Automatic Design Method Research Articles

Structural Parameters Design Optimization of the Geared Reluctance Motor

The structural-parameter design principle and the autmatic optimization method of the geared reluctance motor(GRM) are studied,on the basis of the GRM parameterized model given in reference .By study on the average-torque change-trend according with structural parameters,design principles of parameters are put forward.To reduce artificial design work and search the global advantages,the automatic optimization design method of the GRM based on the generic algorithm is proposed.The constraint conditions of parameters and the mutual constraints between parameters are disgussed.The strength constraint,tooth-shape constraint and the teeth-number rounding of the cycloid gear are studied in detail.Then a prototype is optimized by the algorithm,which make the average torque increased by 35%.At last,the torque characteristic of the optimized GRM is veryfied by the finite element method(FEM).The results show that the error between the optimized theoretical torque and the FEM validation value is less than 3%,which proves correctness of the optimization algorithm.

An Efficient High-Frequency Linear RF Amplifier Synthesis Method Based on Evolutionary Computation and Machine Learning Techniques

Existing radio frequency (RF) integrated circuit (IC) design automation methods focus on the synthesis of circuits at a few GHz, typically less than 10 GHz. That framework is difficult to apply to RF IC synthesis at mm-wave frequencies (e.g., 60-100 GHz). In this paper, a new method, called efficient machine learning-based differential evolution, is presented for mm-wave frequency linear RF amplifier synthesis. By using electromagnetic (EM) simulations to evaluate the key passive components, the evaluation of circuit performances is accurate and solves the limitations of parasitic-included equivalent circuit models and predefined layout templates used in the existing synthesis framework. A decomposition method separates the design variables that require expensive EM simulations and the variables that only need cheap circuit simulations. Hence, a low- dimensional expensive optimization problem is generated. By the newly proposed core algorithm integrating adaptive population generation, naive Bayes classification, Gaussian process and differential evolution, the generated low-dimensional expensive optimization problem can be solved efficiently (by the online surrogate model), and global search (by evolutionary computation) can be achieved. A 100 GHz three-stage differential amplifier is synthesized in a 90 nm CMOS technology. The power gain reaches 10 dB with more than 20 GHz bandwidth. The synthesis costs only 25 h, having a comparable result and a nine times speed enhancement compared with directly using the EM simulator and global optimization algorithms.

Importance Driven Automatic Color Design for Direct Volume Rendering

AbstractThis paper introduces an automatic color design method that is driven by an importance function of the objects within a volumetric dataset. Our method allows the user to intuitively modify the object classification and the importance distribution function in the 2D rendered image. It automatically computes the transfer function, especially the color distribution, to convey the importance of the objects. In our approach, the importance of an object is represented as the attentiveness of a color. In addition, we preserve the color harmony in the rendered image in order to provide a visually pleasing result. In this paper, we propose a set of computational measurements to compute the color attentiveness and color harmony. Our color assignment algorithm supports arbitrary‐dimensional transfer functions and obtains interactive frame rates. Our method involves three color spaces, namely Coloroid system, CIE LChuv, and Adobe RGB color space. It calculates the color attentiveness in CIE LChuv space, and the color harmony in Coloroid system. It, then, assigns the transfer function in a dual space of Adobe RGB space and renders the resulting image in Adobe RGB space. We conducted a detailed user study, which proves that our method successfully conveys the importance distributions. Our contribution in this paper is not only our importance driven approach, but also our computational measurements and our color assignment algorithm.

System analysis of total water systems for water minimization

System-wide analysis of water systems to minimize water use in process industries has been carried out when charges for effluents from the process are simultaneously considered with cost of freshwater intake and in-house water treatment in the design of water and effluent systems. It has been demonstrated that the degree of wastewater regeneration and recycling is heavily dependent on the charges associated wastewater effluent. The reusability of water and its techno-economic impacts are examined with both a graphic-based manual technique and an automated design method using mathematical optimization, with which conceptual insights are sought in a systematic manner to evaluate different integrated options including water reuse, regeneration and recycling. For the optimization model, new solution strategy has been proposed for solving the MINLP problem of total water systems which carries out rigorous economic trade-offs existed in an integrated water network, together with wastewater charges.

