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Your search keyword '"Das, Shuvajit"' showing total 38 results
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38 results on '"Das, Shuvajit"'

3. Brief Report: Development of a Robotic Intervention Platform for Young Children with ASD

Author

Warren, Zachary, Zheng, Zhi, and Das, Shuvajit

Abstract

Increasingly researchers are attempting to develop robotic technologies for children with autism spectrum disorder (ASD). This pilot study investigated the development and application of a novel robotic system capable of dynamic, adaptive, and autonomous interaction during imitation tasks with embedded real-time performance evaluation and feedback. The system was designed to incorporate both a humanoid robot and a human examiner. We compared child performance within system across these conditions in a sample of preschool children with ASD (n = 8) and a control sample of typically developing children (n = 8). The system was well-tolerated in the sample, children with ASD exhibited greater attention to the robotic system than the human administrator, and for children with ASD imitation performance appeared superior during the robotic interaction.

Published
2015
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4. Design Aspects, Challenges and Benefits of SiC-Based Integrated Switched Reluctance Machine Drives

Author

Haque, Md Ehsanul, primary, Chowdhury, Anik, additional, Rahman, Mohammad Arifur, additional, Das, Shuvajit, additional, Bandarkar, Abdul Wahab, additional, Bin Tarek, Md Tawhid, additional, Boler, Okan, additional, Sozer, Yilmaz, additional, Siddiquee, Ashraf, additional, Geither, Jeffrey, additional, Colavincenzo, David, additional, and Venegas, Fernando, additional

Published
2022
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7. Brief Report: Development of a Robotic Intervention Platform for Young Children with ASD

Author

Warren, Zachary, Zheng, Zhi, Das, Shuvajit, Young, Eric M., Swanson, Amy, Weitlauf, Amy, and Sarkar, Nilanjan

Subjects
Pervasive developmental disorders -- Care and treatment -- Research, Robotics -- Usage, Health
Abstract

Increasingly researchers are attempting to develop robotic technologies for children with autism spectrum disorder (ASD). This pilot study investigated the development and application of a novel robotic system capable of dynamic, adaptive, and autonomous interaction during imitation tasks with embedded real-time performance evaluation and feedback. The system was designed to incorporate both a humanoid robot and a human examiner. We compared child performance within system across these conditions in a sample of preschool children with ASD (n = 8) and a control sample of typically developing children (n = 8). The system was well-tolerated in the sample, children with ASD exhibited greater attention to the robotic system than the human administrator, and for children with ASD imitation performance appeared superior during the robotic interaction., Author(s): Zachary Warren[sup.1] , Zhi Zheng[sup.2] , Shuvajit Das[sup.3] , Eric M. Young[sup.4] , Amy Swanson[sup.6] , Amy Weitlauf[sup.5] , Nilanjan Sarkar[sup.2] [sup.4] Author Affiliations: (1) Department of Pediatrics, Psychiatry, [...]

Published
2015
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21. High-Fidelity Analysis With Multiphysics Simulation for Performance Evaluation of Electric Motors Used in Traction Applications

Author

Ortega, Alejandro J. Pina, Das, Shuvajit, Islam, Rakibul, and Kouhshahi, Mojtaba Bahrami

Abstract

A Multi-physics simulation workflow encompassing soft-coupling of electromagnetic, thermal, and NVH (noise, vibration, and harshness) for performance evaluation of the traction drive is proposed in the paper. This study focuses on modeling of the electrical components of the drive unit that includes battery, inverter, and the electric machine. Further, a high-fidelity electric machine model is presented considering the non-idealities introduced by temperature variation, manufacturing process and phase current harmonics. The high-fidelity model is used to simulate electric motors like the ones used in the Tesla Model 3, Jaguar I-Pace and Chevy Bolt battery electric vehicles. Moreover, an in-house design is built and tested to validate the fidelity of the workflow.

