Static and dynamic global stiffness analysis for automotive pre-design

Tesi en modalitat de cotutela: Universitat Politècnica de Catalunya i Swansea UniversityIn order to be worldwide competitive, the automotive industry is constantly challenged to produce higher quality vehicles in the shortest time possible and with the minimum costs of production. Most of the problems with new products derive from poor quality design processes, which often leads to undesired issues in a stage where changes are extremely expensive. During the preliminary design phase, designers have to deal with complex parametric problems where material and geometric characteristics of the car components are unknown. Any change in these parameters might significantly affect the global behaviour of the car. A target which is very sensitive to small variations of the parameters is the noise and vibration response of the vehicle (NVH study), which strictly depends on its global static and dynamic stiffness. In order to find the optimal solution, a lot of configurations exploring all the possible parametric combinations need to be tested. The current state of the art in the automotive design context is still based on standard numerical simulations, which are computationally very expensive when applied to this kind of multidimensional problems. As a consequence, a limited number of configurations is usually analysed, leading to suboptimal products. An alternative is represented by reduced order method (ROM) techniques, which are based on the idea that the essential behaviour of complex systems can be accurately described by simplified low-order models. This thesis proposes a novel extension of the proper generalized decomposition (PGD) method to optimize the design process of a car structure with respect to its global static and dynamic stiffness properties. In particular, the PGD method is coupled with the inertia relief (IR) technique and the inverse power method (IPM) to solve, respectively, the parametric static and dynamic stiffness analysis of an unconstrained car structure and extract its noise and vibrations properties. A main advantage is that, unlike many other ROM methods, the proposed approach does not require any pre-processing phase to collect prior knowledge of the solution. Moreover, the PGD solution is computed with only one offline computation and presents an explicit dependency on the introduced design variables. This allows to compute the solutions at a negligible computational cost and therefore opens the door to fast optimisation studies and real-time visualisations of the results in a pre-defined range of parameters. A novel algebraic approach is also proposed which allows to involve both material and complex geometric parameters, such that shape optimisation studies can be performed. In addition, the method is developed in a nonintrusive format, such that an interaction with commercial software is possible, which makes it particularly interesting for industrial applications. Finally, in order to support the designers in the decision-making process, a graphical interface app is developed which allows to visualise in real-time how changes in the design variables affect pre-defined quantities of interest.Para ser competitiva en todo el mundo, la industria del automóvil se enfrenta constantemente al reto de producir vehículos de mayor calidad en el menor tiempo posible y con los mínimos costes de producción. La mayor parte de los problemas de los nuevos productos derivan de la mala calidad de los procesos de diseño, que a menudo conduce a problemas no deseados en una fase en la que los cambios son extremadamente caros. Durante la fase de diseño preliminar, los diseñadores tienen que enfrentarse a complejos problemas paramétricos en los que se desconocen las características materiales y geométricas de los componentes del coche. Cualquier cambio en estos parámetros puede afectar significativamente al comportamiento global del coche. Un objetivo muy sensible a pequeñas variaciones de los parámetros es la respuesta al ruido y las vibraciones del vehículo (estudio NVH), que depende estrictamente de su rigidez global estática y dinámica. Para encontrar la solución óptima, es necesario probar muchas configuraciones que exploren todas las combinaciones paramétricas posibles. El estado actual de la técnica en el contexto del diseño de automóviles sigue basándose en simulaciones numéricas estándar, que son muy costosas desde el punto de vista de cálculo cuando se aplican a este tipo de problemas multidimensionales. Como consecuencia, se suele analizar un número limitado de configuraciones, lo que conduce a productos subóptimos. Una alternativa la representan las técnicas de reduced order modelling (ROM), que se basan en la idea de que el comportamiento esencial de los sistemas complejos puede describirse con precisión mediante modelos simplificados. Esta tesis propone una nueva extensión del método de proper generalised decomposition (PGD) para optimizar el proceso de diseño de la estructura de un automóvil con respecto a sus propiedades globales de rigidez estática y dinámica. En particular, el método PGD se acopla con la técnica de inertia relief (IR) y el inverse power method (IPM) para resolver, respectivamente, el análisis paramétrico de la rigidez estática y dinámica de una estructura de coche sin restricciones y extraer sus propiedades de ruido y vibraciones. Una de las principales ventajas es que, a diferencia de muchos otros métodos ROM, el enfoque propuesto no requiere ninguna fase de preprocesamiento para recoger el conocimiento previo de la solución. Además, la solución del PGD se calcula con un solo cálculo fuera de línea y presenta una dependencia explícita de las variables de diseño introducidas. Esto permite calcular las soluciones con un coste computacional insignificante y, por tanto, abre la puerta a estudios de optimización rápidos y a la visualización en tiempo real de los resultados en un rango predefinido de parámetros. También se propone un nuevo enfoque algebraico que permite involucrar tanto el material como los parámetros geométricos complejos, de manera que se pueden realizar estudios de optimización de la forma. Además, el método se desarrolla en un formato no intrusivo, de forma que es posible la interacción con software comercial, lo que lo hace especialmente interesante para aplicaciones industriales. Por último, para apoyar a los diseñadores en el proceso de toma de decisiones, se desarrolla una aplicación de interfaz gráfica que permite visualizar en tiempo real cómo los cambios en las variables de diseño afectan a las cantidades de interés predefinidas.Postprint (published version

