6 citations · 8 across the 7 of their papers we have counts for
8 papers
Three-Dimensional Simulation of Flood Propagation at Syabrubesi, Nepal
Rainald Löhner, Harbir Antil
Three-dimensional flood propagation through the Bhote Koshi--Langtang Khola junction at Syabrubesi, Nepal, is studied using an incompressible free-surface model. The calculation is…
Polarization-Induced Beam Bending: Mathematical Model, Discretization, and Algorithm
Harbir Antil, Rainald Löhner, Sarswati Shah
We study a reduced hydrodynamic formulation of paraxial vector beam propagation in which the beam intensity, optical phase, and spatially-dependent polarization are coupled through…
High-Fidelity Digital Twins: Detecting and Localizing Weaknesses in Structures
Rainald Löhner, Facundo N. Airaudo, Harbir Antil +3
An adjoint-based procedure to determine weaknesses, or, more generally, the material properties of structures is developed and tested. Given a series of load cases and correspondin…
Adjoint-based Determination of Weaknesses in Structures
Facundo N. Airaudo, Rainald Löhner, Roland Wüchner +1
An adjoint-based procedure to determine weaknesses, or, more generally the material properties of structures is developed and tested. Given a series of force and deformation/strain…
Adjoint-Based Estimation of Sensitivity of Clinical Measures to Boundary Conditions for Arteries
Rainald Löhner, Harbir Antil, Juan Cebral +1
The use of adjoint solvers is considered in order to obtain the sensitivity of clinical measures in aneurysms to incomplete (or unknown) boundary conditions and/or geometry. It is…
A Deterministic Pathogen Transmission Model Based on High-Fidelity Physics
Rainald Löhner, Harbir Antil, Juan Marcelo Gimenez +2
A deterministic pathogen transmission model based on high-fidelity physics has been developed. The model combines computational fluid dynamics and computational crowd dynamics in o…
Data Assimilation with Deep Neural Nets Informed by Nudging
Harbir Antil, Rainald Löhner, Randy Price
The nudging data assimilation algorithm is a powerful tool used to forecast phenomena of interest given incomplete and noisy observations. Machine learning is becoming increasingly…
Deep Neural Nets with Fixed Bias Configuration
Harbir Antil, Thomas S. Brown, Rainald Löhner +2
For any given neural network architecture a permutation of weights and biases results in the same functional network. This implies that optimization algorithms used to `train' or `…