Publications

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BOOK CHAPTERS

3. Huang, T., Bisram, M., Li, Y., Xu, H., Zeng,D., Su, X., Cao, J., and Chen, W., “Mixed-Variable Concurrent Material, Geometry, and Process Design in Integrated Computational Materials Engineering”. In Machine Learning in Modeling and Simulation: Methods and Applications, pp. 395-426. Cham: Springer International Publishing, 2023.
2. Xu, H., Sheridan, R.J., Brinson, L.C., Chen, W., Jiang, B., Papakonstantopoulos, G., Polinska, P., Burkhart, C., “Data-Driven Multiscale Science for Tire Compounding: Methods and Future Directions”. In Theory and Modeling of Polymer Nanocomposites, pp 281-312. Part of the Springer Series in Materials Science book series (SSMATERIALS, volume 310), 2020.
1. Bostanabad, R., Liang, B., van Beek, A., Gao, J., Liu, W. K., Cao, J., Zeng, D., Su, X., Xu, H., Li, Y. and Chen, W., “Multiscale simulation of fiber composites with spatially varying uncertainties”. In Uncertainty Quantification in Multiscale Materials Modeling, pp. 355-384. Woodhead Publishing, 2020.

JOURNAL PUBLICATIONS

44. Mangrolia, B., Cleeman, J., Patel, A., Wei, S., Shao, C., Xu, H., Malhotra, R., “Continuing Minimal-Defect Production Under Material Integrity Cyberattacks”, Manufacturing Letters, (2024): 40, 54-57.
43. Wang, Z., Xu, H., “Manufacturability-Aware Deep Generative Design of 3D Metamaterial Units for Additive Manufacturing”, Structural and Multidisciplinary Optimization, (2024): 67, no. 2, 22.
42. Xu, L., Naghavi Khanghah, K., Xu, H., ‘‘Designing Mixed-Category Stochastic Microstructures by Deep Generative Model-based and Curvature Functional-based Methods’’, Journal of Mechanical Design, (2024): 146(4), 041702.
41. Chadwick, E., Barrett, A.H., Hobson-Rhoades, W., Okamoto, M., Suleiman Y., Oleksyk, L.E., Xu, H., Shahbazmohamadi, S., Shetty, A., Baker, R., Ma, A., “3D printing confectionaries with tunable mechanical properties”, Journal of Food Engineering, (2024): 111736.
40. Wang, Z., Xian, W., Li, Y., Xu, H., “Embedding Physical Knowledge in Deep Neural Networks for Predicting the Phonon Dispersion Curves of Cellular Metamaterials”, Computational Mechanics, (2023): 72, 221–239.
39. Cao, D., Ji, T., Singh, A., Bak, S., Du, Y., Xiao, X., Xu, H., Zhu, J., Zhu, H., “Unveiling the Mechanical and Electrochemical Evolution of Nano Silicon Composite Anodes in Sulfide based All-solid-state Batteries”, Advanced Energy Materials, (2023): 13(14), p.2203969.
38. Wang, Z., Daeipour, M., Xu, H., “Quantification and Propagation of Aleatoric Uncertainties in Topological Structures”, Reliability Engineering & System Safety, 233 (2023): 109122.
37. Xu, L., Hoffman, N., Wang, Z., Xu, H., “Harnessing Structural Stochasticity in the Computational Discovery and Design of Microstructures”, Materials & Design, 223 (2022): 111223.
36. Kheybari, M., Wang, Z., Xu, H., Bilal, O.R., “Programmability of ultrathin metasurfaces through curvature”, Extreme Mechanics Letters, (2022): 101620.
35. Chinnam, P. R., Xu, L., Cai, L., Cordes, N. L., Kim, S., Efaw, C. M., Murray, D. J., Dufek, E. J., Xu, H., Li, B., “Unlocking Failure Mechanisms and Improvement of Practical Li-S Pouch Cells Through in Operando Pressure Study”, Advanced Energy Materials, (2021), 2103048.
34. Wang, Z., Xian, W., Baccouche, M. R., Lanzerath, H., Li, Y., Xu, H., “Design of Phononic Bandgap Metamaterials based on Gaussian Mixture Beta Variational Autoencoder and Iterative Model Updating”, Journal of Mechanical Design, 144, no. 4, (2022).
33. Xu, H., Zhu, J., Finegan, D. P., Zhao, H., Lu, X., Li, W., Hoffman, N., Bertei, A., Shearing, P., Bazant, M. Z., “Guiding the Design of Heterogeneous Electrode Microstructures for Li-Ion Batteries: Microscopic Imaging, Predictive Modeling, and Machine Learning”, Advanced Energy Materials, 11, no. 19 (2021): 2003908.
