Multi-Physical Modeling
Optimal design & robust control through multi-physical modeling.
Our work involves the development of state-of-art modeling and simulation tools for complex, heterogeneous systems. We apply these models for the optimal design and robust control of a variety of systems including HVAC systems, zero-energy buildings, automobiles, and robotic systems.
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Researchers
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News & Events
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NEWS Ankush Chakrabarty gave an invited talk at University of Illinois at Chicago Date: April 9, 2021
MERL Contact: Ankush Chakrabarty
Research Areas: Control, Machine Learning, Multi-Physical Modeling, OptimizationBrief- Ankush Chakrabarty, a Research Scientist at MERL's Multiphysical Systems (MS) Team, gave an invited talk on "Learning for Control and Estimation using Digital Twins" at the Department of Electrical and Computer Engineering Seminar Series organized at UIC. The talk proposed new learning-based control/estimation architectures that can utilize simulation data obtained from digital twins to add self-optimization and constraint-enforcement features to grey/black-box control systems.
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EVENT MERL Virtual Open House 2020 Date & Time: Wednesday, December 9, 2020; 1:00-5:00PM EST
MERL Contacts: Elizabeth Phillips; Jeroen van Baar; Anthony Vetro
Location: Virtual
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & AudioBrief- MERL will host a virtual open house on December 9, 2020. Live sessions will be held from 1-5pm EST, including an overview of recent activities by our research groups and a talk by Prof. Pierre Moulin of University of Illinois at Urbana-Champaign on adversarial machine learning. Registered attendees will also be able to browse our virtual booths at their convenience and connect with our research staff on engagement opportunities including internship, post-doc and research scientist openings, as well as visiting faculty positions.
Registration: https://mailchi.mp/merl/merl-virtual-open-house-2020
Schedule: https://www.merl.com/events/voh20
Current internship and employment openings:
https://www.merl.com/internship/openings
https://www.merl.com/employment/employment
Information about working at MERL:
https://www.merl.com/employment
- MERL will host a virtual open house on December 9, 2020. Live sessions will be held from 1-5pm EST, including an overview of recent activities by our research groups and a talk by Prof. Pierre Moulin of University of Illinois at Urbana-Champaign on adversarial machine learning. Registered attendees will also be able to browse our virtual booths at their convenience and connect with our research staff on engagement opportunities including internship, post-doc and research scientist openings, as well as visiting faculty positions.
See All News & Events for Multi-Physical Modeling -
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Internships
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MD1593: Design Optimization for Electric Machines
MERL is seeking a motivated and qualified intern to conduct research on design optimization of electrical machines. The ideal candidate should have solid background and demonstrated research experience in mathematical optimization methods, especially in topology optimization, robust optimization, sensitivity analysis, and machine learning techniques. Hands-on experiences with the implementation of optimization algorithms, machine learning and deep learning methods are highly desirable. Knowledge and experience with electric machine principle, design and finite-element analysis is a strong plus. Senior Ph.D. students in related expertise are encouraged to apply. Start date for this internship is flexible and the duration is about 3-6 months. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.
See All Internships for Multi-Physical Modeling -
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Recent Publications
- , "Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning", IEEE Transactions on Industry Applications, DOI: 10.1109/TIA.2021.3091958, June 2021.BibTeX TR2021-081 PDF
- @article{Zhang2021jun,
- author = {Zhang, Shen and Ye, Fei and Wang, Bingnan and Habetler, Thomas G},
- title = {Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning},
- journal = {IEEE Transactions on Industry Applications},
- year = 2021,
- month = jun,
- doi = {10.1109/TIA.2021.3091958},
- url = {https://www.merl.com/publications/TR2021-081}
