Multidisciplinary design optimization of mechanisms

The optimization of mechanisms is usually done in the field of mechanism itself. As a result the structural safety of the mechanism is neglected. To ensure the safety and improve the dynamic characteristics of mechanisms, a multidisciplinary design optimization procedure is proposed in this paper to synthesize optimum mechanisms. Two disciplines are involved in the multidisciplinary design optimization. They are the mechanism and the structure. The multi-level decomposition approach is chosen to generate optimum mechanisms. The optimized mechanisms not only satisfy mechanism and structural constraints but also have optimum objective function values in the two disciplines. In order to solve general mechanism design problems two widely used commercial softwares MSC/NASTRAN and MSC/ADAMS are integrated in the procedure to do the structural and the mechanism analysis, respectively. When the structural optimization is performed, a compromised approach is introduced to treat multiple configurations of mechanisms during operation. Two mechanism design problems are given to test the proposed method.     

卫星通信近期发展综述

随着对无所不在的通信需求和高数据率通信业务的不断增长,卫星通信所具有的无缝覆盖和通信容量大的优势将在新一代通信系统中发挥关键性的作用,卫星通信技术和信息通信产业也正在发生巨大的变革。对近年来卫星通信新技术和发展热点作了全面的综述,总结了多波束天线、星上处理的发展状况和卫星频谱资源的使用情况,概述了星地融合通信和卫星宽带通信并分析了发展中面临的挑战,展望了卫星通信的发展前景。     

Multidisciplinary design optimization of lumbar transpedicular screws

Some of the complications associated with the use of transpedicular screws for spinal fusions include the large diameters of the screws and screw breakagein vivo. Recent advances in multidisciplinary design optimization techniques have provided a unique approach to incorporate the structural, biological, and manufacturing disciplines involved in the design process of spinal screws, allowing the development of smaller and safer transpedicular screws.     

Multidisciplinary design optimization on vehicle tailor rolled blank design

Tailor rolled blank (TRB) is an emerging steel rolling process to produce lightweight vehicle components. It allows continuous metal thickness changes, and as a result, it offers opportunities for automotive design in weight reduction, part complexity reduction, reduced capital investment, yet, maintains equal to or better strength characteristics. The objective of this research is to take advantages of the TRB manufacturing technology and combine with the advanced multidisciplinary design optimization (MDO) methodology to optimize vehicle structure. The process begins with noise vibration and harshness (NVH) optimization. The outputs of the optimal NVH response sensitivities are employed to build the first order response surface models. Uniform Latin Hypercube sampling and subset selection regression methods are used to construct the response surface models for the highly nonlinear impact and seatbelt pull responses. The optimal NVH design is then used as the starting point for MDO to obtain the optimal thickness profiles for the TRB parts. A vehicle application considering multiple impact modes, seatbelt pulls, and NVH, is used to demonstrate the proposed process for vehicle underbody TRB design. Results of this MDO TRB study is presented and discussed.     

User modelling for adaptive computer systems: a survey of recent developments

User modelling is becoming an important sub-area of Artificial Intelligence with both theoretical and practical consequences. The theoretical foundations of user modelling are to be found in key areas of AI, such as knowledge representation and plan recognition, while its practical applications impinge on the construction of intelligent user interfaces and adaptive systems. This paper provides a survey of current work in user modelling. The paper begins by distinguishing between AI approaches, which are the subject of this survey, and those of HCI (Human-Computer Interaction) and then considers the major issues in user modelling such as: types of user modelling system, the sorts of information modelled, how the information is acquired, represented and used. The paper concludes by examining some of the more problematic aspects of user modelling as well as indicating areas for future research.     

