Model-based application of the methodical process for modular lightweight design of aircraft cabins

A Sequential Sampling Generation Method for Multi-fidelity Model Based on Voronoi Region and Sample Density

Journal of Mechanical Design ◽

10.1115/1.4051014 ◽

2021 ◽

pp. 1-17

Author(s):

Yin Liu ◽

Kunpeng Li ◽

Shuo Wang ◽

Peng Cui ◽

Xueguan Song ◽

...

Keyword(s):

Surrogate Model ◽

Optimization Problems ◽

Lightweight Design ◽

Sequential Sampling ◽

Pearson Correlation ◽

Voronoi Tessellation ◽

Element Analysis ◽

Voronoi Region ◽

Model Based ◽

Sample Density

Abstract Multi-fidelity surrogate model-based engineering optimization has received much attention because it alleviates the computational burdens of expensive simulations or experiments. However, due to the nonlinearity of practical engineering problems, the initial sample set selected to produce the first set of data will almost inevitably miss certain features of the landscape, and thus the construction of a useful surrogate often requires further, judicious infilling of some new samples. Sequential sampling strategies used to select new infilling sample during each iteration can gradually extend the dataset and improve the accuracy of the initial model with an acceptable cost. In this paper, a sequential sampling generation method based on the Voronoi region and the sample density, terms as SSGM-VRDS, is proposed. First, with a Monte Carlo-based approximation of a Voronoi tessellation for region division, Pearson correlation coefficients and cross validation (CV) are employed to determine the candidate Voronoi region for infilling a new sample. Then, a relative sample density is defined to identify the position of the new infilling point at which the sample are the sparsest within the selected Voronoi region. A correction of this density is carried out concurrently through an expansion coefficient. The proposed method is applied to three numerical numerical functions and a lightweight design problem via finite element analysis (FEA). Results suggest that the SSGM-VRDS strategy has outstanding effectiveness and efficiency in selecting a new sample for improving the accuracy of a surrogate model, as well as practicality for solving practical optimization problems.

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Lightweight Design of an Outer Tie Rod Using Meta-Model Based Optimization Technique

Journal of the Korea Academia-Industrial cooperation Society ◽

10.5762/kais.2015.16.11.7754 ◽

2015 ◽

Vol 16 (11) ◽

pp. 7754-7760

Author(s):

Young-Jun Kim ◽

Soon-Hyeong Park ◽

Kwon-Hee Lee ◽

Young-Chul Park

Keyword(s):

Lightweight Design ◽

Optimization Technique ◽

Meta Model ◽

Model Based

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INCONSISTENCY MANAGEMENT FOR PRODUCT FAMILIES WITH MANY VARIANTS THROUGH A MODEL-BASED APPROACH IN MODULAR LIGHTWEIGHT DESIGN

Proceedings of the Design Society: DESIGN Conference ◽

10.1017/dsd.2020.309 ◽

2020 ◽

Vol 1 ◽

pp. 917-926

Author(s):

M. Hanna ◽

J. Schwenke ◽

D. Krause

Keyword(s):

Product Development ◽

Data Model ◽

Process Model ◽

Lightweight Design ◽

Product Families ◽

Related Data ◽

Model Based ◽

Inconsistency Management ◽

Numerous Data ◽

Product And Process

AbstractIn methodical product development, numerous data are used and linked with each other, especially variant-related data. This paper presents a model-based solution for avoiding inconsistencies in the development of product families with many variants and extends it to modular lightweight design. In addition, the inconsistencies in methodical product development were classified and solution approaches were shown. Thus, inconsistencies can be avoided with the presented elaborated data model for an integrated product and process model based on the presented procedure.

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

Microscopy and Microanalysis ◽

10.1017/s1431927600028968 ◽

2001 ◽

Vol 7 (S2) ◽

pp. 578-579

Author(s):

David W. Knowles ◽

Sophie A. Lelièvre ◽

Carlos Ortiz de Solόrzano ◽

Stephen J. Lockett ◽

Mina J. Bissell ◽

...

Keyword(s):

Image Analysis ◽

Mammary Epithelial Cells ◽

Nuclear Organization ◽

Critical Role ◽

Quantitative Model ◽

Mammary Epithelial ◽

Cell Phenotype ◽

Proliferating Cells ◽

Mitotic Apparatus ◽

Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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