Static and dynamic global stiffness analysis for automotive pre-design

In order to be worldwide competitive, the automotive industry is constantly challenged to produce higher quality vehicles in the shortest time possible and with the minimum costs of production. Most of the problems with new products derive from poor quality design processes, which often leads to undesired issues in a stage where changes are extremely expensive. During the preliminary design phase, designers have to deal with complex parametric problems where material and geometric characteristics of the car components are unknown. Any change in these parameters might significantly affect the global behaviour of the car. A target which is very sensitive to small variations of the parameters is the noise and vibration response of the vehicle (NVH study), which strictly depends on its global static and dynamic stiffness. In order to find the optimal solution, a lot of configurations exploring all the possible parametric combinations need to be tested. The current state of the art in the automotive design context is still based on standard numerical simulations, which are computationally very expensive when applied to this kind of multidimensional problems. As a consequence, a limited number of configurations is usually analysed, leading to suboptimal products. An alternative is represented by reduced order method (ROM) techniques, which are based on the idea that the essential behaviour of complex systems can be accurately described by simplified low-order models.This thesis proposes a novel extension of the proper generalized decomposi-tion (PGD) method to optimize the design process of a car structure with respect to its global static and dynamic stiffness properties. In particular, the PGD method is coupled with the inertia relief (IR) technique and the inverse power method (IPM) to solve, respectively, the parametric static and dynamic stiffness analysis of an unconstrained car structure and extract its noise and vibrations properties. A main advantage is that, unlike many other ROM methods, the proposed approach does not require any pre-processing phase to collect prior knowledge of the solution. Moreover, the PGD solution is computed with only one offline computation and presents an explicit dependency on the introduced design variables. This allows to compute the solutions at a negligible computational cost and therefore opens the door to fast optimisation studies and real-time visualisations of the results in a pre-defined range of parameters. A novel algebraic approach is also proposed which allows to involve both material and com-plex geometric parameters, such that shape optimisation studies can be performed. In addition, the method is developed in a nonintrusive format, such that an interaction with commercial software is possible, which makes it particularly interesting for industrial applications. Finally, in order to support the designers in the decision-making process, a graphical interface app is developed which allows to visualise in real-time how changes in the design variables affect pre-defined quantities of interest

Nonintrusive parametric solutions in structural dynamics

© 2022 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/A nonintrusive reduced order method able to solve a parametric modal analysis is proposed in this work. The main objective is being able to efficiently identify how a variation of user-defined parameters affects the dynamic response of the structure in terms of fundamental natural frequencies and corresponding mode shapes. A parametric version of the inverse power method (IPM) is presented by using the proper generalised decomposition (PGD) rationale. The proposed approach utilises the socalled encapsulated PGD toolbox and includes a new algorithm for computing the square root of a parametric object. With only one offline computation, the proposed PGD-IPM approach provides an analytical parametric expression of the smallest (in magnitude) eigenvalue (or natural frequency) and corresponding eigenvector (mode shape), which contains all the possible solutions for every combination of the parameters within pre-defined ranges. A Lagrange multiplier deflation technique is introduced in order to compute subsequent eigenpairs, which is also valid to overcome the stiffness matrix singularity in the case of a free-free structure. The proposed approach is nonintrusive and it is therefore possible to be integrated with commercial finite element (FE) packages. Two numerical examples are shown to underline the properties of the technique. The first example includes one material and one geometric parameter. The second example shows a more realistic industrial example, where the nonintrusivity of the approach is demonstrated by employing a commercial FE package for assembling the FE matrices. Finally, a multi-objective optimisation study is performed proving that the developed method could significantly assist the decision-making during the preliminary phase of a new design process.This project is part of the Marie Skłodowska-Curie ITN-EJD ProTechTion funded by the European Union Horizon 2020 research and innovation program with Grant Number 764636. The work of Fabiola Cavaliere, Sergio Zlotnik and Pedro Díez is partially supported by the MCIN/AEI/10.13039/501100011033, Spain (Grant Number: PID2020-113463RB-C32, PID2020-113463RB-C33 and CEX2018-000797-S). Ruben Sevilla also acknowledges the support of the Engineering and Physical Sciences Research Council (Grant Number: EP/P033997/1).Peer ReviewedPostprint (author's final draft

