Processing Free Form Objects within a Product Development Process Framework

doi:10.1115/1.860328_ch13

Cited by 5 publications

(1 citation statement)

References 45 publications

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“…The implementation of a design methodology to solve it therefore relies on three underlying main pillars Falcidieno et al (2014). The runner geometry can be defined by a set of design parameters instantiating a parametric model.…”

Section: Introductionmentioning

confidence: 99%

Toward design optimization of a Pelton turbine runner

Vessaz

Andolfatto

Avellan

et al. 2016

Struct Multidisc Optim

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The objective of the present paper is to propose a strategy to optimize the performance of a Pelton runner based on a parametric model of the bucket geometry, massive particle based numerical simulations and advanced optimization strategies to reduce the dimension of the design problem. The parametric model of the Pelton bucket is based on four bicubic Bézier patches and the number of free parameters is reduced to 21. The numerical simulations are performed using the finite volume particle method, which benefits from a conservative, consistent, arbitrary Lagrangian Eulerian formulation. The resulting design problem is of High-dimension with Expensive Black-box (HEB) performance function. In order to tackle the HEB problem, a preliminary exploration is performed using 2'000 sampled runners geometry provided by a Halton sequence.

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Section: Introductionmentioning

confidence: 99%

Toward design optimization of a Pelton turbine runner

Vessaz

Andolfatto

Avellan

et al. 2016

Struct Multidisc Optim

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Sensitivity Analysis for Simulated Annealing-Based Fitting of CAD Models to Point Clouds of Digitized Parts

Shah

Polette

Pernot

et al. 2021

Lecture Notes in Mechanical Engineering

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This paper addresses the way a simulated annealing-based fitting strategy can be enhanced by leveraging a sensitivity analysis able to characterize the impact of the variations in the parameters of a CAD model on the evolution of the deviation between the CAD model itself and the point cloud of the digitized part to be fitted. The principles underpinning the adopted fitting algorithm are briefly recalled. The applied sensitivity analysis is described together with the comparison of the resulting sensitivity evolution curves with the changes in the CAD model parameters imposed by the simulated annealing algorithm. This analysis suggests several possible improvements that are discussed. The overall approach is illustrated on the fitting of single mechanical parts but it can be directly extended to the fitting of parts’ assemblies. It is particularly interesting in the context of the Industry 4.0 to update digital twins of physical products and systems.

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Case-based tuning of a metaheuristic algorithm exploiting sensitivity analysis and design of experiments for reverse engineering applications

Shah

Polette

Pernot

et al. 2022

Engineering with Computers

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Due to its capacity to evolve in a large solution space, the Simulated Annealing (SA) algorithm has shown very promising results for the Reverse Engineering of editable CAD geometries including parametric 2D sketches, 3D CAD parts and assemblies. However, parameter setting is a key factor for its performance, but it is also awkward work. This paper addresses the way a SA-based Reverse Engineering technique can be enhanced by identifying its optimal default setting parameters for the fitting of CAD geometries to point clouds of digitized parts. The method integrates a sensitivity analysis to characterize the impact of the variations in the parameters of a CAD model on the evolution of the deviation between the CAD model itself and the point cloud to be fitted. The principles underpinning the adopted fitting algorithm are briefly recalled. A framework that uses design of experiments (DOEs) is introduced to identify and save in a database the best setting parameter values for given CAD models. This database is then exploited when considering the fitting of a new CAD model. Using similarity assessment, it is then possible to reuse the best setting parameter values of the most similar CAD model found in the database. The applied sensitivity analysis is described together with the comparison of the resulting sensitivity evolution curves with the changes in the CAD model parameters imposed by the SA algorithm. Possible improvements suggested by the analysis are implemented to enhance the efficiency of SA-based fitting. The overall approach is illustrated on the fitting of single mechanical parts but it can be directly extended to the fitting of parts' assemblies. It is particularly interesting in the context of the Industry 4.0 to update and maintain the coherence of the digital twins with respect to the evolution of the associated physical products and systems.

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Processing Free Form Objects within a Product Development Process Framework

Abstract: is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible.This is an author-deposited version published in: http://sam.ensam.eu Handle

Cited by 5 publications

References 45 publications

Toward design optimization of a Pelton turbine runner

Toward design optimization of a Pelton turbine runner

Sensitivity Analysis for Simulated Annealing-Based Fitting of CAD Models to Point Clouds of Digitized Parts

Case-based tuning of a metaheuristic algorithm exploiting sensitivity analysis and design of experiments for reverse engineering applications

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