Shop : Details
Shop
Details
48,80 €ISBN 978-3-8440-8761-1Paperback186 Seiten63 Abbildungen276 g21 x 14,8 cmEnglischDissertation
September 2022
Stefan Matthias Mertler
Comparative Analysis of Crash Simulation Results using Generative Nonlinear Dimensionality Reduction
Numerical simulations are an integral part of today’s product development. Analysing and comparing multiple simulation results is a time consuming but necessary part. Thus, it is important to develop methods to help with this Comparative Analysis by identifying differences in the results. Here it is crucial to determine how such variations relate to each other.
So-called Dimensionality Reduction Methods (DRMs) have been used for this since several years. Recently, the need for nonlinear reduction approaches was shown. One widely used method called Difference Principal Component Analysis (DPCA), which computes correlation between different parts of simulations, is based on a linear reduction approach. The aim of this dissertation is to extend the DPCA with nonlinear Dimensionality Reduction (DR).
For this, the two steps of the DPCA’s workflow were modified. For the first step of DR, several methods of generative DRMs have been extended. For the second so-called subtraction step, the new generalised concept of Difference Dimensionality Reduction was introduced and demonstrated with two specific implementations.
The new methods were tested on multiple examples: Firstly, on artificial data to test the individual steps in an isolated environment and secondly on simulation results to evaluate them on realistic data. In the case of a nonlinear relation between these data sets, the superiority over linear approaches was demonstrated, while other linear dependencies were confirmed.
With these modifications, the DPCA’s workflow is meaningfully applicable to data sets with nonlinear dependencies, and the evaluation suggests a broad range of possible applications, as nonlinearities can occur in many data sets, for example data from topology optimisation or parameter variation.
So-called Dimensionality Reduction Methods (DRMs) have been used for this since several years. Recently, the need for nonlinear reduction approaches was shown. One widely used method called Difference Principal Component Analysis (DPCA), which computes correlation between different parts of simulations, is based on a linear reduction approach. The aim of this dissertation is to extend the DPCA with nonlinear Dimensionality Reduction (DR).
For this, the two steps of the DPCA’s workflow were modified. For the first step of DR, several methods of generative DRMs have been extended. For the second so-called subtraction step, the new generalised concept of Difference Dimensionality Reduction was introduced and demonstrated with two specific implementations.
The new methods were tested on multiple examples: Firstly, on artificial data to test the individual steps in an isolated environment and secondly on simulation results to evaluate them on realistic data. In the case of a nonlinear relation between these data sets, the superiority over linear approaches was demonstrated, while other linear dependencies were confirmed.
With these modifications, the DPCA’s workflow is meaningfully applicable to data sets with nonlinear dependencies, and the evaluation suggests a broad range of possible applications, as nonlinearities can occur in many data sets, for example data from topology optimisation or parameter variation.
Schlagwörter: Crash Simulation; Dimensionality Reduction; Data Analysis
Verfügbare Online-Dokumente zu diesem Titel
Sie benötigen den Adobe Reader, um diese Dateien ansehen zu können. Hier erhalten Sie eine kleine Hilfe und Informationen, zum Download der PDF-Dateien.
Bitte beachten Sie, dass die Online-Dokumente nicht ausdruckbar und nicht editierbar sind.
Bitte beachten Sie auch weitere Informationen unter: Hilfe und Informationen.
Bitte beachten Sie auch weitere Informationen unter: Hilfe und Informationen.
| Dokument |  | Gesamtdokument | ||
| Dateiart |  | |||
| Kosten |  | 36,60 € | ||
| Aktion |  | Zahlungspflichtig kaufen und download der Datei | ||
| Dokument |  | Inhaltsverzeichnis | ||
| Dateiart | | |||
| Kosten |  | frei | ||
| Aktion |  | Download der Datei | ||
Benutzereinstellungen für registrierte Online-Kunden (Online-Dokumente)
Sie können hier Ihre Adressdaten ändern sowie bereits georderte Dokumente erneut aufrufen.
Benutzer
Nicht angemeldet
Export bibliographischer Daten
Shaker Verlag GmbH
Am Langen Graben 15a
52353 Düren
Am Langen Graben 15a
52353 Düren
Mo. - Do. 8:00 Uhr bis 16:00 Uhr
Fr. 8:00 Uhr bis 15:00 Uhr
Fr. 8:00 Uhr bis 15:00 Uhr
Kontaktieren Sie uns. Wir helfen Ihnen gerne weiter.
