Tsung-Hui (Alex) Huang, 黃琮暉

Associate Professor 副教授

Office 辦公室: ENG1-R626 工一館626室

Phone 分機: 03-5715131 ext.33731

Research Area: Computational Mechanics, Numerical Methods, Extreme Events, Fluid-Structure Interaction, Shock Modeling, Meshfree and Finite Element Methods, Machine Learning Enhanced Methods

研究領域：計算力學、數值方法、極限工程、流固耦合、衝擊波模擬、無網格法、有限元素法、機器學習強化法

About Research: Doing research is different from doing homework or taking an exam. We must learn to view the problem from various perspectives and find out their connections.

研究二三事：做研究跟做功課或考試不一樣。需要學會從不同角度去觀察問題的關聯性並從而找出更多可能性。

Recruitment 人才招募

We are currently hiring talented PostDoc, PhD/MS students. Please refer to GROUP for details. 本研究團隊正在招募對計算力學有興趣的人才，細節請參閱研究團隊一節

BACKGROUND 學歷/經歷

Bio 個人簡介

Tsung-Hui (Alex) Huang is currently an associate professor in the Department of Power Mechanical Engineering, National Tsing Hua University, Taiwan from 2020 (Fall). His research focuses on developing novel computational tools for engineering problems involving structure or material under extreme conditions. Specifically, he developed meshfree methods to model material undergoing high strain-rate, strong hydrodynamical effect, and damage/fragmentation process. He recently works on the flow analysis and fluid-structure interaction for complicated bionic structures, and machine learning enhanced simulation techniques.

Appointment 經歷

2024 - Now, Associate Professor, Power Mechanical Engineering, National Tsing Hua University, Taiwan,

國立清華大學動力機械工程學系副教授,

2020 - 2024, Assistant Professor, Power Mechanical Engineering, National Tsing Hua University, Taiwan,

國立清華大學動力機械工程學系助理教授,

2015 - 2016, Research Assistant, CAE Division, Civil Engineering, National Taiwan University, Taiwan.

國立台灣大學土木工程學系研究助理,

Education 學歷

2016 - 2020, PhD, Structural Engineering, University of California San Diego, USA. 美國加州大學聖地牙哥分校結構工程學系

2013 - 2014, MS, Mechanical Engineering, University of Minnesota Twin Cities, USA. 美國明尼蘇達大學雙城分校機械工程學系

2008 - 2012, BS, Mechanical Engineering, National Taiwan University, Taiwan. 國立台灣大學機械工程學系

Personal Honors and Awards 個人獎項

2024 Guest Editor: Engineering with Computers (SCI/EI, IF: 8.7 in 2022)

2022 University New Faculty Research Award, NTHU, Taiwan
2022 New Faculty Research Award, School of Engineering, NTHU, Taiwan

2021 Cross-Generation Young Scholars Program, MOST, Taiwan

2021 UCSD Structural Engineering Department Nomination for Chancellor’s Dissertation Medal

2021 Conference Travel Award, WCCM: WCCM2020 (Will be a virtual conference due to the COVID19 pandemic)

2020 UCSD Thesis Dissertation Fellowship

2019 Conference Travel Award, USACM: FEF2019

2018 Taiwanese Government Scholarship, Ministry of Education in Taiwan

2018 Conference Travel Award, USACM: MFEM2018

Honors and Awards for Supervised Students/Group 指導學生/團隊獎項

2024 Honorable Mention Award in NTHU CoE Student Competition (喜悅 & 承濬)

2023 Excellent Poster Awards of Student Poster Competition in MRSTIC (陳彥臻)

2023 First Place Award in CTAM2023 (周俞均)

2023 The Third Place Award in TSFD Congress 2023 (謝宗燁 & 蔡揚名)

2023 Presentation Award in TWSIAM2023 (Cameron J Rodriguez)

2023 Honorable Mention Award in Poster Competition in TWSIAM2023 (Harshal Shashikant Tangade)
2022 Honorable Mention Award in Poster Competition in TSFD Congress 2022 (謝宗燁)

