A5065750502- Cellular and Composite Structures
- Industrial Vision Systems and Defect Detection
- Automotive and Human Injury Biomechanics
- Robotic Locomotion and Control
- Industrial Technology and Control Systems
- Advanced Measurement and Detection Methods
- Intelligent Tutoring Systems and Adaptive Learning
- Vehicle Dynamics and Control Systems
- Manufacturing Process and Optimization
- AI and HR Technologies
- Online Learning and Analytics
- Mechanics and Biomechanics Studies
- Infrared Target Detection Methodologies
- Transportation Safety and Impact Analysis
- Robotic Mechanisms and Dynamics
- Chaos, Complexity, and Education
RWTH Aachen University
2023-2024
MIT Academy of Engineering
2021-2023
MIT Art, Design and Technology University
2021
Abstract Data-based methods have gained increasing importance in engineering. Success stories are prevalent areas such as data-driven modeling, control, and automation, well surrogate modeling for accelerated simulation. Beyond engineering, generative large-language models increasingly helping with tasks that, previously, were solely associated creative human processes. Thus, it seems timely to seek artificial-intelligence-support engineering design automate, help with, or accelerate...
Abstract The primary goal of the current study is to optimise crash box designs for automobiles. Machine learning (ML) techniques are used build an intelligent and reliable ML framework. With help this framework, design can be optimised crashworthiness analysis. optimisation resource‐intensive due its intricate geometric design, use a variety materials, extensive dynamic simulations determine ideal structural parameters through simulations. A reinforcement learning‐based (RL) optimization...
Abstract This study focuses on the optimization process of crash box design. The design is resource‐intensive and requires multiple dynamic simulations. Numerous parameters can be varied to satisfy crashworthiness objectives. Therefore an intelligent robust machine learning (ML) framework has been developed. employed assist in various components with different Here, a reinforcement learning‐based (RL) It consists finite element method (FEM) surrogate RL environment. FEM trained using data...
Data-based methods have gained increasing importance in engineering, especially but not only driven by successes with deep artificial neural networks. Success stories are prevalent, e.g., areas such as data-driven modeling, control and automation, well surrogate modeling for accelerated simulation. Beyond generative large-language models increasingly performing helping tasks that, previously, were solely associated creative human processes. Thus, it seems timely to seek...
Optimisation for crashworthiness is a critical part of the vehicle development process. Due to stringent regulations and increasing market demands, multiple factors must be considered within limited timeframe. However, optimal design, multiobjective optimisation necessary, complex parts, design parameters evaluated. This analysis requires computationally intensive finite element simulations. challenge leads need inverse multi-parameter multi-objective optimisation. multi-parameter, article...
It is impossible to imagine an industry without a machine. Huge number of machines are working together in industry. Many times if the failure occurs machine it becomes challenging task identify it. Fault may occur due various reasons. Here main focus on identifying fault occurred fine crack metal body. Faulty spare parts can be easily identified and replaced. But finding body difficult work out. To find out such type faults disassembling only option. Disassembling any not that much easy...