Research on Automatic Design of Extendable TrussBased on CAD Software

This paper provides a method of automatic design for extendable truss based on CAD software. The method mainly consists of parametrical design, automatic assembly, interference checking and extraction of model properties. With Visual C + + as programming language, secondary development was done on automatic assembly and other related modules of CAD software, which can achieve parametrically automatic assembly, interference checking and automatically extracting properties of extendable truss model. Thus, this method can guide the design staff performing program design, improve the correctness and accuracy of design, shorten the design cycle of extendable truss and also has reference value on rapid design and development for other products.

An Automated Design Method for Active Trailer Steering Systems of Articulated Heavy Vehicles

An important design decision for active trailer steering (ATS) systems for articulated heavy vehicles (AHVs) is the trade-off between maneuverability and lateral stability. This paper presents an automated design method for this trade-off. The proposed method has the following features: (1) a design framework for bilevel optimization of ATS systems is formulated; (2) design variables of ATS controllers and trailers are optimized simultaneously; (3) two controllers are designed for the ATS system for improving stability and enhancing maneuverability, respectively; and (4) a driver model is introduced in the virtual vehicle simulation for closed-loop testing maneuvers. The design framework allows automation of vehicle modeling, controller construction, performance evaluation, and design variable selection, and all required design processes are implemented in a single loop. The proposed method is compared to a previously published two-loop design method, showing that the new approach can effectively identify desired variables and predict performance envelopes.

Adapting computational optimization concepts from aeronautics to nuclear fusion reactor design

Even on the most powerful supercomputers available today, computational nuclear fusion reactor divertor design is extremely CPU demanding, not least due to the large number of design variables and the hybrid micro-macro character of the flows. Therefore, automated design methods based on optimization can greatly assist current reactor design studies. Over the past decades, ≥DGMRLQWPHWKRGV¥�IRUVKDSHRSWLPL)DWLRQ� have proven their virtue in the field of aerodynamics. Applications include drag reduction for wing and wing-body configurations. Here we demonstrate that also for divertor design, these optimization methods have a large potential. Specifically, we apply the continuous adjoint method to the optimization of the divertor geometry in a 2D poloidal cross section of an axisymmetric tokamak device (as, e.g., JET and ITER), using a simplified model for the plasma edge. The design objective is to spread the target material heat load as much as possible by controlling the shape of the divertor, while maintaining the full helium ash removal capabilities of the vacuum pumping system.

Optimization of Water Systems with the Consideration of Pressure Drop and Pumping

Novel automated design method has been developed to consider impacts of pressure drop and pumping arrangement in the water network in which water reuse is exploited to reduce freshwater consumption in process industries. A superstructure-based optimization framework has been developed to systematically consider all the key design issues simultaneously, including flow rate constraints, pressure-drop constraints, and other operational constraints, as well as to fully accommodate rigorous economic trade-off between freshwater cost, piping cost, and pumping cost. The proposed optimization study enables the identification of the optimal distribution of water within the network, together with the most appropriate location and capacity of pumps required for water systems. A robust and reliable solution strategy has been developed to effectively deal with computational difficulties associated with solving a mixed-integer nonlinear programming problem, with the aid of the effective application of physical insights gained from conceptual understanding of the design problem. The network complexity has been readily controlled by imposing design constraints in the optimization. Examples have been provided to prove the effectiveness of the design method developed in this paper and to demonstrate the importance of considering pressure drop constraints in practice.

Integrated water networks optimisation under uncertainty

An automated design method for the water networks under uncertain process conditions has been developed. To deal with the uncertainty problem, the installation of buffer tank and the installation of supplementing pipelines are systematically considered in the design of water networks. The cost-effective and feasible distribution and reuse of water within the network is identified from the superstructure-based optimisation model, with which all the operational constraints and fluctuating operating characteristics for water-using operations are fully and simultaneously reflected. The optimisation framework provides rigorous economic evaluation of the network through trade-off between operating and capital costs under uncertainty. The conceptual insight related to the design of water networks is incorporated in developing a reliable solution strategy which can effectively deal with the difficulty in solving the mixed-integer nonlinear programming problem. Case studies are given to validate the proposed model and demonstrate the importance of considering uncertain process conditions in the design and optimisation of water networks.

