Algorithmic Mechanism Design of Evolutionary Computation.
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.
Differential evolution and simulated annealing algorithms for mechanical systems design
Directory of Open Access Journals (Sweden)
H. Saruhan
2014-09-01
Full Text Available In this study, nature inspired algorithms – the Differential Evolution (DE and the Simulated Annealing (SA – are utilized to seek a global optimum solution for ball bearings link system assembly weight with constraints and mixed design variables. The Genetic Algorithm (GA and the Evolution Strategy (ES will be a reference for the examination and validation of the DE and the SA. The main purpose is to minimize the weight of an assembly system composed of a shaft and two ball bearings. Ball bearings link system is used extensively in many machinery applications. Among mechanical systems, designers pay great attention to the ball bearings link system because of its significant industrial importance. The problem is complex and a time consuming process due to mixed design variables and inequality constraints imposed on the objective function. The results showed that the DE and the SA performed and obtained convergence reliability on the global optimum solution. So the contribution of the DE and the SA application to the mechanical system design can be very useful in many real-world mechanical system design problems. Beside, the comparison confirms the effectiveness and the superiority of the DE over the others algorithms – the SA, the GA, and the ES – in terms of solution quality. The ball bearings link system assembly weight of 634,099 gr was obtained using the DE while 671,616 gr, 728213.8 gr, and 729445.5 gr were obtained using the SA, the ES, and the GA respectively.
Social Welfare in Algorithmic Mechanism Design Without Money
DEFF Research Database (Denmark)
Filos-Ratsikas, Aris
Social choice theory is concerned with collective decision making under different, possibly contrasting opinions and has been part of the core of society since ancient times. The goal is to implement some socially desired objective while at the same time accounting for the fact that people will act...... strategically, in order to manipulate the outcomes in their favor. In this thesis, we consider the well-known objective of social welfare, i.e. the sum of individual utilities as the social objective and following the agenda of algorithmic mechanism design, we study how well our objectives can be approximated...
Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm
International Nuclear Information System (INIS)
Chaudhary, Kailash; Chaudhary, Himanshu
2015-01-01
In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).
Optimal design of planar slider-crank mechanism using teaching-learning-based optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Chaudhary, Kailash; Chaudhary, Himanshu [Malaviya National Institute of Technology, Jaipur (Malaysia)
2015-11-15
In this paper, a two stage optimization technique is presented for optimum design of planar slider-crank mechanism. The slider crank mechanism needs to be dynamically balanced to reduce vibrations and noise in the engine and to improve the vehicle performance. For dynamic balancing, minimization of the shaking force and the shaking moment is achieved by finding optimum mass distribution of crank and connecting rod using the equipemental system of point-masses in the first stage of the optimization. In the second stage, their shapes are synthesized systematically by closed parametric curve, i.e., cubic B-spline curve corresponding to the optimum inertial parameters found in the first stage. The multi-objective optimization problem to minimize both the shaking force and the shaking moment is solved using Teaching-learning-based optimization algorithm (TLBO) and its computational performance is compared with Genetic algorithm (GA).
Linac design algorithm with symmetric segments
International Nuclear Information System (INIS)
Takeda, Harunori; Young, L.M.; Nath, S.; Billen, J.H.; Stovall, J.E.
1996-01-01
The cell lengths in linacs of traditional design are typically graded as a function of particle velocity. By making groups of cells and individual cells symmetric in both the CCDTL AND CCL, the cavity design as well as mechanical design and fabrication is simplified without compromising the performance. We have implemented a design algorithm in the PARMILA code in which cells and multi-cavity segments are made symmetric, significantly reducing the number of unique components. Using the symmetric algorithm, a sample linac design was generated and its performance compared with a similar one of conventional design
Mechanism design visual and programmable approaches
Russell, Kevin; Sodhi, Raj S
2013-01-01
"… the book provides a lot of MATLAB® and SimMechanics examples. Students could benefit from the experience of solving the complex spatial synthesis problems using computer tools. The mathematics software tools are very efficient to do the displacement analysis, too."-Wen-Tzong Lee, National Pingtung University of Science and Technology, Neipu, Taiwan"The book covers a vast range of mechanism kinematics and design. The algorithm covering the topics presented is useful for mechanism design in class and homework assignments. The book provides an alternative modern tool, as compared to kinematics analysis methods based on Fortran or QuickBasic algorithms, covering all topics for mechanism design."-Thomas G. Chondros, University of Patras, Greece"… well elaborated for students at their first approach to the subject of mechanism design and its computation with MATLAB®."-Marco Ceccarelli, University of Cassino and South Latium, Italy.
Algorithme intelligent d'optimisation d'un design structurel de grande envergure
Dominique, Stephane
The implementation of an automated decision support system in the field of design and structural optimisation can give a significant advantage to any industry working on mechanical designs. Indeed, by providing solution ideas to a designer or by upgrading existing design solutions while the designer is not at work, the system may reduce the project cycle time, or allow more time to produce a better design. This thesis presents a new approach to automate a design process based on Case-Based Reasoning (CBR), in combination with a new genetic algorithm named Genetic Algorithm with Territorial core Evolution (GATE). This approach was developed in order to reduce the operating cost of the process. However, as the system implementation cost is quite expensive, the approach is better suited for large scale design problem, and particularly for design problems that the designer plans to solve for many different specification sets. First, the CBR process uses a databank filled with every known solution to similar design problems. Then, the closest solutions to the current problem in term of specifications are selected. After this, during the adaptation phase, an artificial neural network (ANN) interpolates amongst known solutions to produce an additional solution to the current problem using the current specifications as inputs. Each solution produced and selected by the CBR is then used to initialize the population of an island of the genetic algorithm. The algorithm will optimise the solution further during the refinement phase. Using progressive refinement, the algorithm starts using only the most important variables for the problem. Then, as the optimisation progress, the remaining variables are gradually introduced, layer by layer. The genetic algorithm that is used is a new algorithm specifically created during this thesis to solve optimisation problems from the field of mechanical device structural design. The algorithm is named GATE, and is essentially a real number
Directory of Open Access Journals (Sweden)
Dazhi Jiang
2015-01-01
Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.
