21 citations · 37 across the 7 of their papers we have counts for
9 papers
A mapping-based projection of detailed kinetics uncertainty onto reduced manifolds
Vansh Sharma, Shuzhi Zhang, Rahul Jain +1
Propagating uncertainties introduced by chemical reaction rate parameters to high-fidelity numerical simulations of complex combustion devices is necessary to ascertain impact on c…
An Approximate Graph Elicits Detonation Lattice
Vansh Sharma, Venkat Raman
This study presents a novel algorithm based on graph theory for the precise segmentation and measurement of detonation cells from 3D pressure traces, termed detonation lattices, ad…
Chain of Unit-Physics: A Primitive-Centric Approach to Scientific Code Synthesis
Vansh Sharma, Venkat Raman
Agentic large language models are proposed as autonomous code generators for scientific computing, yet their reliability in high-stakes problems remains unclear. Developing computa…
AutoHood3D: A Multi-Modal Benchmark for Automotive Hood Design and Fluid-Structure Interaction
Vansh Sharma, Harish Jai Ganesh, Maryam Akram +2
This study presents a new high-fidelity multi-modal dataset containing 16000+ geometric variants of automotive hoods useful for machine learning (ML) applications such as engineeri…
Automated Design Optimization via Strategic Search with Large Language Models
Anthony Carreon, Vansh Sharma, Venkat Raman
Optimization methods have long advanced many fields, yet they struggle when faced with design problems where the search space and design parameters are difficult to define. Large l…
Steering Conceptual Bias via Transformer Latent-Subspace Activation
Vansh Sharma, Venkat Raman
This work examines whether activating latent subspaces in language models (LLMs) can steer scientific code generation toward a specific programming language. Five causal LLMs were…
An AMReX-based Compressible Reacting Flow Solver for High-speed Reacting Flows relevant to Hypersonic Propulsion
Shivank Sharma, Ral Bielawski, Oliver Gibson +8
This work presents a comprehensive framework for the efficient implementation of finite-volume-based reacting flow solvers, specifically tailored for high speed propulsion applicat…
A Machine Learning Based Approach for Statistical Analysis of Detonation Cells from Soot Foils
Vansh Sharma, Michael Ullman, Venkat Raman
This study presents a novel algorithm based on machine learning (ML) for the precise segmentation and measurement of detonation cells from soot foil images, addressing the limitati…
A Reliable Knowledge Processing Framework for Combustion Science using Foundation Models
Vansh Sharma, Venkat Raman
This research explores the integration of large language models (LLMs) into scientific data assimilation, focusing on combustion science as a case study. Leveraging foundational mo…