A5054166011- Additive Manufacturing Materials and Processes
- Additive Manufacturing and 3D Printing Technologies
- Welding Techniques and Residual Stresses
- Manufacturing Process and Optimization
- High Entropy Alloys Studies
- Stock Market Forecasting Methods
- Machine Learning in Materials Science
- High Temperature Alloys and Creep
- Forecasting Techniques and Applications
- Advanced Welding Techniques Analysis
- Titanium Alloys Microstructure and Properties
- Iron and Steelmaking Processes
- Hydrology and Watershed Management Studies
- Neural Networks and Applications
- Solidification and crystal growth phenomena
- Hydrology and Sediment Transport Processes
- Geochemistry and Geologic Mapping
- Market Dynamics and Volatility
- Aluminum Alloy Microstructure Properties
- Metallurgical Processes and Thermodynamics
- Laser Material Processing Techniques
- Extraction and Separation Processes
- Consumer Retail Behavior Studies
- Mineral Processing and Grinding
- Flood Risk Assessment and Management
Iowa State University
2023-2025
Pennsylvania State University
2016-2024
Indian Institute of Technology Roorkee
2024
M S Ramaiah University of Applied Sciences
2024
Sardar Vallabhbhai National Institute of Technology Surat
2023
University of Kalyani
2012-2023
TERI University
2014
Ramakrishna Mission Vidyamandira
2010
Although additive manufacturing (AM), or three dimensional (3D) printing, provides significant advantages over existing techniques, metallic parts produced by AM are susceptible to distortion, lack of fusion defects and compositional changes. Here we show that the printability, ability an alloy avoid these defects, can be examined developing testing appropriate theories. A theoretical scaling analysis is used test vulnerability various alloys thermal distortion. kinetic model examine...
Additive manufacturing (AM), also known as 3D printing, is gaining wide acceptance in diverse industries for the of metallic components. The microstructure and properties components vary widely depending on printing process parameters, prediction causative variables that affect structure, defects helpful their control. Since models are most useful when they can correctly predict experimental observations, we focus available mechanistic AM have been adequately validated. Specifically,...
The effects of many process variables and alloy properties on the structure additively manufactured parts are examined using four dimensionless numbers. components made from 316 Stainless steel, Ti-6Al-4V, Inconel 718 powders for various heat inputs, Peclet numbers, Marangoni Fourier numbers studied. Temperature fields, cooling rates, solidification parameters, lack fusion defects, thermal strains a well-tested three-dimensional transient transfer fluid flow model. results show that defects...
Shielding gas, metal vapors, and gases trapped inside powders during atomization can result in gas porosity, which is known to degrade the fatigue strength tensile properties of components made by laser powder bed fusion additive manufacturing. Post-processing trial-and-error adjustment processing conditions reduce porosity are time-consuming expensive. Here, we combined mechanistic modeling experimental data analysis proposed an easy-to-use, verifiable, dimensionless index mitigate pore...
Abstract Friction stir welded joints often contain voids that are detrimental to their mechanical properties. Here we investigate the conditions for void formation using a decision tree and Bayesian neural network. Three types of input data sets including unprocessed welding parameters computed variables an analytical numerical model friction were examined. One hundred eight independent experimental on three aluminum alloys, AA2024, AA2219, AA6061, analyzed. The network-based analysis with...
Abstract Machine learning algorithms are a natural fit for printing fully dense superior metallic parts since 3D embodies digital technology like no other manufacturing process. Since traditional machine needs large volume of reliable historical data to optimize many variables, the algorithm is augmented with human intelligence derived from rich knowledge base metallurgy and physics-based models. The augmentation improves computational efficiency makes problem tractable by enabling use small...