Multi-objective optimum design of fast tool servo based on improved differential evolution algorithm
International Nuclear Information System (INIS)
Zhu, Zhiwei; Zhou, Xiaoqin; Liu, Qiang; Zhao, Shaoxin
2011-01-01
The flexure-based mechanism is a promising realization of fast tool servo (FTS), and the optimum determination of flexure hinge parameters is one of the most important elements in the FTS design. This paper presents a multi-objective optimization approach to optimizing the dimension and position parameters of the flexure-based mechanism, which is based on the improved differential evolution algorithm embedding chaos and nonlinear simulated anneal algorithm. The results of optimum design show that the proposed algorithm has excellent performance and a well-balanced compromise is made between two conflicting objectives, the stroke and natural frequency of the FTS mechanism. The validation tests based on finite element analysis (FEA) show good agreement with the results obtained by using the proposed theoretical algorithm of this paper. Finally, a series of experimental tests are conducted to validate the design process and assess the performance of the FTS mechanism. The designed FTS reaches up to a stroke of 10.25 μm with at least 2 kHz bandwidth. Both of the FEA and experimental results demonstrate that the parameters of the flexure-based mechanism determined by the proposed approaches can achieve the specified performance and the proposed approach is suitable for the optimum design of FTS mechanism and of excellent performances
Toward human-centered algorithm design
Directory of Open Access Journals (Sweden)
Eric PS Baumer
2017-07-01
Full Text Available As algorithms pervade numerous facets of daily life, they are incorporated into systems for increasingly diverse purposes. These systems’ results are often interpreted differently by the designers who created them than by the lay persons who interact with them. This paper offers a proposal for human-centered algorithm design, which incorporates human and social interpretations into the design process for algorithmically based systems. It articulates three specific strategies for doing so: theoretical, participatory, and speculative. Drawing on the author’s work designing and deploying multiple related systems, the paper provides a detailed example of using a theoretical approach. It also discusses findings pertinent to participatory and speculative design approaches. The paper addresses both strengths and challenges for each strategy in helping to center the process of designing algorithmically based systems around humans.
Topology optimum design of compliant mechanisms using modified ant colony optimization
Energy Technology Data Exchange (ETDEWEB)
Yoo, Kwang Seon; Han, Seog Young [Hanyang University, Seoul (Korea, Republic of)
2015-08-15
A Modified ant colony optimization (MACO) algorithm was suggested for topology optimal design of compliant mechanisms since standard ACO cannot provide an appropriate optimal topology. In order to improve computational efficiency and suitability of standard ACO algorithm in topology optimization for compliant mechanisms, a continuous variable, called the 'Element contribution significance (ECS),'is employed, which serves to replace the positions of ants in the standard ACO algorithm, and assess the importance of each element in the optimization process. MACO algorithm was applied to topology optimizations of both linear and geometrically nonlinear compliant mechanisms using three kinds of objective functions, and optimized topologies were compared each other. From the comparisons, it was concluded that MACO algorithm can effectively be applied to topology optimizations of linear and geometrically nonlinear compliant mechanisms, and the ratio of Mutual potential energy (MPE) to Strain energy (SE) type of objective function is the best for topology optimal design of compliant mechanisms.
Algorithms in combinatorial design theory
Colbourn, CJ
1985-01-01
The scope of the volume includes all algorithmic and computational aspects of research on combinatorial designs. Algorithmic aspects include generation, isomorphism and analysis techniques - both heuristic methods used in practice, and the computational complexity of these operations. The scope within design theory includes all aspects of block designs, Latin squares and their variants, pairwise balanced designs and projective planes and related geometries.
Directory of Open Access Journals (Sweden)
Betania Hernández-Ocaña
2016-01-01
Full Text Available This paper presents two-swim operators to be added to the chemotaxis process of the modified bacterial foraging optimization algorithm to solve three instances of the synthesis of four-bar planar mechanisms. One swim favors exploration while the second one promotes fine movements in the neighborhood of each bacterium. The combined effect of the new operators looks to increase the production of better solutions during the search. As a consequence, the ability of the algorithm to escape from local optimum solutions is enhanced. The algorithm is tested through four experiments and its results are compared against two BFOA-based algorithms and also against a differential evolution algorithm designed for mechanical design problems. The overall results indicate that the proposed algorithm outperforms other BFOA-based approaches and finds highly competitive mechanisms, with a single set of parameter values and with less evaluations in the first synthesis problem, with respect to those mechanisms obtained by the differential evolution algorithm, which needed a parameter fine-tuning process for each optimization problem.
Multi-machine power system stabilizers design using chaotic optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Shayeghi, H., E-mail: hshayeghi@gmail.co [Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power System Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Jalilzadeh, S.; Safari, A. [Technical Engineering Department, Zanjan University, Zanjan (Iran, Islamic Republic of)
2010-07-15
In this paper, a multiobjective design of the multi-machine power system stabilizers (PSSs) using chaotic optimization algorithm (COA) is proposed. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from the local optimum, is a promising tool for the engineering applications. The PSSs parameters tuning problem is converted to an optimization problem which is solved by a chaotic optimization algorithm based on Lozi map. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization problem introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. Two different objective functions are proposed in this study for the PSSs design problem. The first objective function is the eigenvalues based comprising the damping factor, and the damping ratio of the lightly damped electro-mechanical modes, while the second is the time domain-based multi-objective function. The robustness of the proposed COA-based PSSs (COAPSS) is verified on a multi-machine power system under different operating conditions and disturbances. The results of the proposed COAPSS are demonstrated through eigenvalue analysis, nonlinear time-domain simulation and some performance indices. In addition, the potential and superiority of the proposed method over the classical approach and genetic algorithm is demonstrated.
8. Algorithm Design Techniques
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 8. Algorithms - Algorithm Design Techniques. R K Shyamasundar. Series Article Volume 2 ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...
Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P
2010-10-30
Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy. Copyright © 2010 Elsevier B.V. All rights reserved.
Research on application of complex-genetic algorithm in nuclear component optimal design
International Nuclear Information System (INIS)
He Shijing; Yan Changqi; Wang Jianjun; Wang Meng
2010-01-01
Complex algorithm is one of the most commonly used methods in the mechanical design optimization, such as the optimization of nuclear component. An improved method,complex-genetic algorithm(CGA), is developed based on traditional complex algorithm(TCA), in which the disadvantages of TCA have been overcome. An optimal calculation,which represents the pressurizer, is carried out in order to analyze the optimization capability of CGA. The results show that CGA has better optimizing performance than TCA. (authors)
Reactor controller design using genetic algorithms with simulated annealing
International Nuclear Information System (INIS)
Erkan, K.; Buetuen, E.
2000-01-01
This chapter presents a digital control system for ITU TRIGA Mark-II reactor using genetic algorithms with simulated annealing. The basic principles of genetic algorithms for problem solving are inspired by the mechanism of natural selection. Natural selection is a biological process in which stronger individuals are likely to be winners in a competing environment. Genetic algorithms use a direct analogy of natural evolution. Genetic algorithms are global search techniques for optimisation but they are poor at hill-climbing. Simulated annealing has the ability of probabilistic hill-climbing. Thus, the two techniques are combined here to get a fine-tuned algorithm that yields a faster convergence and a more accurate search by introducing a new mutation operator like simulated annealing or an adaptive cooling schedule. In control system design, there are currently no systematic approaches to choose the controller parameters to obtain the desired performance. The controller parameters are usually determined by test and error with simulation and experimental analysis. Genetic algorithm is used automatically and efficiently searching for a set of controller parameters for better performance. (orig.)