Wireless sensor networks: a survey on recent developments and potential synergies

Wireless sensor network (WSN) has emerged as one of the most promising technologies for the future. This has been enabled by advances in technology and availability of small, inexpensive, and smart sensors resulting in cost effective and easily deployable WSNs. However, researchers must address a variety of challenges to facilitate the widespread deployment of WSN technology in real-world domains. In this survey, we give an overview of wireless sensor networks and their application domains including the challenges that should be addressed in order to push the technology further. Then we review the recent technologies and testbeds for WSNs. Finally, we identify several open research issues that need to be investigated in future. Our survey is different from existing surveys in that we focus on recent developments in wireless sensor network technologies. We review the leading research projects, standards and technologies, and platforms. Moreover, we highlight a recent phenomenon in WSN research that is to explore synergy between sensor networks and other technologies and explain how this can help sensor networks achieve their full potential. This paper intends to help new researchers entering the domain of WSNs by providing a comprehensive survey on recent developments.     

Multidisciplinary design optimization of a compact highly loaded fan

The recent progress in Multidisciplinary Design Optimization (MDO) enables engineers to revise design strategies and to address more complex problems. In this paper, the full design of a compact highly loaded fan for aerospace applications is considered. The design comprises several conflicting objectives, such as aerodynamic efficiency and structural integrity. Optimization techniques are applied at every stage of the design, leading to a reduced and accelerated overall process and an enlarged design space. Performance of the machine are first evaluated by through-flow modeling (low-fidelity radial distributions based on experimental correlations) to determine an optimal flow path configuration. High-fidelity aero-mechanical performances are then considered to generate the detailed design of the rotors, including section profiles along the span, as well as lean and sweep. The multi-objective algorithm enables one to consider simultaneously Computational Fluid Dynamics (CFD) and Computational Structural Mechanics (CSM). The methodology is applied to the design of a compact highly loaded fan achieving a 2.1 pressure ratio with an efficiency of 88 % while satisfying the mechanical constraint of titanium with a safety margin of 32 %. The proposed approach allows to generate an original configuration with a reduced time to market.     

多学科目标兼容优化算法及在MEMS中应用

针对复杂系统的优化设计问题,提出了面向非层级复杂系统的多学科目标兼容优化设计方法,对其基本思路、原理进行阐述。通过在系统级中建立兼容约束和在子系统中构造兼容目标,使各子系统在独立优化设计的同时满足各系统之间的耦合关系,并使系统得到总体的最优解。并将此算法应用于梳齿式微加速度计的设计中,验证了此方法的可行性。     

基于多级并行策略的复杂产品多学科设计优化

针对复杂产品设计需要进行多学科协作设计和优化的问题,结合计算机应用技术提出基于多级并行策略的多学科优化方法。该方法基于过程建模的层次化优化思想,实现复杂产品设计过程的自动化和优化。减速器标准多学科优化算例说明该方法可实现不同学科的层次化并行优化。将该方法与其他传统的多学科优化方法进行比较,验证该方法的高效性和最优设计的准确性。     

A survey of recent developments in parallel implementations of Gaussian elimination

Gaussian elimination is a canonical linear algebra procedure for solving linear systems of equations. In the last few years, the algorithm has received a lot of attention in an attempt to improve its parallel performance. This article surveys recent developments in parallel implementations of Gaussian elimination for shared memory architecture. Five different flavors are investigated. Three of them are based on different strategies for pivoting: partial pivoting, incremental pivoting, and tournament pivoting. The fourth one replaces pivoting with the Partial Random Butterfly Transformation, and finally, an implementation without pivoting is used as a performance baseline. The technique of iterative refinement is applied to recover numerical accuracy when necessary. All parallel implementations are produced using dynamic, superscalar, runtime scheduling and tile matrix layout. Results on two multisocket multicore systems are presented. Performance and numerical accuracy is analyzed. Copyright © 2014 John Wiley & Sons, Ltd.     

A survey of recent developments in cryptographic algorithms for smart cards

This article presents an update on recent developments in the area of cryptographic algorithms that are relevant for smart cards. It includes a review of the status of hash functions, block ciphers and stream ciphers and presents an update on authenticated or unforgeable encryption. Finally the issue of secure padding for the RSA algorithm is discussed and the status of Elliptic Curve Cryptography is briefly reviewed.     

Multidisciplinary design optimization for vehicle handling stability of steering-by-wire system

The Journal of Supercomputing - As the important performance of automobile, the vehicle handling stability has always been the focus of the research. The steering-by-wire (SBW) system is a major...     