2022 Second Place Award in CTAM2022 (Cameron J Rodriguez)
2022 Honorable Mention Award in student poster competition of NTHU School of Engineering. (林威辰)

2021 Third Place Award in CSME2021 (林威辰)

2021 Honorable Mention Award in CTAM2021 (趙家廉)

educaton

RESEARCH 研究計畫與方向

Research Direction｜研究方向

Our research focuses on the development and employment of novel numerical methods ad AI machine learning technology for different types of engineering problem: 本研究室專注於開發及應用數值方法及特殊模擬技術（人工智慧與機器學錫）於解決傳統商業軟體無法解決之工程問題，研究方向含括：

Numerical Methods Development (Mesh-based and Meshfree Method) / 演算法開發（有限元素法，無網格法）
Material and Structure under Extreme Condition / 材料及結構極限探討
Multi-Scale Structure and Multi Physics Phenomena / 多尺度結構及多重物理問題
Advanced Fluid Modeling and Fluid-Structure Interaction / 新式流體建模與流固耦合分析
Machine Learning and Data-Driven Mechanics and Simulation / 機器學習及數據驅動模擬
ML-enhanced Analysis in Micro and Nano-scale problems / 以機器學習分析介觀與納米尺度問題
Computational Methods in Semiconductor Manufacturing and Packaging / 半導體製程與封裝中之計算方法

Research Project (on-going)｜研究計畫

利用材料基因數位技術優化先進積層製造技術設計開發具優異力學性能之複合材料與多材料異質接合 Design and Development of Composites and Multi-materials Heterogeneous Interfaces with Superior Mechanical Performance by Advanced Additive Manufacturing Optimized by Materials Genome Initiative Approaches. (Co-PI, MOST 2030 Thematic Project in the Field of Materials Science, 23/08/01~26/07/31)
開發並應用新型破壞力學模型與模擬技術於分析壓力殼結構破裂問題 Development and Application of Novel Fracture Mechanics and Simulation Techniques on the Analysis of the Fracture Problems for Pressure Hull. (PI, MOST 2030 Cross-Generation Young Scholar Program, 20/08/01~24/07/31)
發展物理信息神經網路演算法於散熱分析及參數最佳化設計 Developing Physics Informed Neural Network Approach for Heat Transfer Analysis and Parameter Optimization. (PI, ITRI Commissioned Research Project, 24/06/15~24/12/31)
智能化水處理 Smart Water Treatment. (PI, ITRI Commissioned Research Project, 24/10/01~24/12/31)
積體電路封裝製程中晶片裂紋之應力建模分析 Stress Simulation Model of Die Crack for IC Assembly. (PI, ASE Chungli Industrial-School Co-op Project, 24/11/01~26/11/31)　
基於物理之機器學習模型用於機台和零件的健康評估 Physics-Informed Machine Learning Model for Health Assessment of Machine Tool and Parts. (PI, TSMC JDP Project, 25/03/01~26/02/28)　
[Closed] 基於物理信息神經網路之結構異常偵測技術 Physics-Informed Neural Network based Structured Anomaly Detection Technique. (PI, ITRI Commissioned Research Project, 23/08/01~23/12/31)
[Closed] 開發新世代無網格法與數據驅動計算力學於分析極限工程問題 Development of Next-Generation Meshfree Methods and Data-Driven Computational Mechanics for the Analysis of Extreme Event Problems. (PI, MOST General Project, 20/11/01~23/09/30)

Gallery | 研究展示

彈道學模擬 Bullet Penetration of Metal Plate

(Advanced Meshfree, VC-NSNI)

金屬板衝擊模擬 Aluminium Plate Impact

(Keyword: Meshfree, Shock Algorithm)

冷凍鑄造法模擬 Freeze-Casting Simulation

(Keyword: Adaptive Finite Element, Phase-Field Methoid)

腔室崩塌 Room Collapse and Closure

(Keyword: Advanced Meshfree, VC-NSNI)