Automatic optimization design of Gaussian beam shaping system by using ZEMAX software

This paper studies the method of automatic optimization design of Gaussian beam shaping. Firstly, the principle of Gaussian beam shaping was studied theoretically and the flattened Lorentzian function (FL) is chosen as the distribution of flattened beam. The mapping function of arbitrary ray in incident plane and image plane was deduced based on the law of conservation of energy. And then, according to the characteristics of this system, Zemax programming language (ZPL) was used to compile ZPL macro orders to optimize the Gaussian beam shaping automatically. Finally, optical analyzing software was used to test the aspheric lens system. The method is not only simple but also practical with high efficient energy conversion and significant engineering application value.

Automatic Design of Digital Synthetic Gene Circuits

De novo computational design of synthetic gene circuits that achieve well-defined target functions is a hard task. Existing, brute-force approaches run optimization algorithms on the structure and on the kinetic parameter values of the network. However, more direct rational methods for automatic circuit design are lacking. Focusing on digital synthetic gene circuits, we developed a methodology and a corresponding tool for in silico automatic design. For a given truth table that specifies a circuit's input–output relations, our algorithm generates and ranks several possible circuit schemes without the need for any optimization. Logic behavior is reproduced by the action of regulatory factors and chemicals on the promoters and on the ribosome binding sites of biological Boolean gates. Simulations of circuits with up to four inputs show a faithful and unequivocal truth table representation, even under parametric perturbations and stochastic noise. A comparison with already implemented circuits, in addition, reveals the potential for simpler designs with the same function. Therefore, we expect the method to help both in devising new circuits and in simplifying existing solutions.

2107 外乱を考慮したHDL記述の制御器の機能創発(OS10-2 創発の手法と機能創出,OS10 創発性と多様性の設計)

In this paper, a method of automatic controller design for electronic control systems considering for disturbance is described. In order to automate the design of the electronic controller, an evolutionary computation is applied. First, the framework for applying the genetic algorithm to the automation of controller design is described. In particular, the coding of a chromosome is shown in detail. Then, how to make a fitness function is represented, with an inverted pendulum as an example, and the controller of the inverted pendulum is developed automatically using our proposed framework. Finally, an evolutionary simulation is performed to confirm our framework.

Automated Design of an FDI-System for the Wind Turbine Benchmark

AbstractPresent paper proposes an FDI-system for the wind turbine benchmark designed by application of a generic automated design method, in which the number of required human decisions and assumptions are minimized. No specific adaptation of the method for the wind turbine benchmark is needed, and the number of parameter choices is small. The method contains in essence three steps: generation of potential residual generators; residual generator selection; and diagnostic test construction. The second and third step are based on novel ideas developed in this paper; a greedy selection algorithm for the second step, and a methodology based on the Kullback-Leibler divergence for the third step. The proposed FDI-system performs well in spite of no specific adaptation or tuning to the benchmark. All faults in the pre-defined test sequence can be detected and all faults, except a double fault, can also be isolated shortly thereafter. In addition, there are no false or missed detections.

Automatic Design Method of Wind Turbine Tower and it’s Application

In order to solve the engineering application problems of parametric rapidly in design of wind turbine tower, an automatic design method of wind turbine tower is put forward first, and the automatic design model was built through analyzing the key parameters and parameters’ calculation relation in different cases: same taper tower design and variable taper tower design. The key parameters, height, diameter and wall thickness of the tower, are mainly considered. Then, an automatic design system of the wind turbine tower is developed and realized according to the model. Finally, the system effectiveness is verified through taking a wind turbine for example. The results show that the system can enhance the design efficiency and shorten the cycle times at the same time.

Reversible Logic Synthesis-Oriented Multi-Objective Automatic Design Method Based on Evolutionary Design Techniques

This paper applies evolutionary design techniques to the reversible logic synthesis, and proposes a reversible logic synthesis-oriented multi-objective automatic design method based on evolutionary design techniques. Firstly, build a gate-level array model of reversible logic circuits (RLC) in order to model the synthesis problems as ones of constrained multi-objective optimizations. Then, encode the candidate RLC to a set of binary evolutionary individuals which are solved by the specialized Pareto-optimal multi-objective evolutionary algorithm. In addition, adopt “pre-bit priority” mechanism to repair infeasible individuals and adopt the rule-based local transformation method to simple the redundant RLC. The results of synthesis experiments demonstrate that the proposed method is feasible and effective, and can automatically synthesize the better RLC.

