19,430 research outputs found

    Improving machine dynamics via geometry optimization

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    The central thesis of this paper is that the dynamic performance of machinery can be improved dramatically in certain cases through a systematic and meticulous evolutionary algorithm search through the space of all structural geometries permitted by manufacturing, cost and functional constraints. This is a cheap and elegant approach in scenarios where employing active control elements is impractical for reasons of cost and complexity. From an optimization perspective the challenge lies in the efficient, yet thorough global exploration of the multi-dimensional and multi-modal design spaces often yielded by such problems. Morevoer, the designs are often defined by a mixture of continuous and discrete variables - a task that evolutionary algorithms appear to be ideally suited for. In this article we discuss the specific case of the optimization of crop spraying machinery for improved uniformity of spray deposition, subject to structural weight and manufacturing constraints. Using a mixed variable evolutionary algorithm allowed us to optimize both shape and topology. Through this process we have managed to reduce the maximum roll angle of the sprayer by an order of magnitude , whilst allowing only relatively inexpensive changes to the baseline design. Further (though less dramatic) improvements were shown to be possible when we relaxed the cost constraint. We applied the same approach to the inverse problem of reducing the mass while maintaining an acceptable roll angle - a 2% improvement proved possible in this cas

    Exploiting hybrid parallelism in the kinematic analysis of multibody systems based on group equations

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    Computational kinematics is a fundamental tool for the design, simulation, control, optimization and dynamic analysis of multibody systems. The analysis of complex multibody systems and the need for real time solutions requires the development of kinematic and dynamic formulations that reduces computational cost, the selection and efficient use of the most appropriated solvers and the exploiting of all the computer resources using parallel computing techniques. The topological approach based on group equations and natural coordinates reduces the computation time in comparison with well-known global formulations and enables the use of parallelism techniques which can be applied at different levels: simultaneous solution of equations, use of multithreading routines, or a combination of both. This paper studies and compares these topological formulation and parallel techniques to ascertain which combination performs better in two applications. The first application uses dedicated systems for the real time control of small multibody systems, defined by a few number of equations and small linear