Nonintrusive parametric NVH study of a vehicle body structure

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Mechanics based design of structures and machines on 27/06/22, available online at: http://www.tandfonline.com/10.1080/15397734.2022.2098140A reduced order model technique is presented to perform the parametric Noise, Vibration and Harshness (NVH) study of a vehicle body-in-white (BIW) structure characterized by material and shape design variables. The ultimate goal is to develop a methodology which allows to efficiently explore the variation in the design space of the BIW static and dynamic global stiffnesses, such that the NVH performance can be evaluated already in the preliminary phase of the development process. The proposed technique is based on the proper generalized decomposition (PGD) method. The obtained PGD solution presents an explicit dependency on the introduced design variables, which allows to obtain solutions in 0.1 milliseconds and therefore opens the door to fast optimization studies and real-time visualizations of the results in a pre-defined range of parameters. The method is nonintrusive, such that an interaction with commercial software is possible. A parametrized finite element (FE) model of the BIW is built by means of the ANSA CAE preprocessor software, which allows to account for material and geometric parameters. A comparison between the parametric NVH solutions and the full-order FE simulations is performed using the MSC-Nastran software, to validate the accuracy of the proposed method. In addition, an optimization study is presented to find the optimal materials and shape properties with respect to the NVH performance. Finally, in order to support the designers in the decision-making process, a graphical interface app is developed which allows to visualize in real-time how changes in the design variables affect pre-defined quantities of interest.This project is part of the Marie Skłodowska-Curie ITN-EJD ProTechTion funded by the European Union Horizon 2020 research and innovation program with Grant Number 764636. The work of Fabiola Cavaliere, Sergio Zlotnik and Pedro D ıez is partially supported by the MCIN/AEI/10.13039/501100011033, Spain (Grant Number: PID2020-113463RB-C32, PID2020-113463RB-C33 and CEX2018-000797-S). Ruben Sevilla also acknowledges the support of the Engineering and Physical Sciences Research Council (Grant Number: EP/T009071/1).Peer ReviewedPostprint (published version

Nonintrusive Proper Generalized Decomposition Method for the Design Optimization of a Car

A model order reduction technique is proposed in order to optimise the design process of a car body structure with respect to the noise and vibration characteristics of the vehicle. The final goal is to support designers in the decision-making process, such that they can evaluate in real-time the impact of certain parameters on the global response of the structure

The Other Side of the Coin: May Androgens Have a Role in Breast Cancer Risk?

Breast cancer prevention is a major challenge worldwide. During the last few years, efforts have been made to identify molecular breast tissue factors that could be linked to an increased risk of developing the disease in healthy women. In this concern, steroid hormones and their receptors are key players since they are deeply involved in the growth, development and lifetime changes of the mammary gland and play a crucial role in breast cancer development and progression. In particular, androgens, by binding their own receptor, seem to exert a dichotomous effect, as they reduce cell proliferation in estrogen receptor α positive (ERα+) breast cancers while promoting tumour growth in the ERα negative ones. Despite this intricate role in cancer, very little is known about the impact of androgen receptor (AR)-mediated signalling on normal breast tissue and its correlation to breast cancer risk factors. Through an accurate collection of experimental and epidemiological studies, this review aims to elucidate whether androgens might influence the susceptibility for breast cancer. Moreover, the possibility to exploit the AR as a useful marker to predict the disease will be also evaluated