Multi-Objective Aerodynamic Optimization of Axial Turbine Blades Using a Novel Multilevel Genetic Algorithm

In this paper, a new multiploid genetic optimization method handling surrogate models of the CFD solutions is presented and applied for a multi-objective turbine blade aerodynamic optimization problem. A fast, efficient, robust, and automated design method is developed to aerodynamically optimize 3D gas turbine blades. The design objectives are selected as maximizing the adiabatic efficiency and torque so as to reduce the weight, size, and cost of the gas turbine engine. A 3D steady Reynolds averaged Navier–Stokes solver is coupled with an automated unstructured grid generation tool. The solver is verified using two well-known test cases. The blade geometry is modeled by 36 design variables plus the number of blade variables in a row. Fine and coarse grid solutions are respected as high- and low-fidelity models, respectively. One of the test cases is selected as the baseline and is modified by the design process. It was found that the multiploid multi-objective genetic algorithm successfully accelerates the optimization and prevents the convergence with local optimums.

Simultaneous design of the sensory morphology and controller of mobile robots

AbstractThis paper proposes a method for automatic design of the sensory morphology of a mobile robot. The proposed method employs two types of adaptations, ontogenetic and phylogenetic, to optimize the sensory morphology of the robot. In ontogenetic adaptation, reinforcement learning searches for the optimal policy, which is highly dependent on the sensory morphology. In phylogenetic adaptation, a genetic algorithm is used to select morphologies with which the robot can learn tasks faster. Our proposed method was applied to the design of the sensory morphology of a line‐following robot. We performed simulation experiments to compare the design solution with a hand‐coded robot. The results of the experiments revealed that our robot outperformed the hand‐coded robot in terms of the following accuracy and learning speed, although our robot had fewer sensors than the hand‐coded one. We also built a physical robot using the design solution. The experimental results revealed that this physical robot used its morphology effectively and outperformed the hand‐coded robot. © 2010 Wiley Periodicals, Inc. Electr Eng Jpn, 172(1): 48–57, 2010; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20965

Model-Based Design of Scanning Input Communication Aids: State of the Art and Research Issues

Scanning input communication aids are used by people with speech and motor disabilities. These aids are typically in the form of on-screen matrix of alphanumeric characters. To compose communicative messages, disabled users select characters from the matrix with scanning input methods. The problem faced by designers of such systems is to choose the best design from a large number of design alternatives. The problem may be alleviated by automated design methods based on user models. We performed a critical analysis of the related work and found that the present user models do not consider several factors that are important for user-system interaction. These include (a) scanning interaction, (b) visual search, and (c) user errors. In this paper, we present review and analysis of existing models and suggest directions for future research.

Design automation and optimization of assembly sequences for complex mechanical systems

Assembly sequence design for a mechanical system can have significant impact on manufacturing cost and product quality. Traditionally, such a design process is largely based on experience and best practices, often ineffective and non-optimal as the system becomes complex. This paper proposes a new, systematic method for automatic assembly sequence design and optimization. Key elements include assembly modeling, sequence planning, locating scheme optimization, dimensional quality evaluation, and optimization. First, a directed graph and an assembly matrix are employed to describe the assembly relation of a system. Then, the feasible assembly sequences are generated through layered subassembly detection of adjacency matrices, filtered by engineering constraints. To evaluate quickly the assembly quality and compare the influences of different locating point schemes, a linear 3D variation propagation analysis model with deterministic locating principle is introduced. The optimal locating scheme is then selected using a genetic algorithm with the least variation propagation. Finally, the assembly dimensional quality for different sequences is evaluated and the optimal assembly sequences are achieved through genetic algorithms. A case of automotive body side assembly is presented to illustrate the whole methodology.

Automated Procedure for Roll Pass Design

The aim of this work has been to develop an automatic roll pass design method, capable of minimizing the number of roll passes. The adoption of artificial intelligence technologies, particularly expert systems, and a hybrid model for the surface profile evaluation of rolled bars, has allowed us to model the search for the minimal sequence with a tree path search. This approach permitted a geometrical optimization of roll passes while allowing automation of the roll pass design process. Moreover, the heuristic nature of the inferential engine contributes a great deal toward reducing search time, thus allowing such a system to be employed for industrial purposes. Finally, this new approach was compared with other recently developed automatic systems to validate and measure possible improvements among them.