Dynamic Analysis of Epicyclic Gear Trains by Means of Computer Algebra

The paper illustrates the application of a systematic technique for thededuction of dynamic equations of epicyclic gear trains. The use of theproposed method is particularly amenable in conjuction with proceduresfor the computerized enumeration of geared kinematic chains. Thediscussed examples illustrate how the presented approach can be extendedfor computing the equivalent inertia of an epicyclic gear train or forthe stability analysis of 2 d.o.f. gear trains.     

A genetic algorithm approach to piping route path planning

A genetic algorithm (GA) approach to support interactive planning of a piping route path in plant layout design is presented. To present this approach, the paper mainly describes the basic ideas used in the methodology, which include the definition of genes to deal with pipe routes, the concept of spatial potential energy, the method of generating initial individuals for GA optimization, the zone concept in route generation using GAs, the evaluation of crossover methods, and definition and application of fitness functions. The prototype system that has been developed based on the methodology gives designers an environment to design a piping route path in an interactive and collaborative manner with a very simple operation. The GA optimization technique generates a route path through evolution of genes that represent the pipe route. A designer evaluates the route path, modifies it, conducts another GA optimization and/or repeats the procedure until the appropriate route is desig ned. The paper also presents some simulation results using the prototype system to show the validity of this approach.     

基于径向基网络与交互式遗传算法的服装设计

针对将交互式遗传算法应用到服装设计中产生的人的疲劳问题,提出利用神经网络来逼近适应度函数.给出了以GA操作产生的每代最佳个体初步作为神经网络径向基网络函数的中心值并结合相似距离值,利用K-Means求出径向基网络的各参数以逼近适应度函数.在服装设计系统应用中取得了良好的效果.     

Genetic algorithm approach for precedence-constrained sequencing problems

In this paper we propose a genetic algorithm (GA) approach based on a topological sort (TS)-based representation procedure for effectively solving precedence-constrained sequencing problems (PCSPs). The TS-based representation procedure used in the proposed GA approach can generate feasible sequences in PCSPs. By applying the proposed GA approach, the sequence determination problems with precedence constraints can be easily solved. Experimental results show that the proposed GA approach is a good alternative in locating optimal sequence for various types of PCSPs.     

An artificial intelligence approach to the efficiency improvement of a universal motor

This paper presents a design approach for improvement of the efficiency of a universal motor, the type of motor that is typically used in home appliances and power tools. The goal of our optimization was to find optimal values of the independent geometrical parameters of the rotor and the stator of the UM with the aim of reducing the motor's main power losses—they occur in the iron and the copper. Our procedure is based on a genetic algorithm (GA), and by using it we were able to significantly improve the motor's efficiency. The GA proved to be a simple and efficient search-and-optimization method for solving this day-to-day design problem in industry. It significantly outperformed a conventional design procedure that was used previously.     

An optimum preliminary strength design of reinforced concrete frames

An optimization procedure is organized for the preliminary design of a multistory-multibay, moment-resisting reinforced concrete frame. A reduced set of collapse mechanisms are used to define the kinematic constraints, special constraints are defined in order to satisfy building code requirements and practical design considerations. In the proposed optimum preliminary design the total volume of reinforcing steel required by the members of the structure is minimized. A strong column—weak beam design results from the optimization study. An example is presented to illustrate the proposed method.     

遗传算法在钟表机芯设计中的应用

在钟表机芯设计中，齿轮参数的优化设计是一个组合优化问题，很难用传统优化方法解决.遗传算法是一种基于生物进化原理的启发式搜索方法，近年来，它成功地解决了许多计算难题.使用该算法的难点是如何将具体问题映射成适于该算法的编码以及根据编码进行各种操作.该文对传动系统各齿轮参数序号进行编码，成功地解决了齿轮参数的优化设计问题，也为一般机械设计中传动系统参数的优化提供了经验.通过比较，利用遗传算法得出的参数比用专家系统得出的参数更优.     

Immune network simulations in multicriterion design

A modification to the genetic algorithm (GA) based search procedure, based on the modeling of a biological immune system, is proposed as an approach to solving the multicriterion design problem. Such problems have received considerable attention, given that decisions in engineering design practice typically require allocation of resources to satisfy multiple, and frequently conflicting requirements. The approach is particularly amenable to problems with a mix of continuous, discrete, and integer design variables, where the GA has been shown to perform in an effective manner. The approach considered in the present work is based on the concept of converting the multicriterion problem into one with a scalar objective through the use of the utility function. The strength of the approach is in its ability to generate the Pareto-Edgeworth front of compromise solutions in a single execution of the GA. A characteristic feature of biological immune systems which allows for the generation of multiple specialist antibodies, is shown to be an effective approach to facilitate the generation of the Pareto-Edgeworth front. Solutions to problems in structural design are presented in support of the proposed approach.     