Optimal synthesis of four-bar steering mechanism using AIS and genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Ettefagh, Mir Mohammad; Javash, Morteza Saeidi [University of Tabriz, Tabriz (Iran, Islamic Republic of)
2014-06-15
Synthesis of four-bar Ackermann steering mechanism was considered as an optimization problem for generating the best function between input and output links. The steering mechanism was designed through two heuristic optimization methods, namely, artificial immune system (AIS) algorithm and genetic algorithm (GA). The optimization was implemented using the two methods, length was selected as optimization parameter in the first method, whereas precision point distribution was considered in the second method. Two of the links in the first method had the same length to achieve a symmetric mechanism; one of these lengths was considered as optimization parameter. Five precision points were considered in the precision point distribution method, one of which was in the straight line condition, whereas the others were symmetric. The obtained results showed that the AIS algorithm can generate the closest function to the desired function in the first method. By contrast, GA can generate the closest function to the desired function with the least error in the second method.
Analog Circuit Design Optimization Based on Evolutionary Algorithms
Directory of Open Access Journals (Sweden)
Mansour Barari
2014-01-01
Full Text Available This paper investigates an evolutionary-based designing system for automated sizing of analog integrated circuits (ICs. Two evolutionary algorithms, genetic algorithm and PSO (Parswal particle swarm optimization algorithm, are proposed to design analog ICs with practical user-defined specifications. On the basis of the combination of HSPICE and MATLAB, the system links circuit performances, evaluated through specific electrical simulation, to the optimization system in the MATLAB environment, for the selected topology. The system has been tested by typical and hard-to-design cases, such as complex analog blocks with stringent design requirements. The results show that the design specifications are closely met. Comparisons with available methods like genetic algorithms show that the proposed algorithm offers important advantages in terms of optimization quality and robustness. Moreover, the algorithm is shown to be efficient.
Automatic Circuit Design and Optimization Using Modified PSO Algorithm
Directory of Open Access Journals (Sweden)
Subhash Patel
2016-04-01
Full Text Available In this work, we have proposed modified PSO algorithm based optimizer for automatic circuit design. The performance of the modified PSO algorithm is compared with two other evolutionary algorithms namely ABC algorithm and standard PSO algorithm by designing two stage CMOS operational amplifier and bulk driven OTA in 130nm technology. The results show the robustness of the proposed algorithm. With modified PSO algorithm, the average design error for two stage op-amp is only 0.054% in contrast to 3.04% for standard PSO algorithm and 5.45% for ABC algorithm. For bulk driven OTA, average design error is 1.32% with MPSO compared to 4.70% with ABC algorithm and 5.63% with standard PSO algorithm.
Algebraic Algorithm Design and Local Search
National Research Council Canada - National Science Library
Graham, Robert
1996-01-01
.... Algebraic techniques have been applied successfully to algorithm synthesis by the use of algorithm theories and design tactics, an approach pioneered in the Kestrel Interactive Development System (KIDS...
Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm
Directory of Open Access Journals (Sweden)
Feifei Dong
2014-01-01
Full Text Available Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC. The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Genetic Algorithms in Wind Turbine Airfoil Design
Energy Technology Data Exchange (ETDEWEB)
Grasso, F. [ECN Wind Energy, Petten (Netherlands); Bizzarrini, N.; Coiro, D.P. [Department of Aerospace Engineering, University of Napoli ' Federico II' , Napoli (Italy)
2011-03-15
One key element in the aerodynamic design of wind turbines is the use of specially tailored airfoils to increase the ratio of energy capture to the loading and thereby to reduce cost of energy. This work is focused on the design of a wind turbine airfoil by using numerical optimization. Firstly, the optimization approach is presented; a genetic algorithm is used, coupled with RFOIL solver and a composite Bezier geometrical parameterization. A particularly sensitive point is the choice and implementation of constraints; in order to formalize in the most complete and effective way the design requirements, the effects of activating specific constraints are discussed. A numerical example regarding the design of a high efficiency airfoil for the outer part of a blade by using genetic algorithms is illustrated and the results are compared with existing wind turbine airfoils. Finally a new hybrid design strategy is illustrated and discussed, in which the genetic algorithms are used at the beginning of the design process to explore a wide domain. Then, the gradient based algorithms are used in order to improve the first stage optimum.
Directory of Open Access Journals (Sweden)
B. Thamaraikannan
2014-01-01
Full Text Available This paper studies in detail the background and implementation of a teaching-learning based optimization (TLBO algorithm with differential operator for optimization task of a few mechanical components, which are essential for most of the mechanical engineering applications. Like most of the other heuristic techniques, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. A differential operator is incorporated into the TLBO for effective search of better solutions. To validate the effectiveness of the proposed method, three typical optimization problems are considered in this research: firstly, to optimize the weight in a belt-pulley drive, secondly, to optimize the volume in a closed coil helical spring, and finally to optimize the weight in a hollow shaft. have been demonstrated. Simulation result on the optimization (mechanical components problems reveals the ability of the proposed methodology to find better optimal solutions compared to other optimization algorithms.
Mechanical Design Optimization Using Advanced Optimization Techniques
Rao, R Venkata
2012-01-01
Mechanical design includes an optimization process in which designers always consider objectives such as strength, deflection, weight, wear, corrosion, etc. depending on the requirements. However, design optimization for a complete mechanical assembly leads to a complicated objective function with a large number of design variables. It is a good practice to apply optimization techniques for individual components or intermediate assemblies than a complete assembly. Analytical or numerical methods for calculating the extreme values of a function may perform well in many practical cases, but may fail in more complex design situations. In real design problems, the number of design parameters can be very large and their influence on the value to be optimized (the goal function) can be very complicated, having nonlinear character. In these complex cases, advanced optimization algorithms offer solutions to the problems, because they find a solution near to the global optimum within reasonable time and computational ...
Genetic algorithms applied to nuclear reactor design optimization
International Nuclear Information System (INIS)
Pereira, C.M.N.A.; Schirru, R.; Martinez, A.S.
2000-01-01
A genetic algorithm is a powerful search technique that simulates natural evolution in order to fit a population of computational structures to the solution of an optimization problem. This technique presents several advantages over classical ones such as linear programming based techniques, often used in nuclear engineering optimization problems. However, genetic algorithms demand some extra computational cost. Nowadays, due to the fast computers available, the use of genetic algorithms has increased and its practical application has become a reality. In nuclear engineering there are many difficult optimization problems related to nuclear reactor design. Genetic algorithm is a suitable technique to face such kind of problems. This chapter presents applications of genetic algorithms for nuclear reactor core design optimization. A genetic algorithm has been designed to optimize the nuclear reactor cell parameters, such as array pitch, isotopic enrichment, dimensions and cells materials. Some advantages of this genetic algorithm implementation over a classical method based on linear programming are revealed through the application of both techniques to a simple optimization problem. In order to emphasize the suitability of genetic algorithms for design optimization, the technique was successfully applied to a more complex problem, where the classical method is not suitable. Results and comments about the applications are also presented. (orig.)
Hybrid real-code ant colony optimisation for constrained mechanical design
Pholdee, Nantiwat; Bureerat, Sujin
2016-01-01
This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.
Application of ant colony Algorithm and particle swarm optimization in architectural design
Song, Ziyi; Wu, Yunfa; Song, Jianhua
2018-02-01
By studying the development of ant colony algorithm and particle swarm algorithm, this paper expounds the core idea of the algorithm, explores the combination of algorithm and architectural design, sums up the application rules of intelligent algorithm in architectural design, and combines the characteristics of the two algorithms, obtains the research route and realization way of intelligent algorithm in architecture design. To establish algorithm rules to assist architectural design. Taking intelligent algorithm as the beginning of architectural design research, the authors provide the theory foundation of ant colony Algorithm and particle swarm algorithm in architectural design, popularize the application range of intelligent algorithm in architectural design, and provide a new idea for the architects.
