Low-Cost Design Optimization of Antennas with Peripheral Components

2020 ◽  
Author(s):  
Adrian Bekasiewicz ◽  
Slawomir Koziel
Keyword(s):  
Design Optimization ◽  
Low Cost

Improved Trust Region Model Management for Approximate Optimization

1998 ◽  
Author(s):  
Brett A. Wujek ◽  
John E. Renaud
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Low Cost ◽  
Approximation Error ◽  
Trust Region ◽  
Model Management ◽  
Multidisciplinary Design ◽  
Test Problems ◽  
Approximation Techniques ◽  
Approximate Optimization

Abstract Approximations play an important role in multidisciplinary design optimization (MDO) by offering system behavior information at a relatively low cost. Most approximate optimization strategies are sequential in which an optimization of an approximate problem subject to design variable move limits is iteratively repeated until convergence. The move limits are imposed to restrict the optimization to regions of the design space in which the approximations provide meaningful information. In order to insure convergence of the sequence of approximate optimizations to a Karush Kuhn Tucker solution a move limit management strategy is required. In this paper, issues of move-limit management are reviewed and a new adaptive strategy for move limit management is developed. With its basis in the provably convergent trust region methodology, the TRAM (Trust region Ratio Approximation Method) strategy utilizes available gradient information and employs a backtracking process using various two-point approximation techniques to provide a flexible move-limit adjustment factor. The new strategy is successfully implemented in application to a suite of multidisciplinary design optimization test problems. These implementation studies highlight the ability of the TRAM strategy to control the amount of approximation error and efficiently manage the convergence to a Karush Kuhn Tucker solution.

Analysis and design optimization of a low-cost axial flux Vernier machine with SMC cores and ferrite magnets

2020 ◽  
Vol 102 (4) ◽  
pp. 2595-2604
Author(s):  
Chengcheng Liu ◽  
Kelin Wang ◽  
Shaopeng Wang ◽  
Feng Niu ◽  
Youhua Wang
Keyword(s):  
Design Optimization ◽  
Low Cost ◽  
Axial Flux ◽  
Analysis And Design

SNB AOI Topside Design Optimization: Solution for Marginal Resources

2021 ◽  
Author(s):  
Rudi Syahru Mubarok ◽  
Monica Andriana ◽  
Albertino Prabowo
Keyword(s):  
Design Optimization ◽  
Detection System ◽  
Low Cost ◽  
Design Concept ◽  
Process Safety ◽  
Platform Design ◽  
Offshore Area ◽  
Knock Out ◽  
Area Of Interest ◽  
Fit For Purpose

Abstract Sisi Nubi Area of Interest (SNB AOI) is an ongoing project to develop the marginal resources located in Sisi Nubi offshore field operated by Pertamina Hulu Mahakam (PHM). As the resources being developed are small and scattered, low cost solution platform design is required to develop these marginal resources. Therefore, design optimization is a must. Fit-for-purpose design concept is used as the basis to develop process and safety facilities in new SNB AOI platforms while maintaining the compliance with government regulations and international codes and standards. Various exercises were performed in order to ensure optimized process, safety and operating philosophy requirement. Lesson learnt and benchmarking from various established platforms design including PHM's minimalist offshore/swamp platform were performed. The previous designs are reviewed, adopted and SNB AOI platform design is adjusted as per operating philosophy requirement. Based on the available basis of design and operating parameters, fully rated topside facilities design is considered feasible to be applied for new SNB AOI platforms. With this design, relief system size (i.e. vent stack and vent knock-out drum) can be further optimized. In addition, closed drain drum and LP (low pressure) vent knock-out drum is also combined in one single vessel after careful safety verification. Other optimization is externalizing equipment that could be managed with Operating Expenditure (e.g. well offloading activity by using external facility). As for process safety design, preliminary reviews based on international codes and standards showed that the following designs are considered feasible: portable Gas Detector by operator during platform visit (in lieu of permanent Gas Detection system), Fusible Plug loop installation only (instead of redundant protection using Flame Detector system), non-provision of dry fire water mains, application of Passive Fire Protection (PFP) only after confirmation from fire risk study (risk-based approach), and considering not permanently manned installation, 1 (one) stair & 1 (one) ladder combination on each platform deck (instead of dual stairs). Overall, the proposed design maintains the safety of installation with minimum impacts to future platform operation. This optimization has contributed to reduction of dimension and weight of topside installation (i.e. 32% less compared to PHM's latest Offshore Minimalist Platform design) and also weight of the structure. Design of SNB AOI project could become a good reference for other Pertamina affiliate and other companies and could open a further way forward to economically develop the "marginal resources", especially in offshore area, by implementing the "fit for purpose" design concept.

Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation

2019 ◽  
Vol 37 (2) ◽  
pp. 753-788
Author(s):  
Slawomir Koziel ◽  
Adrian Bekasiewicz
Keyword(s):  
Design Optimization ◽  
Design Problem ◽  
Low Cost ◽  
Computational Cost ◽  
Search Space ◽  
Population Based ◽  
Design Framework ◽  
Content Type ◽  
Multi Objective ◽  
Variable Fidelity

Purpose The purpose of this paper is to investigate the strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup. Design/methodology/approach Formulation of the multi-objective design problem-oriented toward execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploits variable fidelity modeling, physics- and approximation-based representation of the structure and model correction techniques. The considered approach is suitable for handling various problems pertinent to the design of microwave and antenna structures. Numerical case studies are provided demonstrating the feasibility of the segmentation-based framework for the design of real-world structures in setups with two and three objectives. Findings Formulation of appropriate design problem enables identification of the search space region containing Pareto front, which can be further divided into a set of compartments characterized by small combined volume. Approximation model of each segment can be constructed using a small number of training samples and then optimized, at a negligible computational cost, using population-based metaheuristics. Introduction of segmentation mechanism to multi-objective design framework is important to facilitate low-cost optimization of many-parameter structures represented by numerically expensive computational models. Further reduction of the design cost can be achieved by enforcing equal-volumes of the search space segments. Research limitations/implications The study summarizes recent advances in low-cost multi-objective design of microwave and antenna structures. The investigated techniques exceed capabilities of conventional design approaches involving direct evaluation of physics-based models for determination of trade-offs between the design objectives, particularly in terms of reliability and reduction of the computational cost. Studies on the scalability of segmentation mechanism indicate that computational benefits of the approach decrease with the number of search space segments. Originality/value The proposed design framework proved useful for the rapid multi-objective design of microwave and antenna structures characterized by complex and multi-parameter topologies, which is extremely challenging when using conventional methods driven by population-based metaheuristics algorithms. To the authors knowledge, this is the first work that summarizes segmentation-based approaches to multi-objective optimization of microwave and antenna components.

MEMS Accelerometer Design Optimization Using Genetic Algorithm

2013 ◽  
Vol 705 ◽  
pp. 288-294 ◽  
Author(s):  
V.S. Krushnasamy ◽  
A. Vimala Juliet
Keyword(s):  
Genetic Algorithm ◽  
Design Optimization ◽  
High Efficiency ◽  
Microelectromechanical Systems ◽  
Optimal Parameter ◽  
Low Cost ◽  
Complex Nature ◽  
Mems Accelerometer ◽  
Mems Technology ◽  
Parameter Values

MEMS (Microelectromechanical Systems) refers to the technology integrating electrical and mechanical components with feature size of 1~1000 microns. Due to its small size, low cost, low power consumption and high efficiency, MEMS technology has been widely used in many fields.In this paper,the design optimization of MEMS accelerometer is discussed.The main objective of this investigation is to find a optimum design of MEMS,which satisfies a set of given constraints. The accelerometer employs a double folded beam flexure system and the mass being displaced is the proof mass.Due to the complex nature of the problem,a genetic algorithm (GA) is developed for the optimization of MEMS.The GA attempts to minimize the die area and so the four optimal parameter values can be determined. MEMS accelerometers can be used in air-bag deployment systems in automobiles.The experimental results will show the optimal design of MEMS.

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