 33, 103319; doi: 10.1063/5.0065697 (SCI) Oct. 2021
Y.C. Tai, J. Vides, B. Nkonga and C.Y. Kuo (2021). Multi-Mesh-Scale Approximation of Thin Geophysical Mass Flows on Complex Topographies. Communications in Computational Physics (CiCP), 29(1), 148-185. (SCI) Jan. 2021
Y.C. Tai, J. Heß and Y. Wang (2019). Modeling two-phase debris flows with grain-fluid separation over rugged topography: Application to the 2009 Hsiaolin event, Taiwan. Journal of Geophysical Research -- Earth Surface, 124, 305–333. http://doi.org/10.1029/2018JF004671. (SCI)
（Special issues/books）Luca, I., Tai, Y. C., Kuo, C. Y. (2016) “Shallow Geophysical Mass Flows down Arbitrary Topo- graphy.” Springer Verlag, ISBN: 978-3-319-02626-8.
WP Tsai
Bindas, Tadd, Wen-Ping Tsai, Jiangtao Liu, Farshid Rahmani, Dapeng Feng, Yuchen Bian and Chaopeng Shen*, 2024. “Improving river routing using a differentiable Muskingum-Cunge model and physics-informed machine learning”, Water Resources Research 60 (1).
Yalan Song, Wen-Ping Tsai, Jonah Gluck, Alan Rhoades, Colin Zarzycki, Rachel McCrary, Kathryn Lawson, and Chaopeng Shen, 2024. “LSTM-based data integration to improve snow water equivalent prediction and diagnose error sources”, Journal of Hydrometeorology. 25(1):223-237.
Wen-Ping Tsai, Dapeng Fen, Ming Pan, Hylke Beck, Kathryn Lawson, Yuan Yang, Jiangtao Liu, and Chaopeng Shen, 2021. “From calibration to parameter learning: Harnessing the scaling effects of big data in geoscientific modeling”, Nature Communications. 12, 5988.
Kai Ma, Dapeng Feng, Kathryn Lawson, Wen-Ping Tsai, Chuan Liang, Xiaorong Huang, Ashutosh Sharma, Chaopeng Shen, 2021. “Transferring hydrologic data across continents -- leveraging data-rich regions to improve hydrologic prediction in data-sparse regions”, Water Resources Research. 57(5). e2020WR028600.
Wei Zhi, Dapeng Feng, Wen-Ping Tsai, Gary Sterle, Adrian Harpold, Chaopeng Shen, Li Li, 2021. “From hydrometeorology to river water quality: can a deep learning model predict dissolved oxygen at the continental scale?”, Environmental Science & Technology. 55, 4, 2357-2368.
Wen-Ping Tsai, Kuai Fang, Xinye Ji, Kathryn Lawson, Chaopeng Shen, 2020, ”Revealing causal controls of storage-streamflow relationships with a data-centric Bayesian framework combining machine learning and process-based modeling”, Frontiers in Water. 2: 40.
Jia-Hao Hu, Wen-Ping Tsai*, Su-Ting Cheng, Fi-John Chang, 2020, “Explore the Relationship between Fish Community and Environmental Factors by Machine Learning Techniques”, Environmental Research. 184:109262.
Tao Bai, Wen-Ping Tsai*, Yen-Ming Chiang, Fi-John Chang, Wan-Yu Chang, Li-Chiu Chang, Kuang-Chih Chang, 2019, “Modeling and Investigating the Mechanisms of Groundwater Level Variation in the Jhuoshui River Basin of Central Taiwan”, Water. 11(8), 1554.
Wen-Ping Tsai, Chung-Lien Cheng, Tinn-Shuan Uen, Yanlai Zhou, Fi-John Chang, 2019, “Drought Mitigating under Urbanization through an Intelligent Water Allocation System”, Agricultural Water Management. 213: 87-96.
Su-Ting Cheng, Wen-Ping Tsai, Tzu-Chun Yu, Edwin Herricks, and Fi-John Chang, 2018, “Signals of stream fish homogenization revealed by AI-based clusters”, Scientific Reports. 8(1): 15960.
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