生物體表面流場模擬 Flow Simulation for Biological Model

(Keyword: Advanced FEM, Variational Multiscale Method)

神經網路強化有限元於多尺度模擬 NN-enhanced FEM for multiscale modeling
(Left: Direct Numerical Simulation, Right: Employed NN method)

反數值鎖死穩定化技術 Anti Numerical Locking Stabilization
(Keyword: Mixed Formulation, Variational Multiscale Method)

研究介紹與研究資源簡介(2022年錄製) Introduction to our research, resources, tools, and applications (filmed 2022)

research

GROUP 研究團隊

[Member & Research Direction 團隊成員與研究方向]

[PD] 釋哈利：Meshfree Method無網格法、Fluid Mechanics 流體力學、Shock Wave 衝擊波

[RA] 楊承濬：Fluid Mechanics 流體力學、Meshfree Methods 無網格法

[D1] 周俞均：Machine Learning 機器學習、Bio-Mechanics 生物力學 (與英國利物浦大學Rosti Readioff教授共同指導)

[M2] 謝文翊：Structure Identification 結構辨識、Physics Informed Machine Learning 物理驅動機器學習

[M2] 李郁臻：Machine Learning 機器學習、Material Identification and Modeling 材料辨識與模擬

[M2] 蔡揚名：Physics Informed/Guided Machine Learning 物理驅動導向機器學習、Fluid Mechanics 流體力學

[M2] 俞淞涵：Material Point Method 物質點法、Fragmentation 破片分析

[M2] 謝佳峻：Machine Learning 機器學習、Contact Mechanics 接觸力學

[M2] 陳　馨：Digital Twin 數位孿生、Fatigue 疲勞

[M1] 李威遠：Machine Learning 機器學習
[M1] 李浚瑀：Physics Informed Machine Learning 物理驅動導向機器學習
[M1] 周品瑋：Semiconductor Packaging Analysis 半導體封裝分析
[M1] 姜俐彣：Machine Learning 機器學習
[M1] 郭又維：Machine Learning 機器學習
[M1] Rutuja：TBA

[Lab Focus and Training 實驗室訓練]

The lab training focuses on mathematics, coding and algorithm development, basic training for commercial simulation software. We focus on fundamental research, and the lab is especially welcome for people who are looking for research positions in the near future. Interested students may contact via email. 歡迎對計算力學，結構及材料極限，數值方法，流固耦合及人工智慧驅動模擬有興趣的專題生及研究生加入，學生訓練側重數學邏輯思考，編程、計算軟體開發、二次開發與熟用商業建模與模擬軟體。有興趣加入的學生請直接email聯繫

[Recruitment for MS Students 碩士生招募]:

Each year this lab will recruit 3-5 MS students. Please email me directly for detailed information 本實驗室每年招收3-5個不同領域之碩士生，詳情可參考清大動機系網頁。有興趣的同學請直接聯繫我

[Recruitment for PhD Students, Postdocs, Research Assistant 博士生及專業研究人才招募]:

We are currently recruiting new research assistant, PhD students or Postdocs in the field of computational mechanics. The candidates must have the following conditions 我們目前正在招募計算力學領域的研究助理、博士生或博士後，申請者必需要有下列基礎能力：

Basic understanding in theory of FEM for solid mechanics (in contrast to using commercial software). 對於數值方法、尤其是有限元素法理論、以及固體力學或一般連體力學有著相當程度的理解（非使用有限元素商業軟體之經驗）
Computer coding skills, especially in Python/C++ and Linux system operation. 良好編程技術，尤其是在Python/C++以及Linux系統操作能力
Experience in academia writing/publication. 有過學術期刊或報告撰寫經驗(國內外皆可)

This lab will provide sufficient/competitive monthly stipend and applicant should contact me directly. Please contact me directly if you are interested. 本實驗室將提供有競爭力之獎助學金及薪資，有興趣者請直接聯繫我詳談。