32. Du, X., Xu, H., Zhu, F., “Understanding the effect of hyperparameter optimization on machine learning models for structure design problems”, Computer-Aided Design, 135 (2021): 103013.
31. Wang, Z., Xu, H., “Quantitative Representation of Aleatoric Uncertainties in Network-like Topological Structural Systems”, Journal of Mechanical Design, 143.3 (2021): 031713.
30. Du, X., Xu, H., Zhu, F., “A Data Mining Method for Structure Design with Uncertainty in Design Variables”, Computers and Structures, 244 (2021): 106457.
29. Xu, H., Usseglio-Viretta, F., Kench, S., Cooper, S., Finegan, D., “Microstructure Reconstruction of Battery Polymer Separators by Fusing 2D and 3D Image Data for Transport Property Analysis”, Journal of Power Sources, 480 (2020): 229101.
28. Tang, H., Chen, Z., Xu, H., Liu, Z., Sun, Q., Zhou, G., Yan, W., Han, W., Su, X., “Computational Micromechanics Model based Failure Criteria for Chopped Carbon Fiber Sheet Molding Compound Composites”, Composites Science and Technology, 200 (2020): 108400.
27. Pan, Z., Zhu, J., Xu, H., Sedlatschek, T., Zhang, X., Li, W., Gao, T., Xia, Y., Wierzbicki, T., “Microstructural deformation patterns of a highly orthotropic polypropylene separator of lithium-ion batteries: Mechanism, model, and theory”, Extreme Mechanics Letters, 37 (2020): 100705.
26. Xu, H., “Constructing Oscillating Function-based Covariance Matrix to allow Negative Correlations in Gaussian Random Field Models for Uncertainty Quantification”, Journal of Mechanical Design, 142, no.7 (2020).
25. Liu, Z., Xu, H., Zhu, P., “An adaptive multi-fidelity approach for design optimization of mesostructure-structure systems”, Structural and Multidisciplinary Optimization (2020): 1-12.
24. Xu, H., Bae, C., “Stochastic 3D Microstructure Reconstruction and Mechanical Modeling of Anisotropic Battery Separators”, Journal of Power Sources, 430 (2019): 67-73.
23. Xu, H., Liu, Z., “Control variate multi-fidelity estimators for the variance and sensitivity analysis of mesostructure-structure systems”, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 2 (2019): 020907.
22. Chen, Z., Tang, H., Shao, Y., Sun, Q., Zhou, G., Li, Y., Xu, H., Zeng, D., Su, X., “Failure of chopped carbon fiber Sheet Molding Compound (SMC) composites under uniaxial tensile loading: Computational prediction and experimental analysis.” Composites Part A: Applied Science and Manufacturing, 118 (2019): 117-130.
21. Yang, J., Xu, H., Zhan, Z., Chuang, C-H., “A Structural Equation Modeling-Based Strategy for Design Optimization of Multilayer Composite Structural Systems”, Journal of Mechanical Design, 140.11 (2018), 111407.
20. Li, Y., Chen, Z., Su, L., Chen, W., Jin, X., Xu, H., “Stochastic Reconstruction and Microstructure Modeling of SMC Chopped Fiber Composites”, Composite Structures, 200 (2018): 153-164.
19. Bostanabad, R., Liang, B., Gao, J., Liu, W.K., Cao, J., Zeng, D., Su, X., Xu, H., Li, Y., Chen, W., “Uncertainty quantification in multiscale simulation of woven fiber composites”, Computer Methods in Applied Mechanics and Engineering, 338 (2018): 506-532.
18. Chen, Z., Huang, T., Shao, Y., Li, Y., Xu, H., Avery, K., Zeng, D., Chen, W., Su, X., “Multiscale Finite Element Modeling of Sheet Molding Compound (SMC) Composite Structure based on Stochastic Mesostructure Reconstruction”, Composite Structures, 188 (2018): 25-38.
17. Xu, H., Zhu, M., Marcicki, J., and Yang, X. G., “Mechanical Modeling of Battery Separator based on Microstructure Image Analysis and Stochastic Characterization”,Journal of Power Sources, 345 (2017): 137-145.
