scispace - formally typeset
V

Vidyashankar R. Buravalla

Researcher at General Motors

Publications -  36
Citations -  571

Vidyashankar R. Buravalla is an academic researcher from General Motors. The author has contributed to research in topics: Shape-memory alloy & SMA*. The author has an hindex of 14, co-authored 36 publications receiving 547 citations. Previous affiliations of Vidyashankar R. Buravalla include University of Sheffield & General Electric.

Papers
More filters

Models for Shape Memory Alloy Behavior: An overview of modeling approaches

TL;DR: An overview of shape memory alloys (SMA) can be found in this article, where the authors provide a brief introduction to the SMA behavior and the underlying martensitic transformation.
Patent

Reconfigurable tools and/or dies, reconfigurable inserts for tools and/or dies, and methods of use

TL;DR: A reconfigurable tool and/or die geometry and methods of use generally comprise forming at least a portion of a shape defining surface with a shape memory material as discussed by the authors, in response to an activation signal.
Journal ArticleDOI

Advances in damping materials and technology

TL;DR: In the continual search for better damping materials and technologies, significant advances have been made of late as mentioned in this paper, where Functionally Gradient Materials, liquid crystal polymers, magnetostrictive materials and plasma deposited damping coatings have been investigated in the Dynamics Research Group at the University of Sheffield.
Journal ArticleDOI

Effect of mechanical cycling on the stress–strain response of a martensitic Nitinol shape memory alloy

TL;DR: In this article, an experimental investigation into the ambient temperature, load-controlled tension-tension fatigue behavior of a martensitic Nitinol shape memory alloy (SMA) was conducted.
Patent

Tunable vehicle structural members and methods for selectively changing the mechanical properties thereto

TL;DR: In this paper, a tunable structural member for a vehicle is defined as an active material adapted to selectively undergo a change in at least one attribute in response to an activation signal, such as shape memory alloys, shape memory polymers, magnetorheological fluids and elastomers, piezoelectrics, and electroactive polymers.