[Alumni & Thesis Topic 畢業生與畢業論文題目]

2024

[M] 周俞均：發展基於力學的機器學習方法應用於破裂到損傷多尺度模擬 (PhD in NTHU-UoL Program)

[M] 楊承濬：開發穩態物質點法應用於自由表面流建模 (RA at my lab)

[M] 鄭辰亘：研究類神經網路建模中之計算加速方法 (Military Service)

2023

[M] 魏彥寧：可應用於厚板殼模擬之穩定無網格伽遼金法 (Language School at Japan)

[M] 謝宗燁：應用類神經網路法模擬具強平流現象之流體問題 (PhD at Carnegie Mellon University)

[M] 陳彥臻：基於類神經網路與可參數化三度週期最小曲面之仿生結構模擬 (Engineer at TSMC)

[M] 王楚皓：以類神經網絡有限元模擬多尺度複合材料問題 (MS in Robotics at NYU)

[M] 喜悅：以相場法耦合網格法與無網格法模擬結構破裂問題 (Foxconn India)

[M] 柯沐龍：積分一致再生核物質點法與其應用於衝擊接觸穿透問題 (PhD at Columbia University)

2022

[M] 趙家廉：開發單點積分穩態有限元法於模擬近似不可壓縮材料 (MS at NTU and will join TSMC soon)

[M] 林威辰：應用多尺度變分有限元素法於鯊魚仿生皮齒結構流場阻力分析與初步流固耦合分析架構探討 (Engineer at TSMC)

group

SOFTWARE 開源軟體

I am dedicating to the open-source implementation and paper publications. Open-sourcing is essential for expanding the horizon of knowledge, and it can connect scientists and engineers in different field, creating new scientific disciplines.

除了研究之外，本團隊亦致力於開源軟體的推廣與發展；開源軟體及論文有助於拓展人類知識邊界，也容易聯繫不同領域的科學家與工程師合作與發展新的科學項目

RKPM2D: an open-source implementation of nodally integrated reproducing kernel particle method for solving partial differential equations

This program includes the Galerkin equation for the linear elasticity, implemented under MATLAB, which is easy to access and is highly readable. The 2D RKPM and stabilized nodal integration are included. It is perfectly suitable for beginner and graduate students to study meshfree method.

基於求解偏微分方程之二維無網格再生核質點法與穩定節點積分技術的開源程式

本程式歸納了線性彈性力學的迦遼金形式並運用MATLAB程序方便取得且易讀的特性，開發了二維無網格再生核質點法與穩態節點積分技術之開源MATLAB程式，尤其適合無網格法的初學者與研究生作為上手使用

Paper Link 論文連結: https://rdcu.be/bPTx0

Download Link 程式下載連結: https://doi.org/10.17632/prfxg9cbrx

Bio 簡介

The implemented RKPM2D program is a two-dimensional RKPM-based code developed for the static analysis of two-dimensional linear elasticity problems. The code is developed based on Reproducing Kernel Particle Method (RKPM) with the following features. (1) User-friendly MATLAB program for straightforward meshfree analysis and easy implementation and modification for new functionalities. (2) Subroutine for discretization of two-dimensional domains of arbitrary geometry and nodal representative domain creation through Voronoi diagram partitioning. (3) A complete meshfree Galerkin equation solver with two types of domain integration: stabilized nodal integration, and conventional background Gauss integration. (4) Built-in visualization tools for post-processing of the numerical results. The RKPM2D code is implemented under a MATLAB environment with pre-processing, solver, and post-processing functions fully integrated for supporting reproducible research and serving as an efficient test platform for further development of meshfree methods. Both the MATLAB built-in mesh generator and standard neutral files exported by other mesh generators can be used to obtain the point-based domain discretization for meshfree analysis. A meshfree Galerkin equation solver for 2-dimensional elastostatics, and visualization tools for post-processing are provided. Nitsche’s method is adopted for imposition of essential boundary conditions. Spatial domain integration techniques implemented in the code include the Gauss Integration (GI), the Direct Nodal Integration (DNI), and the Stabilized Conforming Nodal Integration (SCNI). For nodal integration, two different types of stabilization methods are implemented in RKPM2D, including the Modified Stabilized Conforming Nodal Integration (MSCNI) and the Naturally Stabilized Nodal Integration (NSNI).

