28 citations · 60 across the 14 of their papers we have counts for
14 papers
Anvil: An integration of artificial intelligence, sampling techniques, and a combined CAD-CFD tool
Harsh Vardhan, Umesh Timalsina, Michael Sandborn +3
In this work, we introduce an open-source integrated CAD-CFD tool, Anvil, which combines FreeCAD for CAD modeling and OpenFOAM for CFD analysis, along with an AI-based optimization…
Sample-Efficient and Surrogate-Based Design Optimization of Underwater Vehicle Hulls
Harsh Vardhan, David Hyde, Umesh Timalsina +2
Physics simulations like computational fluid dynamics (CFD) are a computational bottleneck in computer-aided design (CAD) optimization processes. To overcome this bottleneck, one r…
Constrained Bayesian Optimization for Automatic Underwater Vehicle Hull Design
Harsh Vardhan, Peter Volgyesi, Will Hedgecock +1
Automatic underwater vehicle hull Design optimization is a complex engineering process for generating a UUV hull with optimized properties on a given requirement. First, it involve…
Search for universal minimum drag resistance underwater vehicle hull using CFD
Harsh Vardhan, Janos Sztipanovits
In Autonomous Underwater Vehicles (AUVs) design, hull resistance is an important factor in determining the power requirements and range of vehicle and consequently affect battery s…
Fusion of ML with numerical simulation for optimized propeller design
Harsh Vardhan, Peter Volgyesi, Janos Sztipanovits
In computer-aided engineering design, the goal of a designer is to find an optimal design on a given requirement using the numerical simulator in loop with an optimization method.…
Data efficient surrogate modeling for engineering design: Ensemble-free batch mode deep active learning for regression
Sarthak Kapoor, Harsh Vardhan, Umesh Timalsina +3
High fidelity design evaluation processes such as Computational Fluid Dynamics and Finite Element Analysis are often replaced with data driven surrogates to reduce computational co…
Deep Active Learning for Regression Using -weighted Hybrid Query Strategy
Harsh Vardhan, Janos Sztipanovits
Designing an inexpensive approximate surrogate model that captures the salient features of an expensive high-fidelity behavior is a prevalent approach in design optimization. In re…
Deep Learning-based Finite Element Analysis (FEA) surrogate for sub-sea pressure vessel
Harsh Vardhan, Janos Sztipanovits
During the design process of an autonomous underwater vehicle (AUV), the pressure vessel has a critical role. The pressure vessel contains dry electronics, power sources, and other…
Reduced Robust Random Cut Forest for Out-Of-Distribution detection in machine learning models
Harsh Vardhan, Janos Sztipanovits
Most machine learning-based regressors extract information from data collected via past observations of limited length to make predictions in the future. Consequently, when input t…
Rare event failure test case generation in Learning-Enabled-Controllers
Harsh Vardhan, Janos Sztipanovits
Machine learning models have prevalent applications in many real-world problems, which increases the importance of correctness in the behaviour of these trained models. Finding a g…
DesignBIP: A Design Studio for Modeling and Generating Systems with BIP
Anastasia Mavridou, Joseph Sifakis, Janos Sztipanovits
The Behavior-Interaction-Priority (BIP) framework, rooted in rigorous semantics, allows the construction of systems that are correct-by-design. BIP has been effectively used for th…
DesignBIP: A Design Studio for Modeling and Generating Systems with BIP
Anastasia Mavridou, Joseph Sifakis, Janos Sztipanovits
The Behavior-Interaction-Priority (BIP) framework, rooted in rigorous semantics, allows the construction of systems that are correct-by-design. BIP has been effectively used for th…
Approaches to Enhancing Cyber Resilience: Report of the North Atlantic Treaty Organization (NATO) Workshop IST-153
Alexander Kott, Benjamin Blakely, Diane Henshel +21
This report summarizes the discussions and findings of the 2017 North Atlantic Treaty Organization (NATO) Workshop, IST-153, on Cyber Resilience, held in Munich, Germany, on 23-25…
Anonymously Analyzing Clinical Datasets
Nafees Qamar, Yilong Yang, Andras Nadas +2
This paper takes on the problem of automatically identifying clinically-relevant patterns in medical datasets without compromising patient privacy. To achieve this goal, we treat d…