See what's possible with the best algorithms today
Jan 16, 2024 (Available on-demand)
Dr. Abhishek Deshmukh
In this webinar, you’ll learn how large acoustics simulations can be run in the cloud to achieve massive, up to 100x speed-ups in runtime compared to existing desktop-based solutions.
This webinar is for every acoustics professional wanting to see first-hand the transformative effects cloud computing can provide in large-scale acoustics simulations with the unique opportunity of real-time Q&A with Dr. Deshmukh.
Dr. Abhishek Deshmukh, the Team Lead of our Application Engineering team, will present a live demonstration consisting of three simulations of a 3D loudspeaker in a room.
First with Perfectly Matched Layers (PMLs) and 7.8 million unknowns
Second, with Absorbing Boundary Conditions (ABCs) and 6.9 million unknowns
Finally, with ABCs and 105 million unknowns
About the speaker
Dr. Abhishek Deshmukh
Team Lead - Application Engineering
Abhishek has more than nine years of experience in computational fluid dynamics (CFD) research and software development, especially for applications in high-speed compressible flows, turbulence, multiphase flows, and combustion.
For the simulations, we’ll cover geometric modeling, material properties; applying physics, couplings, and boundary conditions; meshing and simulation; and visualization and analysis of the results.
In addition, we’ll show how you can effortlessly set up parameter sweeps in Quanscient Allsolve to rapidly generate data for further optimization.
While waiting for the simulation to run, we’ll cover previous use cases as well as explore other benefits cloud computing can provide.
In summary:
See directly the possibilities cloud computing can enable in large acoustics simulations through a step-by-step walkthrough of a 100M unknowns acoustics simulation solved live in less than 10 minutes
Get the webinar executive summary
In addition to the recording, you can download the Executive Summary PDF, offering a detailed overview of the topics covered in the webinar.
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