Optimal Design of Gear Ratios and Offset for Energy Conservation of an Articulated Manipulator

It is important to minimize the energy dissipated by the reduction gears and motors in a three-jointed vertically articulated manipulator. This paper proposes an optimal design method for simultaneously determining eight design variables, which are three motor masses, three reduction gear ratios, a counterbalancer mass for the third link and an offset between the first and the second links. Using these design variables, the equation of motion and the dissipated energy can be expressed as functions of the moment of inertia and the Coulomb friction torque of the joints and the inertia matrix of the manipulator. Optimal design variables can be determined by minimizing the dissipated energy under the constraint conditions for the motors and the offset. The numbers of stages for the reduction gear trains are determined from the optimal gear ratios. Simulations show that the proposed design method can reduce the dissipated energy more effectively than the inertia matching method.      

Automated development of neural net analysis and optimization expert

The envisioned role of an Automated Intelligent Designer Associate (AIDA) is to help the creative designer to conveniently explore his design concepts. Such a capability should be able to learn and improve its performance by accumulating experience. As a step towards an AIDA capability, Artificial Neural Nets are shown to capture structural analysis and optimization domain expertise and provide quick estimates of structural behavior and of optimum designs within the domain of their training. In the approach discussed here, an automated procedure generates random instances of structural analysis or optimization “experiences” within a design domain, extracts training patterns, constructs and trains an appropriate network architecture. The final product is a trained neural net that can estimate analysis or optimization results for given design conditions within the domain of its “expertise”.     

A note on genetic algorithms for large-scale feature selection

We introduce the use of genetic algorithms (GA) for the selection of features in the design of automatic pattern classifiers. Our preliminary results suggest that GA is a powerful means of reducing the time for finding near-optimal subsets of features from large sets.     

An inverse shape design method for railway wheel profiles

Optimisation of a railway vehicle–track system is a complex process. The paper presents a procedure for optimal design of a wheel profile based on geometrical wheel/rail contact characteristics such as the rolling radii difference (RRD). The procedure uses optimality criteria based on an RRD function. The criteria account for stability of wheelset, cost efficiency, minimum wear of wheels and rails as well as safety requirements. The shape of the wheel profile approximated by a piecewise cubic Hermite interpolating polynomial is varied during the optimisation process to satisfy the optimality criteria. A numerical technique called multipoint approximations based on response surface fitting (MARS) has been chosen as an optimisation method. The proposed optimum design procedure has been applied to improve the performance of metro trains in Rotterdam (RET), The Netherlands. The trains were suffering from severe wheel tread wear and as a result of that from lateral vibrations (hunting). Using the proposed procedure, a new wheel profile has been obtained and applied to the RET metro trains. The results of the optimisation have shown that the performance of a railway vehicle can be improved by improving the contact properties of the wheel and rail. After the application of the optimised wheel profile, the instability of the metro trains has been eliminated and the lifetime of the wheels has been increased from 15,000 to 120,000 km.     

Computerized design of modified helical gears finished by plunge shaving

Among the several types of gear shaving operations, plunge shaving is used for finishing gears in mass-production due to the low cost and short machining time. Plunge shaving may be used to apply surface modifications with the purpose of reducing noise and vibration by the predesign of favorable functions of transmission errors, and modify gear tooth surfaces to avoid edge contacts and increase gear endurance, safety, and service life. A new geometry for helical gear tooth surfaces that combine the advantages of gear drives with lineal and localized contacts is proposed and obtained by plunge shaving. The shaver tooth surfaces are conjugated to those of an ideal helical gear with surface modifications. In this way, the to-be-shaved gear and the shaving cutter will be in line contact, and only a radial feed motion of the shaver is needed to generate the required pressure for the shaver to cut the excess of material on the gear tooth surfaces. A numerical example of design illustrates the advantages of the proposed geometry.     

Process Parameters Optimization: A Design Study for TiO$_{2}$ Thin Film of Vacuum Sputtering Process

This paper proposes a procedure for process parameters design by combining both modeling and optimization methods. The proposed procedure integrates the Taguchi method, the artificial neural network (ANN), and the genetic algorithm (GA). First, the Taguchi method is applied to minimize experimental numbers and to collect experimental data representing the quality performances of a system. Next, the ANN is used to build a system model based on the data from the Taguchi experimental method. Then, the GA is employed to search for the optimal process parameters. A process parameters design for a titanium dioxide (TiO₂) thin film in the vacuum sputtering process is studied in this paper. The quality objective is to form a smaller water contact angle on the TiO₂ thin-film surface. The water contact angle is 4° obtained from the system model of the proposed procedure. The process parameters obtained from the proposed procedure were used to conduct the experiment in the vacuum sputtering process for the TiO₂ thin film. The water contact angle given from the practical experiment is 3.93°. The difference percent is 1.75% between 4° and 3.93°. The result obtained from the system model of the proposed procedure is promising. Hence, we can conclude that the proposed procedure is a very good approach in solving the problem of the process parameters design.     

