scholarly journals Globalized parametric optimization of microwave components by means of response features and inverse metamodels

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anna Pietrenko-Dabrowska ◽  
Slawomir Koziel
Keyword(s):  
Computational Cost ◽  
Global Search ◽  
Optimization Process ◽  
Inverse Regression ◽  
Local Algorithms ◽  
Simulation Tools ◽  
Computational Overhead ◽  
Microwave Components ◽  
Feature Technology ◽  
Cost Issue

AbstractSimulation-based optimization of geometry parameters is an inherent and important stage of microwave design process. To ensure reliability, the optimization process is normally carried out using full-wave electromagnetic (EM) simulation tools, which entails significant computational overhead. This becomes a serious bottleneck especially if global search is required (e.g., design of miniaturized structures, dimension scaling over broad ranges of operating frequencies, multi-modal problems, etc.). In pursuit of mitigating the high-cost issue, this paper proposes a novel algorithmic approach to rapid EM-driven global optimization of microwave components. Our methodology incorporates a response feature technology and inverse regression metamodels to enable fast identification of the promising parameter space regions, as well as to yield a good quality initial design, which only needs to be tuned using local routines. The presented technique is illustrated using three microstrip circuits optimized under challenging scenarios, and demonstrated to exhibit global search capability while maintaining low computational cost of the optimization process of only about one hundred of EM simulations of the structure at hand on the average. The performance is shown to be superior in terms of efficacy over both local algorithms and nature-inspired global methods.

Efficient Gradient-Based Algorithms for the Construction of Pareto Fronts

2011 ◽  
Author(s):  
Sriram Shankaran ◽  
Brian Barr
Keyword(s):  
Pareto Front ◽  
Computational Cost ◽  
High Fidelity ◽  
Simulation Tools ◽  
Pareto Points ◽  
Uniform Spacing ◽  
Design Variables ◽  
Gradient Based ◽  
Pareto Fronts ◽  
Sampling Approach

The objective of this study is to develop and assess a gradient-based algorithm that efficiently traverses the Pareto front for multi-objective problems. We use high-fidelity, computationally intensive simulation tools (for eg: Computational Fluid Dynamics (CFD) and Finite Element (FE) structural analysis) for function and gradient evaluations. The use of evolutionary algorithms with these high-fidelity simulation tools results in prohibitive computational costs. Hence, in this study we use an alternate gradient-based approach. We first outline an algorithm that can be proven to recover Pareto fronts. The performance of this algorithm is then tested on three academic problems: a convex front with uniform spacing of Pareto points, a convex front with non-uniform spacing and a concave front. The algorithm is shown to be able to retrieve the Pareto front in all three cases hence overcoming a common deficiency in gradient-based methods that use the idea of scalarization. Then the algorithm is applied to a practical problem in concurrent design for aerodynamic and structural performance of an axial turbine blade. For this problem, with 5 design variables, and for 10 points to approximate the front, the computational cost of the gradient-based method was roughly the same as that of a method that builds the front from a sampling approach. However, as the sampling approach involves building a surrogate model to identify the Pareto front, there is the possibility that validation of this predicted front with CFD and FE analysis results in a different location of the “Pareto” points. This can be avoided with the gradient-based method. Additionally, as the number of design variables increases and/or the number of required points on the Pareto front is reduced, the computational cost favors the gradient-based approach.

Generalized Field-Development Optimization With Derivative-Free Procedures

SPE Journal ◽  
2014 ◽  
Vol 19 (05) ◽  
pp. 891-908 ◽  
Author(s):  
Obiajulu J. Isebor ◽  
David Echeverría Ciaurri ◽  
Louis J. Durlofsky
Keyword(s):  
Computational Cost ◽  
Optimization Method ◽  
Optimal Number ◽  
Global Search ◽  
Search Method ◽  
Pattern Search ◽  
Mixed Integer ◽  
Categorical Variables ◽  
Field Development ◽  
Derivative Free

Summary The optimization of general oilfield development problems is considered. Techniques are presented to simultaneously determine the optimal number and type of new wells, the sequence in which they should be drilled, and their corresponding locations and (time-varying) controls. The optimization is posed as a mixed-integer nonlinear programming (MINLP) problem and involves categorical, integer-valued, and real-valued variables. The formulation handles bound, linear, and nonlinear constraints, with the latter treated with filter-based techniques. Noninvasive derivative-free approaches are applied for the optimizations. Methods considered include branch and bound (B&B), a rigorous global-search procedure that requires the relaxation of the categorical variables; mesh adaptive direct search (MADS), a local pattern-search method; particle swarm optimization (PSO), a heuristic global-search method; and a PSO-MADS hybrid. Four example cases involving channelized-reservoir models are presented. The recently developed PSO-MADS hybrid is shown to consistently outperform the standalone MADS and PSO procedures. In the two cases in which B&B is applied, the heuristic PSO-MADS approach is shown to give comparable solutions but at a much lower computational cost. This is significant because B&B provides a systematic search in the categorical variables. We conclude that, although it is demanding in terms of computation, the methodology presented here, with PSO-MADS as the core optimization method, appears to be applicable for realistic reservoir development and management.

scholarly journals Modelling of textile composite reinforcements on the micro-scale

2014 ◽  
Vol 14 (1) ◽  
pp. 28-33 ◽  
Author(s):  
Oliver Döbrich ◽  
Thomas Gereke ◽  
Chokri Cherif
Keyword(s):  
Numerical Simulation ◽  
Finite Element Analysis ◽  
Computational Cost ◽  
Textile Composite ◽  
Element Analysis ◽  
Simulation Tools ◽  
Micro Scale ◽  
Generating Method ◽  
Geometrical Effects ◽  
Composite Reinforcements

Abstract Numerical simulation tools are increasingly used for developing novel composites and composite reinforcements. The aim of this paper is the application of digital elements for the simulation of the mechanical behaviour of textile reinforcement structures by means of a finite element analysis. The beneficial computational cost of these elements makes them applicable for the use in large models with a solution on near micro-scale. The representation of multifilament yarn models by a large number of element-chains is highly suitable for the analysis of structural and geometrical effects. In this paper, a unit cell generating method for technical reinforcement textiles, using digital elements for the discretization, is introduced.

scholarly journals Elliptic Curve Signcryption-Based Mutual Authentication Protocol for Smart Cards

2020 ◽  
Vol 10 (22) ◽  
pp. 8291
Author(s):  
Anuj Kumar Singh ◽  
Arun Solanki ◽  
Anand Nayyar ◽  
Basit Qureshi
Keyword(s):  
Elliptic Curve ◽  
Smart Card ◽  
Mutual Authentication ◽  
Computational Cost ◽  
Authentication Protocol ◽  
Security Protocol ◽  
Smart Cards ◽  
Communication Overhead ◽  
Authentication Mechanism ◽  
Computational Overhead

In the modern computing environment, smart cards are being used extensively, which are intended to authenticate a user with the system or server. Owing to the constrictions of computational resources, smart card-based systems require an effective design and efficient security scheme. In this paper, a smart card authentication protocol based on the concept of elliptic curve signcryption has been proposed and developed, which provides security attributes, including confidentiality of messages, non-repudiation, the integrity of messages, mutual authentication, anonymity, availability, and forward security. Moreover, the analysis of security functionalities shows that the protocol developed and explained in this paper is secure from password guessing attacks, user and server impersonation, replay attacks, de-synchronization attacks, insider attacks, known key attacks, and man-in-the-middle attacks. The results have demonstrated that the proposed smart card security protocol reduces the computational overhead on a smart card by 33.3% and the communication cost of a smart card by 34.5%, in comparison to the existing efficient protocols. It can, thus, be inferred from the results that using elliptic curve signcryption in the authentication mechanism reduces the computational cost and communication overhead by a significant amount.

Design and Simulation of Molded Interconnect Devices with Two Shot Molding

2011 ◽  
Vol 295-297 ◽  
pp. 1651-1655
Author(s):  
Yong Zhuo ◽  
Juan Peng ◽  
Yan Jun Wu
Keyword(s):  
Optimal Design ◽  
Three Dimensional ◽  
Manufacturing Processes ◽  
Specific Design ◽  
Product Model ◽  
Simulation Tools ◽  
Integrated Environment ◽  
Feature Technology ◽  
Effective Design ◽  
Molded Interconnect Devices

Three Dimensional Molded Interconnect Devices (3D-MID) has enormous potential for rationalization in both manufacturing process and the freedom to design of mechatronic products. Two shot molding is one of the most important and commonly used methods among the various MID manufacturing processes. Currently, there is a lack of effective design and simulation tools that can be used for MID with two shot molding. In this paper, an integrated product model using feature technology, some MID-specific design functions, and one special interface based on the API of Moldflow Plastics Insight (MPI) and the COM-Technology are presented. These developed product model, functions and interface increase the efficiency of the MID design process, and the design and simulation integrated environment also towards the rational and optimal design of MID products with two shot molding.

scholarly journals Reliability-Based Robust Design Optimization of Structures Considering Uncertainty in Design Variables

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Shujuan Wang ◽  
Qiuyang Li ◽  
Gordon J. Savage
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Robust Design ◽  
Structural Reliability ◽  
Computational Cost ◽  
Optimization Process ◽  
Robust Design Optimization ◽  
Global Approximation ◽  
Design Variables ◽  
Uncertainty In Design

This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO) method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method.