Published
2023
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22. Comparison of Electric Machine Types for Electrically Driven Engine Accessories Using Multiphysics Simulation Tools

Author

Vadamodala, Lavanya, primary, Das, Shuvajit, additional, Gundogmus, Omer, additional, Sozer, Yilmaz, additional, Chowdhury, Anik, additional, Bandarkar, Abdul W., additional, Harasis, Salman, additional, Chowdhury, Sifat M., additional, Haque, Ehsanul, additional, Husain, Tausif, additional, Venegas, Fernando, additional, Colavincenzo, David, additional, and Geither, Jeffrey, additional

Published
2021
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23. DC-Link Current Ripple Reduction in Switched Reluctance Machine Drives

Author

Haque, Md Ehsanul, primary, Chowdhury, Anik, additional, Chowdhury, Sifat Morshed, additional, Harasis, Salman, additional, Das, Shuvajit, additional, Sozer, Yilmaz, additional, Gundogmus, Omer, additional, Vadamodala, Lavanya, additional, Venegas, Fernando, additional, Colavincenzo, David, additional, and Geither, Jeffrey, additional

Published
2021
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38. A Semi-Analytical Approach to Noise and Vibration Performance Optimization in Electric Machines

Author

Das, Shuvajit

Subjects
Electromagnetics, Electrical Engineering, Engineering, Automotive Engineering, Electromagnetism, Mechanical Engineering, Technology, Electric machines, NVH, Damping, Rayleigh damping, NVH optimization, NVH mitigation, Stator bridges, SRM, Switched reluctance machine, PMSM, Permanent magnet synchronous machines, Noise reduction, Multi-physics modeling, NVH measurement, Electric machine design, Electric machine optimization, Multi-objective optimization
Abstract

Acoustic noise and vibration prediction, mitigation, and performance optimization, in electric machines, are studied in this dissertation. First, vibration prediction enhancement in electric machines through frequency-dependent damping characterization is proposed in this dissertation. Different methods of mass and stiffness-dependent Rayleigh damping coefficient calculation are studied to identify the best damping estimation strategy. The proposed damping estimation strategy is used to predict the vibration spectrums of two 12-slot 10-pole (12s10p) permanent magnet synchronous machine (PMSM) designs and predicted vibration spectrums are experimentally validated through run-up tests of two prototypes. Moreover, to eliminate the dependency of the damping estimation strategy on the availability of a prototype, a damping coefficient prediction methodology is proposed. The proposed prediction methodology is experimentally validated using a third 12s10p PMSM prototype. Secondly, a lumped unit response-based sensitivity analysis procedure is introduced, which isolates electromagnetic and structural impacts brought by variation of different design parameters in an electric machine. The lumped unit response strategy utilizes the frequency-dependent damping estimation method developed early in the dissertation. The impact of different generic design parameters and a structural feature on a range of output quantities are studied in detail for a 12s10p PMSM. Analysis reveals that on a 12s10p PMSM, slot opening has a very high impact on the dominant airgap force component. A multi-level non-linear regression model-based optimization strategy is introduced considering electromagnetic and structural design objectives and constraints following the sensitivity analysis. A 12s10p PMSM prototype is tested to validate the FEA simulations used during the optimization process. Finally, the lumped unit response-based vibration prediction methodology developed in this dissertation is applied to perform a multi-speed point optimization of a targeted feature in switched reluctance machine (SRM) to mitigate acoustic noise and vibration. The targeted feature is stator pole bridges and it is applied to a 24-slot 16-pole (24s/16p) SRM. Average torque reduction due to flux shorting in stator pole bridges is addressed by utilizing a material with low magnetic permeability for the bridges. Multi-physics aspects and manufacturing issues of stator pole bridge design are presented in the chapter. The enhanced vibration prediction methodology proposed in this dissertation is used to perform a wide speed range optimization of stator pole bridge thickness. Following the optimization, two 100-kW SRM prototypes are built. Experimental results verify simulation-based predictions and report a maximum noise reduction of 12.52 dBA in the stator pole bridge model compared to the baseline SRM with no bridges.

Published
2021

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