Directory of Open Access Journals (Sweden)
Chen Zhou
2018-02-01
Full Text Available Two cylinders arranged symmetrically on a frame have become a major form of steering mechanism for articulated off-road vehicles (AORVs. However, the differences of stroke and arm lead to pressure fluctuation, vibration noise, and a waste of torque. In this paper, the differences of stroke and arm are reduced based on a genetic algorithm (GA. First, the mathematical model of the steering mechanism is put forward. Then, the difference of stroke and arm are optimized using a GA. Finally, a FW50GLwheel loader is used as an example to demonstrate the proposed GA-based optimization method, and its effectiveness is verified by means of automatic dynamic analysis of mechanical systems (ADAMS. The stroke difference of the steering hydraulic cylinders was reduced by 92% and the arm difference reached a decrease of 78% through GA optimization, in comparison with unoptimized structures. The simulation result shows that the steering mechanism optimized by GA behaved better than by previous methods.
Algorithm for designing smart factory Industry 4.0
Gurjanov, A. V.; Zakoldaev, D. A.; Shukalov, A. V.; Zharinov, I. O.
2018-03-01
The designing task of production division of the Industry 4.0 item designing company is being studied. The authors proposed an algorithm, which is based on the modified V L Volkovich method. This algorithm allows generating options how to arrange the production with robotized technological equipment functioning in the automatic mode. The optimization solution of the multi-criteria task for some additive criteria is the base of the algorithm.
Investigation of balancing problem for a planar mechanism using genetic algorithm
International Nuclear Information System (INIS)
Erkaya, Selcuk
2013-01-01
In this study, optimal balancing of a planar articulated mechanism is investigated to minimize the shaking force and moment fluctuations. Balancing of a four-bar mechanism is formulated as an optimization problem. On the other hand, an objective function based on the sub-components of shaking force and moment is constituted, and design variables consisting of kinematic and dynamic parameters are defined. Genetic algorithm is used to solve the optimization problem under the appropriate constraints. By using commercial simulation software, optimized values of design variables are also tested to evaluate the effectiveness of the proposed optimization process. This work provides a practical method for reducing the shaking force and moment fluctuations. The results show that both the structure of objective function and particularly the selection of weighting factors have a crucial role to obtain the optimum values of design parameters. By adjusting the value of weighting factor according to the relative sensitivity of the related term, there is a certain decrease at the shaking force and moment fluctuations. Moreover, these arrangements also decrease the initiative of mechanism designer on choosing the values of weighting factors.
The PBIL algorithm applied to a nuclear reactor design optimization
Energy Technology Data Exchange (ETDEWEB)
Machado, Marcelo D.; Medeiros, Jose A.C.C.; Lima, Alan M.M. de; Schirru, Roberto [Instituto Alberto Luiz Coimbra de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ-RJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear. Lab. de Monitoracao de Processos]. E-mails: marcelo@lmp.ufrj.br; canedo@lmp.ufrj.br; alan@lmp.ufrj.br; schirru@lmp.ufrj.br
2007-07-01
The Population-Based Incremental Learning (PBIL) algorithm is a method that combines the mechanism of genetic algorithm with the simple competitive learning, creating an important tool to be used in the optimization of numeric functions and combinatory problems. PBIL works with a set of solutions to the problems, called population, whose objective is create a probability vector, containing real values in each position, that when used in a decoding procedure gives subjects that present the best solutions for the function to be optimized. In this work a new form of learning for algorithm PBIL is developed, having aimed at to reduce the necessary time for the optimization process. This new algorithm will be used in the nuclear reactor design optimization. The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment zone reactor, considering some restrictions. In this optimization is used the computational code HAMMER, and the results compared with other methods of optimization by artificial intelligence. (author)
The PBIL algorithm applied to a nuclear reactor design optimization
International Nuclear Information System (INIS)
Machado, Marcelo D.; Medeiros, Jose A.C.C.; Lima, Alan M.M. de; Schirru, Roberto
2007-01-01
The Population-Based Incremental Learning (PBIL) algorithm is a method that combines the mechanism of genetic algorithm with the simple competitive learning, creating an important tool to be used in the optimization of numeric functions and combinatory problems. PBIL works with a set of solutions to the problems, called population, whose objective is create a probability vector, containing real values in each position, that when used in a decoding procedure gives subjects that present the best solutions for the function to be optimized. In this work a new form of learning for algorithm PBIL is developed, having aimed at to reduce the necessary time for the optimization process. This new algorithm will be used in the nuclear reactor design optimization. The optimization problem consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment zone reactor, considering some restrictions. In this optimization is used the computational code HAMMER, and the results compared with other methods of optimization by artificial intelligence. (author)
Risitano, Antonino
2011-01-01
METHODOLOGICAL STATEMENT OF ENGINEERING DESIGNApproaches to product design and developmentMechanical design and environmental requirementsPROPERTIES OF ENGINEERING MATERIALSMaterials for mechanical designCharacterization of metalsStress conditionsFatigue of materialsOptimum material selection in mechanical designDESIGN OF MECHANICAL COMPONENTS AND SYSTEMSFailure theoriesHertz theoryLubrificationShafts and bearingsSplines and keysSpringsFlexible machine elementsSpur gearsPress and shrink fitsPressure tubesCouplingsClutchesBrakes
A Fuzzy Gravitational Search Algorithm to Design Optimal IIR Filters
Directory of Open Access Journals (Sweden)
Danilo Pelusi
2018-03-01
Full Text Available The goodness of Infinite Impulse Response (IIR digital filters design depends on pass band ripple, stop band ripple and transition band values. The main problem is defining a suitable error fitness function that depends on these parameters. This fitness function can be optimized by search algorithms such as evolutionary algorithms. This paper proposes an intelligent algorithm for the design of optimal 8th order IIR filters. The main contribution is the design of Fuzzy Inference Systems able to tune key parameters of a revisited version of the Gravitational Search Algorithm (GSA. In this way, a Fuzzy Gravitational Search Algorithm (FGSA is designed. The optimization performances of FGSA are compared with those of Differential Evolution (DE and GSA. The results show that FGSA is the algorithm that gives the best compromise between goodness, robustness and convergence rate for the design of 8th order IIR filters. Moreover, FGSA assures a good stability of the designed filters.
Quantum mechanical design of enzyme active sites.