16. Li, Y., Chen, Z., Xu, H., Dahl, J., Zeng, D., Mirdamadi, M. and Su, X., “Modeling and Simulation of Compression Molding Process for Sheet Molding Compound (SMC) of Chopped Carbon Fiber Composites”,SAE International Journal of Materials and Manufacturing, 10, No. 2017-01-0228 (2017).
15. Xu, H., Li, Y., and Zeng, D., “Process Integration and Optimization of ICME Carbon Fiber Composites for Vehicle Lightweighting: A Preliminary Development”,SAE International Journal of Materials and Manufacturing, 10, No. 2017-01-0229 (2017).
14. Zheng, K., Yang, R., Xu, H., and Hu, J., “A new distribution metric for comparing Pareto optimal solutions”,Structural and Multidisciplinary Optimization, 55, no. 1 (2017): 53-62.
13. Hassinger, I., Li, X., Zhao, H., Xu, H., Huang, Y., Prasad, A., Schadler, L., Chen, W. and Brinson, L.C., “Toward the development of a quantitative tool for predicting dispersion of nanocomposites under non-equilibrium processing conditions”,Journal of Materials Science, 9 (2016), pp.4238-4249.
12. Xu, H., Jiang, Z., Apley, D. W., and Chen, W., “New Metrics for Validation of Data-Driven Random Process Models in Uncertainty Quantification”, Journal of Verification, Validation and Uncertainty Quantification 1, no. 2 (2016): 021002.
11. Xu, H., Chuang, C., and Yang, R., “Towards Optimization of Multi-Material Structure: Metamodeling of Mixed-Variable Problems”,SAE International Journal of Materials and Manufacturing, 9, no. 2016-01-0302 (2016): 400-409.
10. Xu, H., Chuang, C., and Yang, R., “A Data Mining-Based Strategy for Direct Multidisciplinary Optimization.”SAE International Journal of Materials and Manufacturing 2015-01-0479 (2015): 357-363.
9. Xu, H., Liu, R., Choudhary, A. Chen, W., “A Machine Learning-based Design Representation Method for Designing Heterogeneous Microstructures”, Journal of Mechanical Design, 137.5 (2015), 051403.
8. Xu, H., Dikin, D., Chen, W., “Descriptor-based Methodology for Statistical Characterization and 3D Reconstruction for Microstructure Materials”, Computational Material Science, Vol. 85 (2014), 206-216.
7. Xu, H., Li, Y., Brinson, L. C., Chen, W., “A Descriptor-based Design Methodology for Developing Heterogeneous Microstructural Materials System”, Journal of Mechanical Design, 5 (2014): 051007 (JMD Editor’s Choice Paper Award).
6. Majcher, M., Xu, H., Chuang, C., Fu, Y., Yang, R. J., “A Comparative Benchmark Study of using Different Multi-Objective Algorithms for Restraint System Design”,SAE International journal of transportation safety 2014-01-0564 (2014): 301-306.
5. Xu, H., Greene, M. S., Deng, H., Dikin, D., Brinson, L. C., Liu, W. K., Burkhart, C., Papakonstantopoulos, G., Poldneff, M., Chen, W., “A Stochastic Reassembly Strategy for Managing Informatio​n Complexity in Heterogene​ous Materials Analysis and Design”, Journal of Mechanical Design, 135(10), 2013.
4. M. Breneman, L.C. Brinson, L.S. Schadler, B. Natarajan, M. Krein, K. Wu, L. Morkowchuk, Y. Li, H. Deng, H. Xu, “Stalking the Materials Genome: A Data-driven Approach to the Virtual Design of Nanostructured Polymers”, Advanced Functional Materials, DOI: 10.1002/adfm.201301744, 2013.
3. Greene, M. S., Xu, H., Tang, S., Chen, W., Liu, W. K., “A generalized uncertainty propagation criterion from benchmark studies of microstructured material systems”, Computer Methods in Applied Mechanics and Engineering, 254, pp 271-291, 2012.
2. Li, G., Zhang, C., Xu, H., Luo, J., Liu, S., “The Film Behaviors of Grease in Point Contact during Micro-oscillation”. Tribology Letters, 38(3), pp 259-266, 2010.
1. Xu, H., Zhang, C.H., “Finite element analysis of roller bearing based on the plastic material models.” Mech. Eng. 46.11 (2010): 29-35.