融合可拓语义和模糊综合评价的地铁列车外观设计方法

为进一步提升和彰显地铁列车外形中的地域文化特征,提出了一种基于专家和用 户视角的融合可拓语义和模糊综合评价的地铁列车外观设计方法。基于可拓语义提出了文化基 元概念,构建了涵盖文化载体、文化特征和文化价值的三元组,给出了地铁列车外观设计中的 可拓语义分析与表征步骤;基于模糊综合评价法来评估地铁列车外观设计方案的文化特征,给 出了评估流程,并以一款低速 B2 型成都地铁列车外观设计为例,结合专家和用户调查,从文化 提取与表征、方案设计和方案评估 3 方面对所提方法的可行性进行了验证。研究结果表明：该 方法能够有效将典型文化元素以语义符号的形式融入地铁列车的外观设计,有助于提升设计方 案的地域文化特征。     

Genetic algorithm for control design of biped locomotion

Dynamic biped walking is a difficult control problem. The design involves that of the controller as well as the gait. A typical design procedure involves tedious analysis, careful planning, and testing. The procedure is time consuming and the analysis is often based on some linearized model. Selection of control parameters and nominal trajectory determines the quality of control and in typical designs, some or all of the parameters are selected intuitively. The result is often not the best. If some special goal (such as to walk as fast as possible) is desirable, the design may become even harder. While the analytical approach is not easy, one possible alternative is to obtain the optimal or near-optimal design through parameter search. This study explores this approach. The design of the biped controller and gait is formulated as a parameter search problem, and a genetic algorithm is applied to help obtain the optimal design. Designs to achieve different goals, such as being able to walk on an inclined surface, walk at a high speed, or walk with a specified step size have been evolved with the use of the genetic algorithm. Simulation results show that the genetic algorithm (GA) is capable of finding good solutions. © 1997 John Wiley & Sons, Inc.     

Fuzzy multicriterion design using immune network simulation

Structural optimization problems have been traditionally formulated in terms of crisply defined objective and constraint functions. With a shift in application focus towards more practical problems, there is a need to incorporate fuzzy or noncrisp information into an optimization problem statement. Such practical design problems often deal with the allocation of resources to satisfy multiple, and frequently conflicting design objectives. The present paper deals with a genetic algorithm based optimization procedure for solving multicriterion design problems where the objective or constraint functions may not be crisply defined. The approach uses a genetic algorithm based simulation of the biological immune system to solve the multicriterion design problem; fuzzy set theory is adopted to incorporate imprecisely defined information into the problem statement. A notable strength of the proposed approach is its ability to generate a Pareto-Edgeworth front of compromise solutions in a single execution of the GA. Received May 8, 2000     

Glass container production scheduling through hybrid multi-population based evolutionary algorithm

Driven by a real-world application in the capital-intensive glass container industry, this paper provides the design of a new hybrid evolutionary algorithm to tackle the short-term production planning and scheduling problem. The challenge consists of sizing and scheduling the lots in the most cost-effective manner on a set of parallel molding machines that are fed by a furnace that melts the glass. The solution procedure combines a multi-population hierarchically structured genetic algorithm (GA) with a simulated annealing (SA), and a tailor-made heuristic named cavity heuristic (CH). The SA is applied to intensify the search for solutions in the neighborhood of the best individuals found by the GA, while the CH determines quickly values for a relevant decision variable of the problem: the processing speed of each machine. The results indicate the superior performance of the proposed approach against a state-of-the-art commercial solver, and compared to a non-hybridized multi-population GA.     

Identification of a human walking force model based on dynamic monitoring data from pedestrian bridges

A general investigation procedure for the vibration serviceability of pedestrian bridges is accomplished by comparing the dynamic response of structures to vibration effects on serviceability limiting states. The purposes of this study were to investigate the dynamic response characteristics of pedestrian bridges and to develop a human walking force model to assist in the development and design of pedestrian bridges. Human walking force parameters were identified by a genetic algorithm (GA) from experimental forced vibration data. The results of the dynamic response obtained by the GA were in agreement with the experimental results. Therefore, the GA system was useful in the identification of pedestrian walking forces, and from the experimental and calculated results, it is considered that the walking force model identified by the GA is substantially accurate.     

Dynamic contact/impact problems,energy conservation,and planetary gear trains

The paper is a continuation of the work presented in [Comp. Meth. Appl. Mech. Eng. 190 (2001) 1903], aimed at modeling of a general class of dynamic contact/impact problems for systems of rigid bodies. The contact is assumed to be frictionless, and the main challenge is to model the exchange between the kinetic and elastic energies in the system. This calls for a discretization scheme that conserves linear and angular momentum and, first of all, the total energy at the discrete level. Such a scheme has been presented in [Comp. Meth. Appl. Mech. Eng. 190 (2001) 1903], and in this work we complement it with a very general treatment of the no-penetration condition for two elastic bodies. The approach is based on the concept of the sign (Rvachev) function, and it provides a natural generalization of the classical point-to-line condition [Arch. Computat. Meth. Eng. 2 (1995) 1]. The work has been motivated with the modeling of planetary gear trains and has resulted in the first (to our best knowledge) two dimensional parallel finite element simulator for gear sets [Parallel finite element simulator of planetary gear trains, Ph.D. Dissertation, The University of Texas, 2001].