collaborators

5 papers

physics.flu-dyn2026

Supersonic jet impingement on concave surfaces

Hemanth Chandravamsi, Dhanush Vittal Shenoy, Steven H. Frankel

The aeroacoustic resonance of round supersonic jets impinging on concave surfaces is investigated using compressible large-eddy simulations, vortex-sheet modelling, and Powell's fe…

physics.flu-dyn2026

Dynamic masking for boundary-aware velocity reconstruction in volumetric particle tracking with moving solids

Jibu Tom Jose, Arieh Jacobson, Dhanush Vittal Shenoy +2

Volumetric particle tracking velocimetry (PTV) produces scattered Lagrangian tracks that must be reconstructed on an Eulerian grid before velocity gradients, pressure, or hydrodyna…

physics.flu-dyn2026

Gaussian Field Representations for Turbulent Flow: Compression, Scale Separation, and Physical Fidelity

Dhanush Vittal Shenoy, Steven H. Frankel

Representing turbulent flow fields in a compact yet physically faithful form remains a central challenge in computational fluid dynamics. We propose a continuous parametric represe…

eess.AS2025

Spectral Bottleneck in Sinusoidal Representation Networks: Noise is All You Need

Hemanth Chandravamsi, Dhanush V. Shenoy, Itay Zinn +3

This work identifies and attempts to address a fundamental limitation of implicit neural representations with sinusoidal activation. The fitting error of SIRENs is highly sensitive…

cs.CV2025

Improving Accuracy and Efficiency of Implicit Neural Representations: Making SIREN a WINNER

Hemanth Chandravamsi, Dhanush V. Shenoy, Steven H. Frankel

We identify and address a fundamental limitation of sinusoidal representation networks (SIRENs), a class of implicit neural representations. SIRENs Sitzmann et al. (2020), when not…