Dataset for the study of frequency-domain model order reduction techniques in vibroacoustic applications

The dataset is associated with the university dissertation titled "Surrogate modeling of high-dimensional vibroacoustic problems using parametric model order reduction" by Harikrishnan K. Sreekumar. Expensive direct numerical simulations are often used for vibroacoustic problems to yield insights about the model characteristics. These bottlenecks can be circumvented by generating a reduced order model that yields accurate system responses in real time. The current dataset includes various models that are used to investigate efficient reduction to approximate the frequency-domain response of the systems. Considered examples include (1) a simple plate model, (2) a generic aircraft fuselage model, and (3) a complex aircraft fuselage model for cabin noise assessments. The identified challenges of handling large-scale problems, frequency-dependent nature of the system entities and approaches to perform reduction for broadband applications are at focus. This current dataset publication contains essential artifacts (computational notebook, model data and primary results) that enable reproducibility of the outcome presented in the dissertation

Dataset for the study of parametric-domain model order reduction techniques in vibroacoustic applications

The dataset is associated with the university dissertation titled "Surrogate modeling of high-dimensional vibroacoustic problems using parametric model order reduction" by Harikrishnan K. Sreekumar. Parametric model order reduction techniques are used to yield reduced order models (ROMs) that can capture the desired parametric response of a system and deliver system responses for any desired parameter setting in real time. Such a parametric surrogate is highly beneficial for multi-query problems like uncertainty quantification, optimization and sensitivity analysis. However, the training process to yield a parametric ROM becomes cumbersome with increasing number of parameters under consideration leading to the infamous curse of dimensionality. The dissertation presents approaches to deal with the high-dimensional parameter space by deploying dimensionality reduction using active subspaces have shown to alleviate the training effort drastically. In addition, clustering-based techniques assisted by neural networks are used to yield converging ROMs for models exhibiting high dynamics. Furthermore, the efficiency of the method of adaptive sparse grids applied to representative vibroacoustic examples is presented. The current dataset publication contains essential artifacts (computational notebook, model data and primary results) that enable reproducibility of the outcome presented in the dissertation

Dataset for the study of various error measures steering adaptive model order reduction algorithms in vibroacoustic applications

The dataset is associated with the university dissertation titled "Surrogate modeling of high-dimensional vibroacoustic problems using parametric model order reduction" by Harikrishnan K. Sreekumar. To evaluate the accuracy of a reduced order model in the context of model order reduction in the frequency domain, a range of error measures are available. The error measures are extensively used in adaptive algorithms to build reduced order models of optimal dimensions with the least effort. The author performs a detailed study on some of the popular error measures using simple plate examples that are discussed in the thesis. This current dataset publication contains essential artifacts (computational notebook, model data and primary results) that enable reproducibility of the outcome presented in the dissertation

elPaSo AcMoRe - Python module for faster training and evaluation of vibroacoustic systems with model order reduction

Please contact the author Harikrishnan Sreekumar ([email protected]) to make a request for the research software. The dataset contains the software publication artifacts for the software "elPaSo AcMoRe - Python module for faster training and evaluation of vibroacoustic systems with model order reduction" versioned 24.03.4. AcMoRe provides a wide range of functionalities to generate surrogates in frequency and parameter domains for vibroacoustic problems. As a result, one can benefit from faster computations by replacing expensive direct solvers with the yielded reduced-order model (ROM). In addition, to the compute capabilities, the tool offers various visualization routines that enable better insights into the ROM modeling process. The executions are performed in tandem with the elPaSo Research module for the offline ROM creation phase

SURESOFT – CI and Containerization

Continuous integration (CI) and containerization play a key role towards software sustainability and reproducibility. Especially in the field of research, incorporating such practices deliver many advantages thereby increasing the quality of software development. In this workshop, we teach you to create CI pipeline for a software project and also wrap your software dependencies in a container image using Docker

elPaSo Research - Elementary parallel solver research module for high performance vibroacoustic simulations

Please contact the author Harikrishnan Sreekumar ([email protected]) to make a request for the research software. The dataset contains the software publication artifacts for the software "elPaSo Research - Elementary parallel solver research module for high performance vibroacoustic simulations" versioned 24.03.2. The research code “Elementary Parallel Solver (elPaSo)” is the in-house vibroacoustic simulation tool constantly developed since 1996 at TU Braunschweig, presently extended and maintained by the Institute for Acoustics and Dynamics (InAD), TU Braunschweig, Germany. The tool has been used extensively for research and teaching for many years. The current elPaSo project, written in C++, includes advanced computational methods for performing vibroacoustic simulations extending the functionalities of elPaSo Core module. Model order reduction implementations are also available as a part of this research code

SURESOFT workshop series

Software testing ensures the proper functioning of a constantly evolving software and helps to quickly identify faults in a software code. This workshop introduces the first steps toward writing various types of software tests for scientific codes along with hands-on sessions

elPaSo Core - Elementary parallel solver core module for high performance vibroacoustic simulations

The dataset contain the software publication artifacts for the software "elPaSo Core - Elementary parallel solver core module for high performance vibroacoustic simulations" versioned 23.01.2. The research code “Elementary Parallel Solver (elPaSo)” is the in-house vibroacoustic simulation tool constantly developed since 1996 at TU Braunschweig, presently extended and maintained by the Institute for Acoustics (InA), TU Braunschweig, Germany. The tool is used extensively for research and teaching for many years. The whole elPaSo project includes the core software written in C++ and other assisting in-house tools written in python. elPaSo offers a wide range of features and facilitates efficient computations in HPC clusters to support parallel computing of large-scale high-fidelity vibroacoustic models. Moreover, the project is built on a flexible and modular framework to support new research features and potential collaborations

elPaSo AUTOMATE - Automated testing framework for validation and verification of a vibroacoustic simulation tool

The dataset contain the software publication artifacts for the software "elPaSo AUTOMATE - Automated testing framework for validation and verification of a vibroacoustic simulation tool" versioned 23.01.1. elPaSo AUTOMATE is an automated testing framework for the vibroacoustic simulation code elPaSo developed by Institute for Acoustics, TU Braunschweig, Germany. This project is aimed at automatically testing and verifying the proper functioning of elPaSo on every commit in a CI framework. AUTOMATE performs specific tests evaluating the code update for different test parameters such as accuracy, performance, etc by executing different acoustic benchmarks. The results from the different tests are then reported in various forms. Depending upon the user input, the AUTOMATE tool compares the results obtained with benchmarked results which can be from an old stable elPaSo version or results from a commercial software like ABAQUS

Large-scale vibroacoustic simulations using parallel direct solvers for high-performance clusters

The future scenario in computational sciences is the availability of abundant computational resources, thereby enabling high-performance computing. Therefore, the finite element modeling of vibroacoustic problems with large number of degrees of freedom can be efficiently realized in high-performance clusters for solving using parallel sparse solvers. The contribution addresses the different capabilities of the in-house numerical tool, elPaSo (Elementary Parallel Solver), to solve large-scale finite element models. Parallelization is performed with the distribution of workload among different computing nodes and their threads with MPI (Message Passing Interface) and OMP (Open Multi-Processing). An investigation is performed on a generic model with fluid-structure interaction, where the complexity of the system matrix represents a wide range of practical vibroacoustic models for solving. The model is subjected to various parallel LU factorization routines of MUMPS and PARDISO using an interface from PETSc (Portable, Extensible Toolkit for Scientific Computation) suite. Finally, the performances are evaluated in terms of solver clock, speedup and the number of floating-point operations performed