systems, so shared-memory parallelism in combination with linear algebra routines is analyzed in a small multicore and in Raspberry Pi. The control of a Stewart platform is used as a case study. The second application studies large multibody systems in which the kinematic analysis must be performed several times during the design of multibody systems. A simulator which allows us to control the formulation, the solver, the parallel techniques and size of the problem has been developed and tested in more powerful computational systems with larger multicores and GPU.This work was supported by the Spanish MINECO, as well as European Commission FEDER funds, under grant TIN2015-66972-C5-3-

    A distributed optimization framework for localization and formation control: applications to vision-based measurements

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    Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures

    ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ๊ณผ ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํŠน์„ฑ์„ ๋™์‹œ์— ๊ณ ๋ คํ•œ ๊ธฐ๊ตฌ ์œ„์ƒ ๋ฐ ํ˜•์ƒ ํ†ตํ•ฉ ์ตœ์ ์„ค๊ณ„

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€(๋ฉ€ํ‹ฐ์Šค์ผ€์ผ ๊ธฐ๊ณ„์„ค๊ณ„์ „๊ณต), 2020. 8. ๊น€์œค์˜.Mechanism synthesis based on topology optimization has recently received much attention as an efficient design approach. The main thrust behind this trend is the capability of this method to determine automatically the topology and dimensions of linkage mechanisms. Towards this direction, there have been many investigations, but they have thus far focused mainly on mechanism synthesis considering kinematic characteristics describing a desired path or motion. Here, we propose a new topology optimization method that synthesizes a linkage mechanism considering not only kinematic but also compliance (K&C) characteristics simultaneously, as compliance characteristics can also significantly affect the linkage mechanism performance; compliance characteristics dictate how elastic components, such as bushings in a vehicle suspension, are deformed by external forces. To achieve our objective, we use the spring-connected rigid block model (SBM) developed earlier for mechanism synthesis considering only kinematic characteristics, but we make it suitable for the simultaneous consideration of K&C characteristics during mechanism synthesis by making its zero-length springs multifunctional. Variable-stiffness springs were used to identify the mechanism kinematic configuration only, but now in the proposed approach, they serve to determine not only the mechanism kinematic configuration but also the compliance element distribution. In particular, the ground-anchoring springs used to anchor a linkage mechanism to the ground are functionalized to simulate actual bushings as well as to identify the desired linkage kinematic chain. After the proposed formulation and numerical implementation are presented, three case studies to