Reference 參考資料:

Huang, T. H., Wei, H., Chen, J. S., & Hillman, M. C. (2020). RKPM2D: an open-source implementation of nodally integrated reproducing kernel particle method for solving partial differential equations. Computational Particle Mechanics, 7(2), 393-433.

Software

COURSE 課程

* indicates undergraduate level, otherwise is graduate level.

[NTHU]

2024 - 2025：Mechanics of Materials 材料力學*、Advanced Strength of Materials 高等材料力學、Fracture Mechanics 破裂力學

2023 - 2024：Mechanics of Materials 材料力學*、Nonlinear Finite Element Method 非線性有限元、Fracture Mechanics 破裂力學

2022 - 2023：Mechanics of Materials 材料力學*、Nonlinear Finite Element Method 非線性有限元、Fracture Mechanics 破裂力學

2021 - 2022：Nonlinear Finite Element Method 非線性有限元、Plates and Shells 板殼理論、Fracture Mechanics 破裂力學

2020 - 2021：Plates and Shells 板殼理論、Fracture Mechanics 破裂力學

[UCSD]

2020 Summer：Solid Mechanics 固體力學*

2018 - 2020：Finite Element Method 有限元素法（Teaching Assistant）

Courses

Publication

PUBLICATION 發表

Articles In International Journals (*Corresponding Author)