A Metamodeling Technique for Variable Geometry Trusses Design via Equivalent Parametric Macroelements

2009 ◽  
Vol 131 (10) ◽  
Author(s):  
Josu Aguirrebeitia ◽  
Carlos Angulo ◽  
Luis M. Macareno ◽  
Rafael Avilés
Keyword(s):  
Genetic Algorithms ◽  
Finite Elements ◽  
Elastic Energy ◽  
Computational Cost ◽  
Least Square ◽  
Optimization Process ◽  
Fe Model ◽  
Variable Geometry ◽  
Optimum Parameters ◽  
Metamodeling Technique

A metamodeling methodology is applied to reduce the large computational cost required in the design of variable geometry trusses (VGTs). Using this methodology, submodels of finite elements within a complete FE model of the VGT are substituted by groups of fewer elements called equivalent parametric macroelements (EPMs). The EPM optimum parameters are obtained using equivalence criteria based on elastic energy and inertial properties. The optimization process is performed using nonlinear least square minimization and genetic algorithms.

OPTIMAL DESIGN OF STRUCTURES USING THE SIMULTANEOUS PERTURBATION STOCHASTIC APPROXIMATION ALGORITHM

2009 ◽  
Vol 06 (02) ◽  
pp. 229-245 ◽  
Author(s):  
S. FALLAHIAN ◽  
D. HAMIDIAN ◽  
S. M. SEYEDPOOR
Keyword(s):  
Optimal Design ◽  
Stochastic Approximation ◽  
Optimization Problem ◽  
Computational Cost ◽  
Global Optimum ◽  
The Other ◽  
Optimization Process ◽  
Simultaneous Perturbation Stochastic Approximation ◽  
Stochastic Nature ◽  
Problem Dimension

This paper presents an application of the simultaneous perturbation stochastic approximation (SPSA) algorithm to optimization of structures. This method requires only two structural analyses in each cycle of optimization process, regardless of optimization problem dimension. This characteristic is very promising in reduction of computational cost of optimization process, especially in problems with a large number of variables to be optimized. Furthermore, the stochastic nature of the SPSA can enhance the convergence of the method to achieve the global optimum. In order to assess the effectiveness of the proposed method some benchmark truss examples are considered. The numerical results demonstrate the competence of the method in comparison with the other methods found in the literature.

Shape Optimization of Potentially Slender Structures

2008 ◽  
Author(s):  
Kavous Jorabchi ◽  
Joshua Danczyk ◽  
Krishnan Suresh
Keyword(s):  
Finite Element ◽  
Shape Optimization ◽  
Dimensional Reduction ◽  
A Priori ◽  
Computational Cost ◽  
Optimization Process ◽  
Element Analysis ◽  
Dimensional Reduction Method ◽  
Modern Engineering ◽  
Geometric Reduction

Shape optimization lies at the heart of modern engineering design. Through shape optimization, computers can, in theory, ‘synthesize’ engineering artifacts in a fully automated fashion. However, a serious limitation today is that the evolving geometry (during optimization) may become slender, i.e., beam or plate-like. Under such circumstances, modern 3-D computational methods, such as finite element analysis (FEA), will fail miserably, and so will the shape optimization process. Indeed, the recommended method for analyzing slender artifacts is to replace them with 1-D beams/ 2-D plates, prior to discretization and computational analysis, a process referred to as geometric dimensional reduction. Unfortunately explicit geometric reduction is impractical and hard to automate during optimization since one cannot predict a priori when an artifact will become slender. In this paper, we develop an implicit dimensional reduction method where the reduction is achieved through an algebraic process. The proposed method of reduction is computationally equivalent to explicit geometric reduction for comparable computational cost. However, the proposed method can be easily automated and integrated within a shape optimization process, and standard off-the-shelf 3-D finite element packages can be used to implement the proposed methodology.

Nested Kriging Surrogates for Rapid Multi-Objective Optimization of Compact Microwave Components

2021 ◽  
Vol 35 (11) ◽  
pp. 1344-1345
Author(s):  
Anna Pietrenko-Dabrowska ◽  
Slawomir Koziel
Keyword(s):  
Computational Cost ◽  
Search Space ◽  
Optimal Designs ◽  
Minimum Size ◽  
Space Region ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Microwave Components ◽  
Low Computational Cost

A procedure for rapid EM-based multi-objective optimization of compact microwave components is presented. Our methodology employs a recently developed nested kriging modelling to identify the search space region containing the Pareto-optimal designs, and to construct a fast surrogate model. The latter permits determination of the initial Pareto set, further refined using a separate surrogate-assisted process. As an illustration, a three-section impedance transformer is designed for the best matching and minimum size. The set of trade-off designs is produced at the low computational cost of only a few hundred of high-fidelity EM simulations of the transformer circuit despite a large number of its geometry parameters.

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