Engineering topics

Appukuttan, Sreejith

Publications and source records attributed to Appukuttan, Sreejith.

3 records

DOE OSTI2024

Discrete-Element and Material-Point Method (DEM and MPM) Based Solvers for Sustainable Technologies

We present the use of discrete element method (DEM) and material point method (MPM) in three relevant green technology applications that include biomass feedstock handling, lithium-ion battery manufacturing, and high-pressure reverse osmosis. Our open-source DEM and MPM solvers are developed using performance portable grid and particle management library, AMReX, thus enabling superior performance on NVIDIA and AMD GPUs with > 100 million particles. Our DEM solver resolves the motion of individual particles in a granular system and includes a bonded sphere method for modeling non-spherical particles along with Hertzian and liquid bridge-based contact models. We simulate highly variable biomass feedstock flows in large-scale hoppers for biofuel production and electrode calendering in battery manufacturing using DEM. Our simulations predict flow blockage in large scale biomass hoppers and electrode microstructure variations, thus providing valuable information for biofuel and battery manufacturers, respectively. The second half of the talk will be on MPM and its application towards pore resolved simulations of reverse osmosis membranes under compressive loads. We present a validation study of our MPM simulations with membrane microscopy imaging thus providing useful insights on membrane stability under high pressure conditions. We also present a spectral stability analysis of using linear hat, quadratic and cubic spline basis in MPM indicating regions of numerical stability.

BIOMASS FUELS,MATHEMATICS AND COMPUTING↗

DOE OSTI2024

The Pele Simulation Suite for Reacting Flows at Exascale

In this work, we present the Pele suite of software tools for compressible and incompressible reacting flows. The Pele suite leverages several different libraries, notably AMReX and SUNDIALS, to achieve performance portability on heterogeneous computing architectures across the supercomputing landscape. The Pele suite is comprised of PeleC, a compressible reacting flow block-structured adaptive mesh refinement solver, PeleLMeX, a low-Mach number reacting flow block-structured adaptive mesh refinement solver, Pele-Physics, a library for transport, thermodynamics, finite rate chemistry, soot, spray and radiation physics. The objective of this paper is (i) to present the code development efforts necessary to achieve highly effective and scalable applications for exascale machines and (ii) to detail the performance results of the Combustion-Pele project applications on Oak Ridge National Laboratory's Frontier. We show good weak and strong scaling results for both PeleC and PeleLMeX up to more than 50 billion cells on more than 4096 Frontier graphics processing unit nodes. We also present a capability demonstration simulation of a dual-fuel pulse compression ignition engine (six adaptive mesh refinement levels, and 60 billion cells or 2.1 trillion degrees of freedom) on Frontier, to date one of the largest simulations performed on the first exascale-class supercomputer.

adaptive mesh refinement↗

DOE OSTI2024

Adaptive Mesh Refinement Simulations for Turbulent Reacting Flow

With the increased availability of exascale computing hardware, detailed simulations of realistic devices can be performed at practically relevant time and length scales. Insights into the multiscale driving mechanisms in compressible reacting flow systems with complex geometry, such as combustors, can be used for design optimization and technology improvements. However, to effectively perform these simulations, advanced numerical algorithms must be used to maintain solution accuracy without incurring undue computational costs. PeleC, part of the Pele suite of codes, leverages block-structured adaptive mesh refinement (AMR) through the AMReX library to capture fine-scale flow features in compressible reacting flows. In this talk, we discuss recent improvements to the numerical algorithms, particularly in regard to describing flows at complex boundary structures, and PeleC's performance on exascale computing hardware. We will demonstrate that PeleC is well-suited for modern, extreme-scale, heterogenous compute platforms.

combustion↗