synthesize planar linkage mechanisms were considered. Through these case studies, we verified the validation of the proposed approach and proved that the proposed methodology could solve problems when existing methods could not. After the effectiveness of the proposed method is demonstrated with a simplified two-dimensional vehicle suspension design problem, the proposed methodology is applied to design a three-dimensional suspension. To deal with three-dimensional mechanisms, a spatial SBM is newly developed because only planar SBMs have been developed. Furthermore, a set of design variables which can vary bushing stiffness are newly introduced. Using the proposed method, it was possible to successfully synthesize two types of suspension mechanisms which have similar kinematic characteristics to each other but different compliance characteristics. By using the proposed method simultaneously considering kinematic and compliance characteristics, a unique suspension mechanism having an integral module which is known to improve R&H performances was synthesized. In this study, although applications were made only to the design of vehicle suspensions, other practical design problems for which K&C characteristics must be considered simultaneously can be also effectively solved by the proposed approach. This study is expected to pave the way to advance the topology optimization method for general linkage mechanisms considering kinematic characteristics but also the other characteristics such as force-related characteristics.์œ„์ƒ ์ตœ์ ํ™”(topology optimization) ๊ธฐ๋ฒ•์„ ์ด์šฉํ•œ ํ•œ ๊ธฐ๊ตฌ ํ•ฉ์„ฑ(mechanism synthesis)์€ ๊ทธ ํšจ์œจ์„ฑ์œผ๋กœ ์ธํ•ด ์ตœ๊ทผ ๋งŽ์€ ์ฃผ๋ชฉ์„ ๋ฐ›๊ณ  ์žˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ถ”์„ธ์˜ ์ฃผ ์›์ธ์€ ๊ธฐ๊ตฌ ์œ„์ƒ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์œผ๋กœ ์ธํ•ด ๊ธฐ๊ตฌ์˜ ์œ„์ƒ(topology)๊ณผ ์น˜์ˆ˜(dimension)๋ฅผ ์ž๋™์œผ๋กœ ํ•ฉ์„ฑํ•  ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐฉํ–ฅ์„ฑ์„ ๊ฐ€์ง€๊ณ  ์ง€๊ธˆ๊นŒ์ง€ ๋งŽ์€ ์—ฐ๊ตฌ๋“ค์ด ์ง„ํ–‰๋˜์–ด ์™”์ง€๋งŒ, ์ง€๊ธˆ๊นŒ์ง€ ์ง„ํ–‰๋œ ์—ฐ๊ตฌ๋“ค์€ ๋ชจ๋‘ ๊ฒฝ๋กœ ํ•ฉ์„ฑ์ด๋‚˜ ์šด๋™ ํ•ฉ์„ฑ๊ณผ ๊ฐ™์ด ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ์„ ๊ณ ๋ คํ•˜๋Š” ๋ฐ์—๋งŒ ๊ด€์‹ฌ์ด ์ง‘์ค‘๋˜์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ๊ตฌ์˜ ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ(kinematic characteristics)๊ณผ ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํŠน์„ฑ(compliance characteristics)์„ ๋™์‹œ์— ๊ณ ๋ คํ•  ์ˆ˜ ์žˆ๋Š” ์ƒˆ๋กœ์šด ๊ธฐ๊ตฌ ์œ„์ƒ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์„ ์ œ์•ˆํ•œ๋‹ค. ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ์€ ๊ธฐ๊ตฌ ์„ค๊ณ„์— ์žˆ์–ด ๋งค์šฐ ์ค‘์š”ํ•œ ํŠน์„ฑ์ด์ง€๋งŒ, ์™ธ๋ ฅ์ด ์ž‘์šฉํ•˜์˜€์„ ๋•Œ ์ž๋™์ฐจ ์„œ์ŠคํŽœ์…˜(vehicle suspension)์˜ ๋ถ€์‹ฑ(bushing)๊ณผ ๊ฐ™์€ ํƒ„์„ฑ ์š”์†Œ๋“ค์˜ ๋ณ€ํ˜•์œผ๋กœ ์ธํ•ด ๋‚˜ํƒ€๋‚˜๋Š” ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํŠน์„ฑ ๋˜ํ•œ ๊ธฐ๊ตฌ ์„ค๊ณ„ ์‹œ ๊ณ ๋ คํ•ด์•ผ ํ•  ์ค‘์š”ํ•œ ํŠน์„ฑ์ด๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ์ƒˆ๋กœ์šด ๊ธฐ๊ตฌ ์œ„์ƒ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์„ ์œ„ํ•ด ์šฐ๋ฆฌ๋Š” ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ๋งŒ์„ ๊ณ ๋ คํ•˜๊ธฐ ์œ„ํ•ด ๊ฐœ๋ฐœ๋˜์—ˆ๋˜ ์Šคํ”„๋ง-์—ฐ๊ฒฐ ๋ธ”๋ก ๋ชจ๋ธ(spring-connected block model)์„ ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ๊ณผ ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํŠน์„ฑ์„ ๋™์‹œ์— ๊ณ ๋ คํ•  ์ˆ˜ ์žˆ๋„๋ก ๊ณ ์•ˆํ•˜์˜€๋‹ค. ๊ธฐ์กด์˜ ์Šคํ”„๋ง-์—ฐ๊ฒฐ ๋ธ”๋ก ๋ชจ๋ธ์—์„œ๋Š” ๊ธฐ๊ตฌํ•™์  ์—ฐ๊ฒฐ ๊ด€๊ณ„๋งŒ์„ ํ‘œํ˜„ํ•˜๋Š”๋ฐ ์‚ฌ์šฉ๋˜๋˜ ๊ฐ€๋ณ€ ๊ฐ•์„ฑ ์Šคํ”„๋ง์„ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๊ธฐ๊ตฌํ•™์  ์—ฐ๊ฒฐ ๊ด€๊ณ„๋ฟ ์•„๋‹ˆ๋ผ ์‹ค์ œ ๋ถ€์‹ฑ์„ ํ‘œํ˜„ํ•˜๋„๋ก ๋‹ค๋ชฉ์ ์œผ๋กœ ํ™œ์šฉํ•˜์—ฌ ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ๊ณผ ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํŠน์„ฑ์„ ํ•˜๋‚˜์˜ ๋ชจ๋ธ๋ง์„ ํ†ตํ•ด ์„ฑ๊ณต์ ์œผ๋กœ ํ‘œํ˜„ํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœํ•œ ๋ฐฉ๋ฒ•๋ก ์˜ ํšจ๊ณผ๋ฅผ ์ž…์ฆํ•˜๊ธฐ ์œ„ํ•ด ํ‰๋ฉด ๊ธฐ๊ตฌ ํ•ฉ์„ฑ์„ ๋ชฉํ‘œ๋กœ ํ•œ ์„ธ ์ข…๋ฅ˜์˜ ์‚ฌ๋ก€ ์—ฐ๊ตฌ(case study)๋ฅผ ์ง„ํ–‰ํ•˜์˜€๊ณ , ์ด๋Ÿฌํ•œ ์‚ฌ๋ก€ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ์šฐ๋ฆฌ๋Š” ์ œ์•ˆํ•œ ๋ฐฉ๋ฒ•์ด ๊ธฐ์กด์˜ ๋ฐฉ๋ฒ•์œผ๋กœ๋Š” ํ•ด๊ฒฐํ•  ์ˆ˜ ์—†๋Š” ๋ฌธ์ œ ์ƒํ™ฉ์„ ํ•ด๊ฒฐํ•  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ฐœ๋ฐœํ•œ ๋ฐฉ๋ฒ•๋ก ์„ ๋ณด๋‹ค ์‹ค์šฉ์ ์ธ ๋ฌธ์ œ์— ์ ์šฉํ•˜๊ธฐ ์œ„ํ•ด 3์ฐจ์› ์ž๋™์ฐจ ์„œ์ŠคํŽœ์…˜(vehicle suspension) ์„ค๊ณ„ ํ•˜๊ณ ์ž ํ•˜์˜€์œผ๋ฉฐ, ์ด๋ฅผ ์œ„ํ•ด ์Šคํ”„๋ง-์—ฐ๊ฒฐ ๋ธ”๋ก ๋ชจ๋ธ์„ 3์ฐจ์›์œผ๋กœ ํ™•์žฅํ•˜์˜€๋‹ค. ๋˜ํ•œ, ๋ณด๋‹ค ์‹ค์šฉ์ ์ธ ์„ค๊ณ„ ๊ฒฐ๊ณผ ๋„์ถœ์„ ์œ„ํ•ด 2์ฐจ์› ์‚ฌ๋ก€ ์—ฐ๊ตฌ์—์„œ๋Š” ์‚ฌ์šฉํ•˜์ง€ ์•Š์•˜๋˜ ๋ถ€์‹ฑ ๊ฐ•์„ฑ ์กฐ์ ˆ ์„ค๊ณ„ ๋ณ€์ˆ˜๋ฅผ ์ถ”๊ฐ€์ ์œผ๋กœ ๋„์ž…ํ•˜์—ฌ, ๋ถ€์‹ฑ ๊ฐ•์„ฑ๋„ ๋™์‹œ์— ์„ค๊ณ„๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. 3์ฐจ์› ์„œ์ŠคํŽœ์…˜ ์„ค๊ณ„๋Š” ๊ธฐ๊ตฌํ•™์  ์กฐ๊ฑด์€ ๋™์ผํ•˜์ง€๋งŒ, ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํŠน์„ฑ์€ ๋‹ค๋ฅธ ๋‘ ๊ฐ€์ง€ ์กฐ๊ฑด์— ๋Œ€ํ•ด ์ง„ํ–‰๋˜์—ˆ์œผ๋ฉฐ, ๋‘ ์„ค๊ณ„ ์กฐ๊ฑด์—์„œ ๋ชจ๋‘ ์„œ์ŠคํŽœ์…˜ ํ•ฉ์„ฑ์— ์„ฑ๊ณตํ•˜์˜€๋‹ค. ํŠนํžˆ, ๋‘ ์„œ์ŠคํŽœ์…˜์˜ ๊ฒฐ๊ณผ ์œ„์ƒ์ด ์„œ๋กœ ๋‹ค๋ฅธ ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋Š”๋ฐ, ์ด๋ฅผ ํ†ตํ•ด ๊ธฐ๊ตฌํ•™์  ์กฐ๊ฑด์€ ๋™์ผํ•˜๋˜ ์ปดํ”Œ๋ผ์ด์–ธ์Šค ์กฐ๊ฑด์ด ๋‹ฌ๋ผ์ง€๋ฉด ๊ฒฐ๊ณผ ์œ„์ƒ์ด ๋‹ฌ๋ผ์งˆ ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๊ณ , ๊ฐœ๋ฐœํ•œ ๋ฐฉ๋ฒ•๋ก ์„ ํ†ตํ•ด ์„ค๊ณ„ ์กฐ๊ฑด์— ๋งž๋Š” ๊ธฐ๊ตฌ์˜ ์œ„์ƒ๊ณผ ์น˜์ˆ˜ ๊ทธ๋ฆฌ๊ณ  ํ•„์š”ํ•œ ๋ถ€์‹ฑ ๊ฐ•์„ฑ๊นŒ์ง€๋„ ์„ฑ๊ณต์ ์œผ๋กœ ์„ค๊ณ„ํ•  ์ˆ˜ ์žˆ์Œ์„ ์ฆ๋ช…ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ปดํ”Œ๋ผ์ด์–ธ์Šค ์กฐ๊ฑด์ด ํŠนํžˆ ์ค‘์š”์‹œ ๋˜๋Š” ์ž๋™์ฐจ ์„œ์ŠคํŽœ์…˜์„ ์„ค๊ณ„ํ•˜๋Š”๋ฐ ์ง‘์ค‘ํ•˜์˜€์ง€๋งŒ, ๊ฐœ๋ฐœํ•œ ๋ฐฉ๋ฒ•๋ก ์€ ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ๊ณผ ์ปดํ”Œ๋ผ์ด์–ธ์Šค ํŠน์„ฑ์ด ๋ชจ๋‘ ์š”๊ตฌ๋˜๋Š” ๋‹ค๋ฅธ ์„ค๊ณ„ ๋ฌธ์ œ์—๋„ ์ ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ๋˜ํ•œ, ์ด ์—ฐ๊ตฌ๋Š” ๊ธฐ๊ตฌํ•™์  ํŠน์„ฑ๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ํž˜๊ณผ ๊ด€๋ จ๋œ ๋‹ค๋ฅธ ํŠน์„ฑ์„ ๊ณ ๋ คํ•œ ์ผ๋ฐ˜์ ์ธ ๊ธฐ๊ตฌ ์œ„์ƒ ์ตœ์ ํ™” ๊ธฐ๋ฒ•์œผ๋กœ์˜ ๋ฐœ์ „์— ๊ธฐ์—ฌํ•  ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.CHAPTER 1. Introduction 1 1.1 Motivation and related literatures 1 1.2 Research objectives 6 1.3 Background research 8 1.3.1 Linkage mechanism synthesis based on the spring-connected rigid block model (SBM) 8 1.3.2 Determination of the systems degree-of-freedom (DOF) based on the work transmittance efficiency function 10 1.4 Outline of thesis 12 CHAPTER 2. Unified topology and shape optimization method for the mechanism synthesis simultaneously considering kinematic and compliance (K&C) characteristics 18 2.1 Overview 18 2.2 Modeling and analysis 23 2.2.1 Modeling 23 2.2.2 Kinematic and compliance analyses with the SBM 26 2.3 Optimization Formulation 33 2.3.1 Design variable and interpolation 33 2.3.2 Objective and constraint functions 35 2.3.3 Sensitivity analysis 39 2.4 Case studies 43 2.4.1 Case study 1 - Validation of the proposed method 43 2.4.2 Case study 2 - Demonstration of the advantage of the proposed method 46 2.4.3 Case study 3 - Application to the design of a 2D vehicle suspension 50 2.5 Summary 57 CHAPTER 3. Design of vehicle suspensions for rear using topology optimization method considering K&C characteristics 78 3.1 Overview 78 3.2 Modeling and analysis based on the spatial SBM 81 3.2.1 The spatial SBM for the design of a vehicle suspension 81 3.2.2 Kinematic and compliance analyses by the spatial SBM 83 3.3 Optimization Formulation 90 3.3.1 Design variable and interpolation 90 3.3.2 Objective and constraint functions 93 3.3.3 Sensitivity analysis 95 3.4 Design of vehicle suspensions for rear using the proposed method 99 3.4.1 Definition of problem 99 3.4.2 Design Case 1 - Recovery of a double wishbone suspension 101 3.4.3 Design Case 2 - Suspension synthesis for improving ride and handling (R&H) performances 104 3.5 Summary 110 CHAPTER 4. Conclusions 133 APPENDIX A. Target cascading process for deriving K&C characteristics of a suspension to improve vehicles R&H performances 138 A.1 Overview 138 A.2 Ride and handling (R&H) performances 139 A.3 Analysis procedure to evaluate R&H performances using a double wishbone suspension 140 A.4 Design optimization of a double wishbone suspension for deriving K&C characteristics to improve R&H performances 141 A.4.1 Design variable and interpolation 141 A.4.2 Metamodeling 142 A.4.3 Optimization formulation 144 A.4.4 Optimization result 145 APPENDIX B. Technique to suppress floating blocks 158 B.1 Overview 158 B.2 Explanation of techniques to suppress floating blocks 159 B.3 Revisit Case study 3 for applying the technique to suppress floating blocks 161 APPENDIX C. Investigation of mesh dependency issue 167 C.1 Overview 167 C.2 Re-consideration of Case study 1 with the more number of rigid blocks 168 REFERENCES 172 ABSTRACT (KOREAN) 181 ACKNOWLEDTEMENTS 184Docto
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