- }
- , "Patch-based Thermodynamic Property Models for the Subcritical Region", Purdue Air-Conditioning and Refrigeration Conference, May 2021.BibTeX TR2021-053 PDF
- @inproceedings{Laughman2021may,
- author = {Laughman, Christopher R. and Qiao, Hongtao},
- title = {Patch-based Thermodynamic Property Models for the Subcritical Region},
- booktitle = {Purdue Air-Conditioning and Refrigeration Conference},
- year = 2021,
- month = may,
- url = {https://www.merl.com/publications/TR2021-053}
- }
- , "High-Torque Direct-Drive Machine with Combined Axial- and Radial-flux Out-runner Vernier Permanent Magnet Motor", International Electric Machine & Drives Conference (IEMDC), DOI: 10.1109/IEMDC47953.2021.9449499, May 2021, pp. 1-8.BibTeX TR2021-050 PDF
- @inproceedings{Zhou2021may,
- author = {Zhou, Lei and Guo, Feng and Wang, Hongyu and Wang, Bingnan},
- title = {High-Torque Direct-Drive Machine with Combined Axial- and Radial-flux Out-runner Vernier Permanent Magnet Motor},
- booktitle = {2021 IEEE International Electric Machines Drives Conference (IEMDC)},
- year = 2021,
- pages = {1--8},
- month = may,
- publisher = {IEEE},
- doi = {10.1109/IEMDC47953.2021.9449499},
- url = {https://www.merl.com/publications/TR2021-050}
- }
- , "Static Eccentricity Fault Detection for PSH-type Induction Motors Considering High-order Air Gap Permeance Harmonics", International Electric Machine & Drives Conference (IEMDC), DOI: 10.1109/IEMDC47953.2021.9449496, May 2021, pp. 1-7.BibTeX TR2021-051 PDF
- @inproceedings{Zhou2021may2,
- author = {Zhou, Lei and Wang, Bingnan and Lin, Chungwei and Miyoshi, Masahito and Inoue, hiroshi},
- title = {Static Eccentricity Fault Detection for PSH-type Induction Motors Considering High-order Air Gap Permeance Harmonics},
- booktitle = {2021 IEEE International Electric Machines Drives Conference (IEMDC)},
- year = 2021,
- pages = {1--7},
- month = may,
- publisher = {IEEE},
- doi = {10.1109/IEMDC47953.2021.9449496},
- url = {https://www.merl.com/publications/TR2021-051}
- }
- , "Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks", AAAI Spring Symposium on Combining Artificial Intelligence with Physical Sciences, March 2021.BibTeX TR2021-021 PDF
- @inproceedings{Anantharaman2021mar,
- author = {Anantharaman, Ranjan and Ma, Yingbo and Gowda, Shashi and Laughman, Christopher R. and Shah, Viral and Edelman, Alan and Rackauckas, Chris},
- title = {Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks},
- booktitle = {AAAI Spring Symposium on Combining Artificial Intelligence with Physical Sciences},
- year = 2021,
- month = mar,
- url = {https://www.merl.com/publications/TR2021-021}
- }
- , "Modelica-Based Control of A Delta Robot", ASME Dynamic Systems and Control Conference, DOI: doi.org/10.1115/DSCC2020-3158, December 2020.BibTeX TR2020-154 PDF
- @inproceedings{Bortoff2020dec,
- author = {Bortoff, Scott A. and Okasha, Ahmed},
- title = {Modelica-Based Control of A Delta Robot},
- booktitle = {ASME Dynamic Systems and Control Conference},
- year = 2020,
- month = dec,
- doi = {doi.org/10.1115/DSCC2020-3158},
- url = {https://www.merl.com/publications/TR2020-154}
- }
- , "Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks", Advances in Neural Information Processing Systems (NeurIPS), December 2020.BibTeX TR2020-169 PDF
- @inproceedings{Anantharaman2020dec,
- author = {Anantharaman, Ranjan and Ma, Yingbo and Gowda, Shashi and Laughman, Christopher R. and Shah, Viral and Edelman, Alan and Rackauckas, Chris},
- title = {Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2020,
- month = dec,
- url = {https://www.merl.com/publications/TR2020-169}
- }
- , "End-to-End Deep Learning for Phase Noise-Robust Multi-Dimensional Geometric Shaping", European Conference on Optical Communication (ECOC), DOI: 10.1109/ECOC48923.2020.9333382, November 2020.BibTeX TR2020-155 PDF Video
- @inproceedings{Talreja2020nov,
- author = {Talreja, Veeru and Koike-Akino, Toshiaki and Wang, Ye and Millar, David S. and Kojima, Keisuke and Parsons, Kieran},
- title = {End-to-End Deep Learning for Phase Noise-Robust Multi-Dimensional Geometric Shaping},
- booktitle = {European Conference on Optical Communication (ECOC)},
- year = 2020,
- month = nov,
- publisher = {IEEE},
- doi = {10.1109/ECOC48923.2020.9333382},
- isbn = {978-1-7281-7361-0},
- url = {https://www.merl.com/publications/TR2020-155}
- }
- , "Few-Shot Bearing Fault Diagnosis Based on Model-Agnostic Meta-Learning", IEEE Transactions on Industry Applications, DOI: 10.1109/TIA.2021.3091958, June 2021.
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Videos