    FULL LENGTH CONFERENCE PUBLICATIONS

    25. Liang, J., Du, X., Yi, J., Qian, G., Xie, P., Xu, H., ‘‘Platform Hydrodynamic and Structural Control Co-Optimization for the Floating Offshore Wind Turbines’’, ASME 2023 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, (DETC2023-117541). American Society of Mechanical Engineers, 2023.
    24. Xu, L., Naghavi Khanghah, K., Xu, H., ‘‘Design of Mixed-Category Stochastic Microstructures: A Comparison of Curvature Functional-based and Deep Generative Model-based Methods’’, ASME 2023 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, (DETC2023-114601). American Society of Mechanical Engineers, 2023.
    23. Thompson, A., Stuber, M.D., Han, S., Dutta, A., Xu, H., Zhou, S., Yang, Q., Miao, F. and Bollas, G.M., ‘‘Applying a Competency-Based Education Approach for Designing a Unique Interdisciplinary Graduate Program: A Case Study for a Systems Engineering Program’’, In 2023 ASEE Annual Conference & Exposition, June 25-28 2023.
    22. Burkhart, C., Jiang, B., Papakonstantopoulos, G., Polinska, P., Xu, H., Sheridan, R. J., Brinson, L. C., and Chen, W., ‘‘Data-Driven Multiscale Science for Tread Compounding’’, Tire Science and Technology, TSTCA, Vol. 51, No. 2, April–June 2023, pp. 114–131.
    21. Wang, Z., Zhuang, R., Xian, W., Tian, J., Li, Y., Chen, S., Xu, H., “Phononic Metamaterial Design via Transfer Learning-Based Topology Optimization Framework’’, ASME 2022 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Vol. 86229, p. V03AT03A048 (DETC2022-89932). American Society of Mechanical Engineers, 2022.
    20. Wang, Z., Xian, W., Baccouche, M. R., Lanzerath, H., Li, Y., Xu, H., “A Gaussian mixture variational autoencoder-based approach for designing phononic bandgap metamaterials’’, ASME 2021 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, vol. 85390, p. V03BT03A002 (IDETC2021- 67629). American Society of Mechanical Engineers, 2021.
    19. Li, Y., Li, Z., Lai, W.J., Xu, H., Xue, Z., Su, X. and Gao, Z., 2021. “Machine Learning Based Parameter Calibration for Multi-Scale Material Modeling of Laser Powder Bed Fusion (L-PBF) AlSi10Mg’’, (No. 2021-01-0309). SAE Technical Paper, (2021).
    18. Du, X., Bilgen, O., Xu, H., “Generating Pseudo-Data to Enhance the Performance of Classification-based Engineering Design: a Preliminary Investigation”, ASME 2020 International Mechanical Engineering Congress and Exposition (IMECE), IMECE2020-24634.
    17. Wang, Z., Xu, H.*, “Quantification of Uncertainties distributed in Network-like Systems, ASME 2020 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference (IDETC/CIE), IDETC2020-15955.
    16. Wang, Z., Xu, H., Li, Y., “Material Model Calibration by Deep Learning for Additively Manufactured Alloys”, ASME 2020 International Symposium on Flexible Automation, ISFA2020-9640.
    15. Li, Y., Xu, H., Lai, W.J., Li, Z., Su, X., A Multiscale Material Modeling Approach to Predict the Mechanical Properties of Powder Bed Fusion (PBF) Metal, ASTM International’s STP: Selected Technical Papers, in Structural Integrity of Additive Manufactured Materials & Parts, edited by Shamsaei, N. and Seifi, M. (West Conshohocken, PA: ASTM International, 10.1520/STP163120190135), pp.203-213, 2020.
    14. Vogiatzis, P., Chen, S., Gu, X.D., Chuang, C.H., Xu, H. and Lei, N., “Multi-Material Topology Optimization of Structures Infilled With Conformal Metamaterials”. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (Vol. 51760, p. V02BT03A009). American Society of Mechanical Engineers, 2018.
    13. Yang, J., Chuang, C.H., Zhan, Z., Fang, Y., Xu, H. and Guo, G., A Data Mining and Optimization Process with Shape and Size Design Variables Consideration for Vehicle Application (No. 2018-01-0584). SAE Technical Paper (2018).
    12. Liu, Z., Zhu, P., Wang, L., Chuang, C.H. and Xu, H., Multidisciplinary optimization of auto-body lightweight design using hybrid metamodeling technique and particle swarm optimizer. SAE International Journal of Materials and Manufacturing, 11(4), pp.373-384, (2018).
    11. Chen, Z., Wang, M., Shao, Y., Sun, Q., Tang, H., Xu, H., Avery, K., Zeng, D., Su, X., “A Comparative Study of Two ASTM Shear Test Standards for Chopped Carbon Fiber SMC”, SAE Technical Paper 2018-01-0098, (2018).
    10. Xu, H., Yang, J., Chuang, C., and Zhan, Z., “Study of the Design Representative Methods for the Optimization of Multi-layer Composite Structures”, ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC2017-67309.
    9. Chen, Z., Li, Y., Shao, Y., Huang, T., Xu, H., Li, Y., Chen, W., Zeng, D., Avery, K., Kang, H. and Su, X., “A Comparative Study of Two RVE Modelling Methods for Chopped Carbon Fiber SMC”, SAE Technical Paper, No. 2017-01-0224.
    8. Zhao, X., Xi, Z., Xu, H. and Yang, R.J., “Model Bias Characterization Considering Discrete and Continuous Design Variables”, ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC2016-60109.
    7. Xu, H., Chuang, C.H. and Yang, R.J., “Mixed-Variable Metamodeling Methods for Designing Multi-Material Structures”, ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC2016-59176.
    6. Li, Y., Chen, W., Jin, X., and Xu, H., “3D Representative Volume Element Reconstruction of Fiber Composites via Orientation Tensor and Substructure Features”, Proceedings of the American Society for Composites: Thirty-First Technical Conference. 2016.
    5. Xu, H., Chuang, C., and Yang, R., “Improving Multiobjective Multidisciplinary Optimization with a Data Mining-based Hybrid Method”, ASME 2015 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC2015-47361.
    4. Xu, H., Liu, R., Choudhary, A. Chen, W., “A Machine Learning-based Design Representation Method for Designing Heterogeneous Microstructures”, ASME 2014 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC2014-34570 (Best Paper Award).
    3. Xu, H., Majcher, M., Chuang, C., Fu, Y., Yang, R. J., “Comparative Benchmark Studies of Response Surface Model-based Optimization and Direct Multidisciplinary Design Optimization”, SAE World Congress 2014.
    2. Xu, H., Li, Y., Brinson, L. C., Chen, W., “Descriptor-based Methodology for Designing Heterogeneous Materials System”, ASME 2013 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC2013-12232.
    1. Xu, H., Greene, M. S., Deng, H., Brinson, L. C., Dikin, D., Chen, W., “Stochastic Reassembly for Managing the Information Complexity in Multilevel Analysis of Heterogeneous Materials”, ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC2012-70668 (Best Paper Award).