Zhang, Xiyun; DeChancie, Jason; Gunaydin, Hakan; Chowdry, Arnab B; Clemente, Fernando R; Smith, Adam J T; Handel, T M; Houk, K N
2008-02-01
The design of active sites has been carried out using quantum mechanical calculations to predict the rate-determining transition state of a desired reaction in presence of the optimal arrangement of catalytic functional groups (theozyme). Eleven versatile reaction targets were chosen, including hydrolysis, dehydration, isomerization, aldol, and Diels-Alder reactions. For each of the targets, the predicted mechanism and the rate-determining transition state (TS) of the uncatalyzed reaction in water is presented. For the rate-determining TS, a catalytic site was designed using naturalistic catalytic units followed by an estimation of the rate acceleration provided by a reoptimization of the catalytic site. Finally, the geometries of the sites were compared to the X-ray structures of related natural enzymes. Recent advances in computational algorithms and power, coupled with successes in computational protein design, have provided a powerful context for undertaking such an endeavor. We propose that theozymes are excellent candidates to serve as the active site models for design processes.
Fashion sketch design by interactive genetic algorithms
Mok, P. Y.; Wang, X. X.; Xu, J.; Kwok, Y. L.
2012-11-01
Computer aided design is vitally important for the modern industry, particularly for the creative industry. Fashion industry faced intensive challenges to shorten the product development process. In this paper, a methodology is proposed for sketch design based on interactive genetic algorithms. The sketch design system consists of a sketch design model, a database and a multi-stage sketch design engine. First, a sketch design model is developed based on the knowledge of fashion design to describe fashion product characteristics by using parameters. Second, a database is built based on the proposed sketch design model to define general style elements. Third, a multi-stage sketch design engine is used to construct the design. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch design process. The experimental results have demonstrated that the proposed method is effective in helping laypersons achieve satisfied fashion design sketches.
Intelligent design of mechanical parameters of the joint in vehicle body concept design model
Hou, Wen-bin; Zhang, Hong-zhe; Hou, Da-jun; Hu, Ping
2013-05-01
In order to estimate the mechanical properties of the overall structure of the body accurately and quickly in conceptual design phase of the body, the beam and shell mixing elements was used to build simplified finite element model of the body. Through the BP neural network algorithm, the parameters of the mechanical property of joints element which had more affection on calculation accuracy were calculated and the joint finite element model based on the parameters was also constructed. The case shown that the method can improve the accuracy of the vehicle simulation results, while not too many design details were needed, which was fit to the demand in the vehicle body conceptual design phase.
DEFF Research Database (Denmark)
Restrepo-Giraldo, John Dairo
2006-01-01
Most products and machines involve some kind of controlled movement. From window casements to DVD players, from harbor cranes to the shears to prune your garden, all these machines require mechanisms to move. This course intends to provide the analytical and conceptual tools to design such mechan......Most products and machines involve some kind of controlled movement. From window casements to DVD players, from harbor cranes to the shears to prune your garden, all these machines require mechanisms to move. This course intends to provide the analytical and conceptual tools to design...... using criteria such as size, performance parameters, operation environment, etc. Content: Understanding Mechanisms Design (2 weeks) Definitions, mechanisms representations, kinematic diagrams, the four bar linkage, mobility, applications of mechanisms, types of mechanisms, special mechanisms, the design......: equations for various mechanisms. At the end of this module you will be able to analyze existing mechanisms and to describe their movement. Designing mechanisms (7 weeks) Type synthesis and dimensional synthesis, function generation, path generation, three precision points in multi-loop mechanisms...
Multi-objective optimal design of sandwich panels using a genetic algorithm
Xu, Xiaomei; Jiang, Yiping; Pueh Lee, Heow
2017-10-01
In this study, an optimization problem concerning sandwich panels is investigated by simultaneously considering the two objectives of minimizing the panel mass and maximizing the sound insulation performance. First of all, the acoustic model of sandwich panels is discussed, which provides a foundation to model the acoustic objective function. Then the optimization problem is formulated as a bi-objective programming model, and a solution algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is provided to solve the proposed model. Finally, taking an example of a sandwich panel that is expected to be used as an automotive roof panel, numerical experiments are carried out to verify the effectiveness of the proposed model and solution algorithm. Numerical results demonstrate in detail how the core material, geometric constraints and mechanical constraints impact the optimal designs of sandwich panels.
Kriging-based algorithm for nuclear reactor neutronic design optimization
International Nuclear Information System (INIS)
Kempf, Stephanie; Forget, Benoit; Hu, Lin-Wen
2012-01-01
Highlights: ► A Kriging-based algorithm was selected to guide research reactor optimization. ► We examined impacts of parameter values upon the algorithm. ► The best parameter values were incorporated into a set of best practices. ► Algorithm with best practices used to optimize thermal flux of concept. ► Final design produces thermal flux 30% higher than other 5 MW reactors. - Abstract: Kriging, a geospatial interpolation technique, has been used in the present work to drive a search-and-optimization algorithm which produces the optimum geometric parameters for a 5 MW research reactor design. The technique has been demonstrated to produce an optimal neutronic solution after a relatively small number of core calculations. It has additionally been successful in producing a design which significantly improves thermal neutron fluxes by 30% over existing reactors of the same power rating. Best practices for use of this algorithm in reactor design were identified and indicated the importance of selecting proper correlation functions.
Channel Access Algorithm Design for Automatic Identification System
Institute of Scientific and Technical Information of China (English)
Oh Sang-heon; Kim Seung-pum; Hwang Dong-hwan; Park Chan-sik; Lee Sang-jeong
2003-01-01
The Automatic Identification System (AIS) is a maritime equipment to allow an efficient exchange of the navigational data between ships and between ships and shore stations. It utilizes a channel access algorithm which can quickly resolve conflicts without any intervention from control stations. In this paper, a design of channel access algorithm for the AIS is presented. The input/output relationship of each access algorithm module is defined by drawing the state transition diagram, dataflow diagram and flowchart based on the technical standard, ITU-R M.1371. In order to verify the designed channel access algorithm, the simulator was developed using the C/C++ programming language. The results show that the proposed channel access algorithm can properly allocate transmission slots and meet the operational performance requirements specified by the technical standard.
Performance indices and evaluation of algorithms in building energy efficient design optimization
International Nuclear Information System (INIS)
Si, Binghui; Tian, Zhichao; Jin, Xing; Zhou, Xin; Tang, Peng; Shi, Xing
2016-01-01
Building energy efficient design optimization is an emerging technique that is increasingly being used to design buildings with better overall performance and a particular emphasis on energy efficiency. To achieve building energy efficient design optimization, algorithms are vital to generate new designs and thus drive the design optimization process. Therefore, the performance of algorithms is crucial to achieving effective energy efficient design techniques. This study evaluates algorithms used for building energy efficient design optimization. A set of performance indices, namely, stability, robustness, validity, speed, coverage, and locality, is proposed to evaluate the overall performance of algorithms. A benchmark building and a design optimization problem are also developed. Hooke–Jeeves algorithm, Multi-Objective Genetic Algorithm II, and Multi-Objective Particle Swarm Optimization algorithm are evaluated by using the proposed performance indices and benchmark design problem. Results indicate that no algorithm performs best in all six areas. Therefore, when facing an energy efficient design problem, the algorithm must be carefully selected based on the nature of the problem and the performance indices that matter the most. - Highlights: • Six indices of algorithm performance in building energy optimization are developed. • For each index, its concept is defined and the calculation formulas are proposed. • A benchmark building and benchmark energy efficient design problem are proposed. • The performance of three selected algorithms are evaluated.