Multidisciplinary design optimization with discrete and continuous variables of various uncertainties

As a powerful design tool, Reliability Based Multidisciplinary Design Optimization (RBMDO) has received increasing attention to satisfy the requirement for high reliability and safety in complex and coupled systems. In many practical engineering design problems, design variables may consist of both discrete and continuous variables. Moreover, both aleatory and epistemic uncertainties may exist. This paper proposes the formula of RFCDV (Random/Fuzzy Continuous/Discrete Variables) Multidisciplinary Design Optimization (RFCDV-MDO), uncertainty analysis for RFCDV-MDO, and a method of RFCDV-MDO within the framework of Sequential Optimization and Reliability Assessment (RFCDV-MDO-SORA) to solve RFCDV-MDO problems. A mathematical problem and an engineering design problem are used to demonstrate the efficiency of the proposed method.     

Multidisciplinary design of a small satellite launch vehicle using particle swarm optimization

In the present paper, particle swarm optimization, a relatively new population based optimization technique, is applied to optimize the multidisciplinary design of a solid propellant launch vehicle. Propulsion, structure, aerodynamic (geometry) and three-degree of freedom trajectory simulation disciplines are used in an appropriate combination and minimum launch weight is considered as an objective function. In order to reduce the high computational cost and improve the performance of particle swarm optimization, an enhancement technique called fitness inheritance is proposed. Firstly, the conducted experiments over a set of benchmark functions demonstrate that the proposed method can preserve the quality of solutions while decreasing the computational cost considerably. Then, a comparison of the proposed algorithm against the original version of particle swarm optimization, sequential quadratic programming, and method of centers carried out over multidisciplinary design optimization of the design problem. The obtained results show a very good performance of the enhancement technique to find the global optimum with considerable decrease in number of function evaluations.     

Multidisciplinary optimization of car bodies

Rising complexity of industrial development in the automotive industry is leading to a higher degree of interdisciplinarity, which is especially true in the virtual design area. New methods and solution procedures have to be evaluated and integrated in the overall process. For example, in car body design process, a new topic emerged recently: the multidisciplinary optimization of car bodies with respect to crash and NVH (noise, vibration, and harshness). Because rigorous evaluation of appropriate numerical algorithms is still missing, an intense study was realized at the research center of BMW. The results are summarized in this article. Four benchmarks have been studied: (a) a full vehicle model for NVH analysis, (b) a simplified multidisciplinary problem with a single crash case and linear statics and dynamics, (c) a lateral impact problem for multi-criteria optimization, and finally, (d) a small shape optimization problem was included to demonstrate the potential of transferring the results to the more complex problem of optimizations based on real changes in the shape of the structures. Because response surface methods have already been discussed in the literature and because of their failure in certain industrial cases, the focus was set on the evaluation of stochastic algorithms: simulated annealing, genetic and evolutionary algorithms were tested. Finally, a complete industrial multidisciplinary example from the current development process was studied for the validation of the results.     

A survey of multidisciplinary design optimization methods in launch vehicle design

Optimal design of launch vehicles is a complex problem which requires the use of specific techniques called Multidisciplinary Design Optimization (MDO) methods. MDO methodologies are applied in various domains and are an interesting strategy to solve such an optimization problem. This paper surveys the different MDO methods and their applications to launch vehicle design. The paper is focused on the analysis of the launch vehicle design problem and brings out the advantages and the drawbacks of the main MDO methods in this specific problem. Some characteristics such as the robustness, the calculation costs, the flexibility, the convergence speed or the implementation difficulty are considered in order to determine the methods which are the most appropriate in the launch vehicle design framework. From this analysis, several ways of improvement of the MDO methods are proposed to take into account the specificities of the launch vehicle design problem in order to improve the efficiency of the optimization process.     

Multidisciplinary optimization design of a new underwater vehicle with highly efficient gradient calculation

Structural and Multidisciplinary Optimization - In order to reduce the cost of oceanographic exploration, a new underwater vehicle is designed to sail the required distance with the lowest energy...