    PATENTS

    • Xu, H., Friske, D.D., Selvasekar, S., Lee, E., Chuang, C.H. and Pfeiffer, J.J., “Article with solid, lattice, and hollow sub-regions.” U.S. Patent Application 15/879,852, filed July 25, 2019. Application number: US20190224910A1. Patent number: US10906236B2.
    • Xu, H., Selvasekar, S., Chuang, C., and Lee, E., “Integrated digital thread for additive manufacturing design optimization of lightweight structures.” U.S. Patent Application 15/817,330, filed May 23, 2019. Application number: US20190152150A1. Patent number: US11351732B2.

    INVITED TALKS

    • Generative Design of Mixed-Category Microstructures”, Northeastern University, Mar 28, 2023
    • Quantification of Aleatoric Uncertainties in Topological Structures, and Physics-informed Machine Learning Model for Phononic Property Prediction”, GE Research, Sept 29, 2022
    • Deep Generative Design of Complex Deterministic and Stochastic Structures for Additive Manufacturing”, GE Research, July 20, 2022
    • Tailoring Structural Stochasticity in Property-Driven Computational Microstructure Design”, Invited Keynote in USNC/TAM 2022, June 21, 2022
    • Computational Modeling of Battery Separator Microstructure by Statistical Characterization and Stochastic Reconstruction”, ECS Chapter – Purdue Fall 2020 Webinar Series , Dec 7, 2020
    • Uncertainty Quantification Methods for the Computational Design of Microstructure-Structure Systems”, Dassault Systemes Simulia Corporation, Jan 21, 2020
    • Failure Model of Separators based on Statistical Analysis of Microstructures”, 11th MIT workshop on Computational Modeling of Lithium-ion Batteries for Crash Safety, Nov 13, 2019
    • Uncertainty Quantification Methods for Stochastic Microstructure Characterization and Reconstruction”, Stony Brook University, Oct 25, 2019
    • Computational Design and Uncertainty Quantification of Microstructure, Mesostructure, and Structure”, Rutgers University, Jan 19, 2018
    • Application of data mining methods in direct and RSM-based optimization”, ESTECO Academy Workshop, Wayne State University, Jun 9, 2016