Generation of Compliant Mechanisms using Hybrid Genetic Algorithm
Sharma, D.; Deb, K.
2014-10-01
Compliant mechanism is a single piece elastic structure which can deform to perform the assigned task. In this work, compliant mechanisms are evolved using a constraint based bi-objective optimization formulation which requires one user defined parameter ( η). This user defined parameter limits a gap between a desired path and an actual path traced by the compliant mechanism. The non-linear and discrete optimization problems are solved using the hybrid Genetic Algorithm (GA) wherein domain specific initialization, two-dimensional crossover operator and repairing techniques are adopted. A bit-wise local search method is used with elitist non-dominated sorting genetic algorithm to further refine the compliant mechanisms. Parallel computations are performed on the master-slave architecture to reduce the computation time. A parametric study is carried out for η value which suggests a range to evolve topologically different compliant mechanisms. The applied and boundary conditions to the compliant mechanisms are considered the variables that are evolved by the hybrid GA. The post-analysis of results unveils that the complaint mechanisms are always supported at unique location that can evolve the non-dominated solutions.
Algorithm for the real-structure design of neutron supermirrors
International Nuclear Information System (INIS)
Pleshanov, N.K.
2004-01-01
The effect of structure imperfections of neutron supermirrors on their performance is well known. Nevertheless, supermirrors are designed with the algorithms based on the theories of reflection from perfect layered structures. In the present paper an approach is suggested, in which the design of a supermirror is made on the basis of its real-structure model (the RSD algorithm) with the use of exact numerical methods. It allows taking the growth laws and the reflectance of real structures into account. The new algorithm was compared with the Gukasov-Ruban-Bedrizova (GRB) algorithm and with the most frequently used algorithm of Hayter and Mook (HM). Calculations showed that, when the parameters of the algorithms are chosen so that the supermirrors designed for a given angular acceptance m have the same number of bilayers, (a) for perfect layers the GRB, HM and RSD algorithms generate sequences of practically the same reflectance; (b) for real structures with rough interfaces and interdiffusion the GRB and HM algorithms generate sequences with insufficient number of thinner layers and the RSD algorithm turns out to be more responsive and efficient. The efficiency of the RSD algorithm increases for larger m. In addition, calculations have been carried out to demonstrate the effect of fabrication errors and absorption on the reflectance of Ni/Ti supermirrors
Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1998-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
Robust reactor power control system design by genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Joon; Cho, Kyung Ho; Kim, Sin [Cheju National University, Cheju (Korea, Republic of)
1997-12-31
The H{sub {infinity}} robust controller for the reactor power control system is designed by use of the mixed weight sensitivity. The system is configured into the typical two-port model with which the weight functions are augmented. Since the solution depends on the weighting functions and the problem is of nonconvex, the genetic algorithm is used to determine the weighting functions. The cost function applied in the genetic algorithm permits the direct control of the power tracking performances. In addition, the actual operating constraints such as rod velocity and acceleration can be treated as design parameters. Compared with the conventional approach, the controller designed by the genetic algorithm results in the better performances with the realistic constraints. Also, it is found that the genetic algorithm could be used as an effective tool in the robust design. 4 refs., 6 figs. (Author)
Analysis and optimal design of an underactuated finger mechanism for LARM hand
Yao, Shuangji; Ceccarelli, Marco; Carbone, Giuseppe; Zhan, Qiang; Lu, Zhen
2011-09-01
This paper aims to present general design considerations and optimality criteria for underactuated mechanisms in finger designs. Design issues related to grasping task of robotic fingers are discussed. Performance characteristics are outlined as referring to several aspects of finger mechanisms. Optimality criteria of the finger performances are formulated after careful analysis. A general design algorithm is summarized and formulated as a suitable multi-objective optimization problem. A numerical case of an underactuated robot finger design for Laboratory of Robotics and Mechatronics (LARM) hand is illustrated with the aim to show the practical feasibility of the proposed concepts and computations.
A new hybrid meta-heuristic algorithm for optimal design of large-scale dome structures
Kaveh, A.; Ilchi Ghazaan, M.
2018-02-01
In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.
Directory of Open Access Journals (Sweden)
Daniel Antonio Molina
2015-09-01
Full Text Available In this paper we apply to solve the Radio Network Design problem (RND a series of the non-conventional genetic algorithms called Cross generational elitist selection Heterogeneous recombination Cataclysmic mutation (CHC. A set of genetic algorithms is used to perform a comparative performance of the proposed algorithms. An objective function based on signal coverage efficiency is used. Genetic variability of the population is used for both, as a parameter of convergence and detection of incest. Furthermore the variability of the best individual is proposed as a shaking mechanism. This allows generating dynamic populations according to the most promising solutions generating different search spaces. The results obtained by the proposed algorithms are satisfactory.
A Novel Evolutionary Algorithm for Designing Robust Analog Filters
Directory of Open Access Journals (Sweden)
Shaobo Li
2018-03-01
Full Text Available Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP coupled with bond graph modeling. We applied our GP-based robust design (GPRD algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA, our GPRD algorithm with a fitness criterion rewarding robustness, with respect to parameter perturbations, can evolve more robust filters than what was achieved through parameter tuning alone. We also find that inappropriate GA tuning may mislead the search process and that multiple-simulation and perturbed fitness evaluation methods for evolving robustness have complementary behaviors with no absolute advantage of one over the other.
A genetic algorithm for solving supply chain network design model
Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.
2013-09-01
Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.
Designing and implementing of improved cryptographic algorithm using modular arithmetic theory
Directory of Open Access Journals (Sweden)
Maryam Kamarzarrin
2015-05-01
Full Text Available Maintaining the privacy and security of people information are two most important principles of electronic health plan. One of the methods of creating privacy and securing of information is using Public key cryptography system. In this paper, we compare two algorithms, Common And Fast Exponentiation algorithms, for enhancing the efficiency of public key cryptography. We express that a designed system by Fast Exponentiation Algorithm has high speed and performance but low power consumption and space occupied compared with Common Exponentiation algorithm. Although designed systems by Common Exponentiation algorithm have slower speed and lower performance, designing by this algorithm has less complexity, and easier designing compared with Fast Exponentiation algorithm. In this paper, we will try to examine and compare two different methods of exponentiation, also observe performance Impact of these two approaches in the form of hardware with VHDL language on FPGA.
Instrument design and optimization using genetic algorithms
International Nuclear Information System (INIS)
Hoelzel, Robert; Bentley, Phillip M.; Fouquet, Peter
2006-01-01
This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of 'nonstandard' magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods
Instrument design and optimization using genetic algorithms
Hölzel, Robert; Bentley, Phillip M.; Fouquet, Peter
2006-10-01
This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of "nonstandard" magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods.
Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms.
Garro, Beatriz A; Vázquez, Roberto A
2015-01-01
Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems.
