scholarly journals Surrogate-Based Optimization Using an Open-Source Framework: The Bulbous Bow Shape Optimization Case

2018 ◽  
Vol 23 (4) ◽  
pp. 60 ◽  
Author(s):  
Joel Guerrero ◽  
Alberto Cominetti ◽  
Jan Pralits ◽  
Diego Villa
Keyword(s):  
Shape Optimization ◽  
Open Source ◽  
Fault Tolerant ◽  
Work Flow ◽  
Hydrodynamic Resistance ◽  
Practical Case ◽  
Optimization Strategy ◽  
Surrogate Based Optimization ◽  
Bulbous Bow ◽  
Solid Modeler

Shape optimization is a very time-consuming and expensive task, especially if experimental tests need to be performed. To overcome the challenges of geometry optimization, the industry is increasingly relying on numerical simulations. These kinds of problems typically involve the interaction of three main applications: a solid modeler, a multi-physics solver, and an optimizer. In this manuscript, we present a shape optimization work-flow entirely based on open-source tools; it is fault tolerant and software agnostic, allows for asynchronous simulations, and has a high degree of automation. To demonstrate the usability and flexibility of the proposed methodology, we tested it in a practical case related to the naval industry, where we aimed at optimizing the shape of a bulbous bow in order to minimize the hydrodynamic resistance. As design variables, we considered the protrusion and immersion of the bulbous bow, and we used surrogate-based optimization. From the results presented, a non-negligible resistance reduction is obtainable using the proposed work-flow and optimization strategy.

Managing Large Volumes of Interlinked Text and Knowledge With the KnowledgeStore

2018 ◽  
pp. 32-61
Author(s):  
Francesco Corcoglioniti ◽  
Marco Rospocher ◽  
Roldano Cattoni ◽  
Bernardo Magnini ◽  
Luciano Serafini
Keyword(s):  
Semantic Web ◽  
Open Source ◽  
Fault Tolerant ◽  
Storage System ◽  
Open Data ◽  
Unstructured Data ◽  
Data Sources ◽  
Concept Design ◽  
Design Function ◽  
Eu Project

This chapter describes the KnowledgeStore, a scalable, fault-tolerant, and Semantic Web grounded open-source storage system to jointly store, manage, retrieve, and query interlinked structured and unstructured data, especially designed to manage all the data involved in Knowledge Extraction applications. The chapter presents the concept, design, function and implementation of the KnowledgeStore, and reports on its concrete usage in four application scenarios within the NewsReader EU project, where it has been successfully used to store and support the querying of millions of news articles interlinked with billions of RDF triples, both extracted from text and imported from Linked Open Data sources.

scholarly journals Open Source Fault-tolerant Grid Frequency Measurement for Solar Inverters

2021 ◽  
Author(s):  
Bailu Xiao ◽  
Fuhua Li ◽  
Yilu Liu ◽  
Lingwei Zhan
Keyword(s):  
Open Source ◽  
Fault Tolerant ◽  
Frequency Measurement

scholarly journals Discrete adjoint aerodynamic shape optimization using symbolic analysis with OpenFEMflow

2021 ◽  
Author(s):  
Ali Elham ◽  
Michel J. L. van Tooren
Keyword(s):  
Shape Optimization ◽  
Open Source ◽  
Symbolic Analysis ◽  
State Variables ◽  
Aerodynamic Shape Optimization ◽  
Computationally Efficient ◽  
Exact Integration ◽  
Aerodynamic Shape ◽  
Discrete Adjoint ◽  
Gradient Based

AbstractThe combination of gradient-based optimization with the adjoint method for sensitivity analysis is a very powerful and popular approach for aerodynamic shape optimization. However, differentiating CFD codes is a time consuming and sometimes a challenging task. Although there are a few open-source adjoint CFD codes available, due to the complexity of the code, they might not be very suitable to be used for educational purposes. An adjoint CFD code is developed to support students for learning adjoint aerodynamic shape optimization as well as developing differentiated CFD codes. To achieve this goal, we used symbolic analysis to develop a discrete adjoint CFD code. The least-squares finite element method is used to solve the compressible Euler equations around airfoils in the transonic regime. The symbolic analysis method is used for exact integration to generate the element stiffness and force matrices. The symbolic analysis is also used to compute the exact derivatives of the residuals with respect to both design variables (e.g., the airfoil geometry) and the state variables (e.g., the flow velocity). Besides, the symbolic analysis allows us to compute the exact Jacobian of the governing equations in a computationally efficient way, which is used for Newton iteration. The code includes a build-in gradient-based optimization algorithm and is released as open-source to be available freely for educational purposes.