T. Y. Hsieh, T.-H. Huang*. " A Multiscale Stabilized Physics Informed Neural Networks with Weakly Imposed Boundary Conditions Transfer Learning Method for Modeling Advection Dominated Flow." Submitted to Engineering with Computers. (2024): Published Online. DOI: https://doi.org/10.1007/s00366-024-01981-5
H. Tangade, T.-H. Huang*, C. Rodriguez. "A Blended Variationally Consistent Phase Field Material Point Method for Material Fragmentation Problems. Engineering with Computers (Accepted)
Y.-Z. Chen, C.-H. Wang, T.-Y. Hsieh, C.-C. Tung, P.-Y Chen, T.-H. Huang*. "An Efficient Parameterized Neural Network Enhanced Multiscale Finite Element Modeling for Femur with Triply Periodic Minimal Surfaces Meta-Structures." Journal of Materials Research and Technology. (2024): Published Online. DOI: https://doi.org/10.1016/j.jmrt.2024.05.023
C. Rodriguez, T.-H. Huang*. "A Variationally Consistent Reproducing Kernel Enhanced Material Point Method and its Applications to Incompressible Materials." Computational Mechanics. 73 (2024): 599–618. DOI: https://doi.org/10.1007/s00466-023-02381-0.
T.-H. Huang*. "Stabilized and Variationally Consistent Integrated Meshfree Formulation for Advection-Dominated Problems." Computer Methods in Applied Mechanics and Engineering. 403 (2023): 115698. DOI: https://doi.org/10.1016/j.cma.2022.115698
T.-H. Huang*. Y.-L. Wei. "A Stabilized Bending Consistent Integration Method for Reissner-Mindlin Galerkin Formulation." Computational Mechanics. 70.6 (2022): 1211-1239. DOI: https://doi.org/10.1007/s00466-022-02222-6
T.-H. Huang*. C.-L. Chao. "A Stabilized One-Point Integrated Mixed Formulation for Finite Element and Meshfree Methods in Modeling Nearly Incompressible Materials." Acta Mechanica. 233.3 (2022): 1147-1172. DOI: https://doi.org/10.1007/s00707-021-03135-w
T.-H. Huang*. "A Variational Multiscale Stabilized and Locking-Free Meshfree Formulation for Reissner-Mindlin Plate Problems." Computational Mechanics. 69 (2021): 59–93. DOI: https://doi.org/10.1007/s00466-021-02083-5
T.-H. Huang, JS. Chen*, M. R. Tupek, F. N. Beckwith and E. H. Fang. "A Variational Multiscale Immersed Meshfree Formulation for Fluid-Structure Interactive Systems involving Shock Wave." Computer Methods in Applied Mechanics and Engineering. 389 (2022): 114396. DOI: https://doi.org/10.1016/j.cma.2021.114396
Neofytou, T.-H. Huang, S. Kambampati, R. Picelli, JS. Chen, and H. A. Kim*. "Level Set Topology Optimization with Nodally Integrated Reproducing Kernel Particle Method." Computer Methods in Applied Mechanics and Engineering. 385 (2021): 114016. DOI: https://doi.org/10.1016/j.cma.2021.114016
T.-H. Huang, JS. Chen*, M. R. Tupek, F. N. Beckwith, J. J. Koester and E. H. Fang. "A Variational Multiscale Immersed Meshfree Formulation for Heterogeneous Materials." Computational Mechanics. 67.4 (2021): 1059-1097. DOI: https://doi.org/10.1007/s00466-020-01968-1
Neofytou, R. Picelli, T.-H. Huang, JS. Chen, and H. A. Kim*." Level Set topology Optimization for Design-Dependent Pressure Loads Using the Reproducing Kernel Particle Method." Structural and Multidisciplinary Optimization. 61 (2020): 1805-1820. DOI: https://doi.org/10.1007/s00158-020-02549-9.
T.-H. Huang, H. Wei, JS. Chen*, and M. Hillman. "RKPM2D: An Open-Source Implementation of Nodally Integrated Reproducing Kernel Particle Method for Solving Partial Differential Equations." Computational Particle Mechanics. 7.2 (2020): 393-433. DOI: https://doi.org/10.1007/s40571-019-00272-x.
T.-H. Huang, JS. Chen*, H. Wei, MJ. Roth, JA. Sherburn, J. Bishop, M. Tupek, and E. Fang. "A MUSCL-SCNI Approach for Meshfree Modeling of Shock Waves in Fluids." Computational Particle Mechanics. 7.2 (2020): 329-350. DOI: https://doi.org/10.1007/s40571-019-00248-x. (SCI Journal)
T.-H. Huang, T.-H. Huang, Y.-S. Lin, C.-H. Chang, S.-W. Chang, C.-S. Chen*. "A Time Integration Method for Phase-Field Modeling." Multiscale Science and Engineering. 1 (2019): 56-69. DOI: https://doi.org/10.1007/s42493-018-00007-9.
T.-H. Huang, C.-S. Chen*, and S.-W. Chang*. "Microcrack Patterns Control the Mechanical Strength in the Biocomposites." Materials & Design. 140 (2018): 505-515. DOI: https://doi.org/10.1016/j.matdes.2017.12.015.
T.-H. Huang, T.-H. Huang, Y.-S. Lin, C.-H. Chang, P.-Y. Chen, S.-W. Chang, C.-S. Chen*. "Phase-Field Modeling of Microstructural Evolution by Freeze Casting Process." Advanced Engineering Materials. 20.3 (2017): 1700343. DOI: https://doi.org/10.1002/adem.201700343. (Journal Cover; Highlighted News in Manufacturing Technology Category of Advanced Science News)

Technical Report

B. Reedlunn*, G. Moutsanidis, Y. Bazilevs, J. Baek, TH. Huang, X. He, K. Taneja, H. Wei, JS. Chen, J. Koester, E. Matteo, C. Mitchell, R. Lander, and T. Dewers. “Initial Simulations of Empty Room Collapse, Rubble Pile Consolidation, and Rubble Pile Permeability at the Waste Isolation Pilot Plant”. Technical Report (SAND2019-15351). Sandia National Laboratories, Albuquerque, NM (SNL-NM), November 2019.

Please check my google scholar page for details of these papers.