Automatic design of decision-tree induction algorithms
Barros, Rodrigo C; Freitas, Alex A
2015-01-01
Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning, and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain o
Optimum design for rotor-bearing system using advanced generic algorithm
International Nuclear Information System (INIS)
Kim, Young Chan; Choi, Seong Pil; Yang, Bo Suk
2001-01-01
This paper describes a combinational method to compute the global and local solutions of optimization problems. The present hybrid algorithm uses both a generic algorithm and a local concentrate search algorithm (e.g simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The present algorithm can be supplied to minimize the resonance response (Q factor) and to yield the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables
Ship Pipe Routing Design Using NSGA-II and Coevolutionary Algorithm
Directory of Open Access Journals (Sweden)
Wentie Niu
2016-01-01
Full Text Available Pipe route design plays a prominent role in ship design. Due to the complex configuration in layout space with numerous pipelines, diverse design constraints, and obstacles, it is a complicated and time-consuming process to obtain the optimal route of ship pipes. In this article, an optimized design method for branch pipe routing is proposed to improve design efficiency and to reduce human errors. By simplifying equipment and ship hull models and dividing workspace into three-dimensional grid cells, the mathematic model of layout space is constructed. Based on the proposed concept of pipe grading method, the optimization model of pipe routing is established. Then an optimization procedure is presented to deal with pipe route planning problem by combining maze algorithm (MA, nondominated sorting genetic algorithm II (NSGA-II, and cooperative coevolutionary nondominated sorting genetic algorithm II (CCNSGA-II. To improve the performance in genetic algorithm procedure, a fixed-length encoding method is presented based on improved maze algorithm and adaptive region strategy. Fuzzy set theory is employed to extract the best compromise pipeline from Pareto optimal solutions. Simulation test of branch pipe and design optimization of a fuel piping system were carried out to illustrate the design optimization procedure in detail and to verify the feasibility and effectiveness of the proposed methodology.
Evaluating progressive-rendering algorithms in appearance design tasks.
Jiawei Ou; Karlik, Ondrej; Křivánek, Jaroslav; Pellacini, Fabio
2013-01-01
Progressive rendering is becoming a popular alternative to precomputational approaches to appearance design. However, progressive algorithms create images exhibiting visual artifacts at early stages. A user study investigated these artifacts' effects on user performance in appearance design tasks. Novice and expert subjects performed lighting and material editing tasks with four algorithms: random path tracing, quasirandom path tracing, progressive photon mapping, and virtual-point-light rendering. Both the novices and experts strongly preferred path tracing to progressive photon mapping and virtual-point-light rendering. None of the participants preferred random path tracing to quasirandom path tracing or vice versa; the same situation held between progressive photon mapping and virtual-point-light rendering. The user workflow didn’t differ significantly with the four algorithms. The Web Extras include a video showing how four progressive-rendering algorithms converged (at http://youtu.be/ck-Gevl1e9s), the source code used, and other supplementary materials.
Graph Transformation and Designing Parallel Sparse Matrix Algorithms beyond Data Dependence Analysis
Directory of Open Access Journals (Sweden)
H.X. Lin
2004-01-01
Full Text Available Algorithms are often parallelized based on data dependence analysis manually or by means of parallel compilers. Some vector/matrix computations such as the matrix-vector products with simple data dependence structures (data parallelism can be easily parallelized. For problems with more complicated data dependence structures, parallelization is less straightforward. The data dependence graph is a powerful means for designing and analyzing parallel algorithms. However, for sparse matrix computations, parallelization based on solely exploiting the existing parallelism in an algorithm does not always give satisfactory results. For example, the conventional Gaussian elimination algorithm for the solution of a tri-diagonal system is inherently sequential, so algorithms specially for parallel computation has to be designed. After briefly reviewing different parallelization approaches, a powerful graph formalism for designing parallel algorithms is introduced. This formalism will be discussed using a tri-diagonal system as an example. Its application to general matrix computations is also discussed. Its power in designing parallel algorithms beyond the ability of data dependence analysis is shown by means of a new algorithm called ACER (Alternating Cyclic Elimination and Reduction algorithm.
Towards Automatic Controller Design using Multi-Objective Evolutionary Algorithms
DEFF Research Database (Denmark)
Pedersen, Gerulf
of evolutionary computation, a choice was made to use multi-objective algorithms for the purpose of aiding in automatic controller design. More specifically, the choice was made to use the Non-dominated Sorting Genetic Algorithm II (NSGAII), which is one of the most potent algorithms currently in use...... for automatic controller design. However, because the field of evolutionary computation is relatively unknown in the field of control engineering, this thesis also includes a comprehensive introduction to the basic field of evolutionary computation as well as a description of how the field has previously been......In order to design the controllers of tomorrow, a need has risen for tools that can aid in the design of these. A desire to use evolutionary computation as a tool to achieve that goal is what gave inspiration for the work contained in this thesis. After having studied the foundations...
Configurable intelligent optimization algorithm design and practice in manufacturing
Tao, Fei; Laili, Yuanjun
2014-01-01
Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorit
Analog Group Delay Equalizers Design Based on Evolutionary Algorithm
Directory of Open Access Journals (Sweden)
M. Laipert
2006-04-01
Full Text Available This paper deals with a design method of the analog all-pass filter designated for equalization of the group delay frequency response of the analog filter. This method is based on usage of evolutionary algorithm, the Differential Evolution algorithm in particular. We are able to design such equalizers to be obtained equal-ripple group delay frequency response in the pass-band of the low-pass filter. The procedure works automatically without an input estimation. The method is presented on solving practical examples.
A Cultural Algorithm for Optimal Design of Truss Structures
Directory of Open Access Journals (Sweden)
Shahin Jalili
Full Text Available Abstract A cultural algorithm was utilized in this study to solve optimal design of truss structures problem achieving minimum weight objective under stress and deflection constraints. The algorithm is inspired by principles of human social evolution. It simulates the social interaction between the peoples and their beliefs in a belief space. Cultural Algorithm (CA utilizes the belief space and population space which affects each other based on acceptance and influence functions. The belief space of CA consists of different knowledge components. In this paper, only situational and normative knowledge components are used within the belief space. The performance of the method is demonstrated through four benchmark design examples. Comparison of the obtained results with those of some previous studies demonstrates the efficiency of this algorithm.
Performance-based seismic design of steel frames utilizing colliding bodies algorithm.
Veladi, H
2014-01-01
A pushover analysis method based on semirigid connection concept is developed and the colliding bodies optimization algorithm is employed to find optimum seismic design of frame structures. Two numerical examples from the literature are studied. The results of the new algorithm are compared to the conventional design methods to show the power or weakness of the algorithm.
HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN
While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...