scholarly journals Certified Descent Algorithm for shape optimization driven by fully-computable a posteriori error estimators

2017 ◽  
Vol 23 (3) ◽  
pp. 977-1001 ◽  
Author(s):  
Matteo Giacomini ◽  
Olivier Pantz ◽  
Karim Trabelsi
Keyword(s):  
Shape Optimization ◽  
Finite Element Approximation ◽  
Error Estimator ◽  
Element Approximation ◽  
A Posteriori ◽  
Optimization Strategy ◽  
Energy Principle ◽  
Impedance Tomography ◽  
Descent Algorithm ◽  
Shape Gradient

In this paper we introduce a novel certified shape optimization strategy – named Certified Descent Algorithm (CDA) – to account for the numerical error introduced by the Finite Element approximation of the shape gradient. We present a goal-oriented procedure to derive a certified upper bound of the error in the shape gradient and we construct a fully-computable, constant-free a posteriori error estimator inspired by the complementary energy principle. The resulting CDA is able to identify a genuine descent direction at each iteration and features a reliable stopping criterion. After validating the error estimator, some numerical simulations of the resulting certified shape optimization strategy are presented for the well-known inverse identification problem of Electrical Impedance Tomography.

scholarly journals An Efficient Surrogate-Based Optimization Method for BWBUG Based on Multifidelity Model and Geometric Constraint Gradients

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Daiyu Zhang ◽  
Bei Zhang ◽  
Zhidong Wang ◽  
Xinyao Zhu
Keyword(s):  
Shape Optimization ◽  
Optimization Methods ◽  
Optimization Method ◽  
Geometric Constraints ◽  
Geometric Constraint ◽  
High Fidelity ◽  
Surrogate Based Optimization ◽  
Parameterized Model ◽  
Effectiveness And Efficiency ◽  
Optimization Efficiency

Performing shape optimization of blended-wing-body underwater glider (BWBUG) can significantly improve its gliding performance. However, high-fidelity CFD analysis and geometric constraint calculation in traditional surrogate-based optimization methods are expensive. An efficient surrogate-based optimization method based on the multifidelity model and geometric constraint gradient information is proposed. By establishing a shape parameterized model, deriving analytical expression of geometric constraint gradient, constructing multifidelity surrogate model, the calculation times of high-fidelity CFD model and geometric constraints are reduced during the shape optimization process of BWBUG, which greatly improve the optimization efficiency. Finally, the effectiveness and efficiency of the proposed method are verified by performing the shape optimization of a BWBUG and comparing with traditional surrogate-based optimization methods.

Bulbous Bow Retrofit of a Containership Using an Open Source Computational Fluid Dynamics (CFD) Toolbox

2014 ◽  
Author(s):  
Grzegorz Filip ◽  
Dae-Hyun Kim ◽  
Sunil Sahu ◽  
Jan de Kat ◽  
Kevin Maki
Keyword(s):  
Open Source ◽  
Design Space ◽  
Exploration And Exploitation ◽  
Cfd Simulations ◽  
Slow Steaming ◽  
Parameterized Design ◽  
Computational Fluid Dynamics Cfd ◽  
Bulbous Bow ◽  
Alternative Designs ◽  
Propeller Performance

This paper describes a numerical bulbous bow retrofit analysis for a modern container ship operating under a slow-steaming profile. The retrofit analysis is used as an example of a design process based on high-fidelity CFD simulations and surrogate modelling. The bulbous bow design candidates are generated through a parametric modification of the original bow geometry. The alternative designs are evaluated using the open-source CFD toolbox OpenFOAM and the computed effective power predictions are used to rank each design across the entire operating profile. Additionally, the influence of the alternative bulb designs on the wave-making resistance and the propeller performance is examined in detail. Surrogate models are then used to explore the parameterized design space and to establish a sequence of design exploration and exploitation cycles in the retrofit analysis with the ultimate goal of generating an improved bow shape.

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