Lee, Donggil; Lee, Kyounghoon; Kim, Seonghun; Yang, Yongsu
2015-04-01
An automatic abalone grading algorithm that estimates abalone weights on the basis of computer vision using 2D images is developed and tested. The algorithm overcomes the problems experienced by conventional abalone grading methods that utilize manual sorting and mechanical automatic grading. To design an optimal algorithm, a regression formula and R(2) value were investigated by performing a regression analysis for each of total length, body width, thickness, view area, and actual volume against abalone weights. The R(2) value between the actual volume and abalone weight was 0.999, showing a relatively high correlation. As a result, to easily estimate the actual volumes of abalones based on computer vision, the volumes were calculated under the assumption that abalone shapes are half-oblate ellipsoids, and a regression formula was derived to estimate the volumes of abalones through linear regression analysis between the calculated and actual volumes. The final automatic abalone grading algorithm is designed using the abalone volume estimation regression formula derived from test results, and the actual volumes and abalone weights regression formula. In the range of abalones weighting from 16.51 to 128.01 g, the results of evaluation of the performance of algorithm via cross-validation indicate root mean square and worst-case prediction errors of are 2.8 and ±8 g, respectively. © 2015 Institute of Food Technologists®
Expert-guided evolutionary algorithm for layout design of complex space stations
Qian, Zhiqin; Bi, Zhuming; Cao, Qun; Ju, Weiguo; Teng, Hongfei; Zheng, Yang; Zheng, Siyu
2017-08-01
The layout of a space station should be designed in such a way that different equipment and instruments are placed for the station as a whole to achieve the best overall performance. The station layout design is a typical nondeterministic polynomial problem. In particular, how to manage the design complexity to achieve an acceptable solution within a reasonable timeframe poses a great challenge. In this article, a new evolutionary algorithm has been proposed to meet such a challenge. It is called as the expert-guided evolutionary algorithm with a tree-like structure decomposition (EGEA-TSD). Two innovations in EGEA-TSD are (i) to deal with the design complexity, the entire design space is divided into subspaces with a tree-like structure; it reduces the computation and facilitates experts' involvement in the solving process. (ii) A human-intervention interface is developed to allow experts' involvement in avoiding local optimums and accelerating convergence. To validate the proposed algorithm, the layout design of one-space station is formulated as a multi-disciplinary design problem, the developed algorithm is programmed and executed, and the result is compared with those from other two algorithms; it has illustrated the superior performance of the proposed EGEA-TSD.
Optimum Performance-Based Seismic Design Using a Hybrid Optimization Algorithm
Directory of Open Access Journals (Sweden)
S. Talatahari
2014-01-01
Full Text Available A hybrid optimization method is presented to optimum seismic design of steel frames considering four performance levels. These performance levels are considered to determine the optimum design of structures to reduce the structural cost. A pushover analysis of steel building frameworks subject to equivalent-static earthquake loading is utilized. The algorithm is based on the concepts of the charged system search in which each agent is affected by local and global best positions stored in the charged memory considering the governing laws of electrical physics. Comparison of the results of the hybrid algorithm with those of other metaheuristic algorithms shows the efficiency of the hybrid algorithm.
Graph-drawing algorithms geometries versus molecular mechanics in fullereness
Kaufman, M.; Pisanski, T.; Lukman, D.; Borštnik, B.; Graovac, A.
1996-09-01
The algorithms of Kamada-Kawai (KK) and Fruchterman-Reingold (FR) have been recently generalized (Pisanski et al., Croat. Chem. Acta 68 (1995) 283) in order to draw molecular graphs in three-dimensional space. The quality of KK and FR geometries is studied here by comparing them with the molecular mechanics (MM) and the adjacency matrix eigenvectors (AME) algorithm geometries. In order to compare different layouts of the same molecule, an appropriate method has been developed. Its application to a series of experimentally detected fullerenes indicates that the KK, FR and AME algorithms are able to reproduce plausible molecular geometries.
Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis
Brouwer, Randall Jay
1991-01-01
The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.
Genetic local search algorithm for optimization design of diffractive optical elements.
Zhou, G; Chen, Y; Wang, Z; Song, H
1999-07-10
We propose a genetic local search algorithm (GLSA) for the optimization design of diffractive optical elements (DOE's). This hybrid algorithm incorporates advantages of both genetic algorithm (GA) and local search techniques. It appears better able to locate the global minimum compared with a canonical GA. Sample cases investigated here include the optimization design of binary-phase Dammann gratings, continuous surface-relief grating array generators, and a uniform top-hat focal plane intensity profile generator. Two GLSA's whose incorporated local search techniques are the hill-climbing method and the simulated annealing algorithm are investigated. Numerical experimental results demonstrate that the proposed algorithm is highly efficient and robust. DOE's that have high diffraction efficiency and excellent uniformity can be achieved by use of the algorithm we propose.
PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design
Directory of Open Access Journals (Sweden)
Huu-Khoa Tran
2016-09-01
Full Text Available Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO-based algorithm and the evolutionary programming (EP algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models.
A Hybrid Optimization Algorithm for Low RCS Antenna Design
Directory of Open Access Journals (Sweden)
W. Shao
2012-12-01
Full Text Available In this article, a simple and efficient method is presented to design low radar cross section (RCS patch antennas. This method consists of a hybrid optimization algorithm, which combines a genetic algorithm (GA with tabu search algorithm (TSA, and electromagnetic field solver. The TSA, embedded into the GA frame, defines the acceptable neighborhood region of parameters and screens out the poor-scoring individuals. Thus, the repeats of search are avoided and the amount of time-consuming electromagnetic simulations is largely reduced. Moreover, the whole design procedure is auto-controlled by programming the VBScript language. A slot patch antenna example is provided to verify the accuracy and efficiency of the proposed method.
Application of colony complex algorithm to nuclear component optimization design
International Nuclear Information System (INIS)
Yan Changqi; Li Guijing; Wang Jianjun
2014-01-01
Complex algorithm (CA) has got popular application to the region of nuclear engineering. In connection with the specific features of the application of traditional complex algorithm (TCA) to the optimization design in engineering structures, an improved method, colony complex algorithm (CCA), was developed based on the optimal combination of many complexes, in which the disadvantages of TCA were overcame. The optimized results of benchmark function show that CCA has better optimizing performance than TCA. CCA was applied to the high-pressure heater optimization design, and the optimization effect is obvious. (authors)
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2017-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Advances in metaheuristic algorithms for optimal design of structures
Kaveh, A
2014-01-01
This book presents efficient metaheuristic algorithms for optimal design of structures. Many of these algorithms are developed by the author and his colleagues, consisting of Democratic Particle Swarm Optimization, Charged System Search, Magnetic Charged System Search, Field of Forces Optimization, Dolphin Echolocation Optimization, Colliding Bodies Optimization, Ray Optimization. These are presented together with algorithms which were developed by other authors and have been successfully applied to various optimization problems. These consist of Particle Swarm Optimization, Big Bang-Big Crunch Algorithm, Cuckoo Search Optimization, Imperialist Competitive Algorithm, and Chaos Embedded Metaheuristic Algorithms. Finally a multi-objective optimization method is presented to solve large-scale structural problems based on the Charged System Search algorithm. The concepts and algorithms presented in this book are not only applicable to optimization of skeletal structures and finite element models, but can equally ...
Design of reproducible polarized and non-polarized edge filters using genetic algorithm
International Nuclear Information System (INIS)
Ejigu, Efrem Kebede; Lacquet, B M
2010-01-01
Recent advancement in optical fibre communications technology is partly due to the advancement of optical thin film technology. The advancement of optical thin film technology includes the development of new and existing optical filter design methods. The genetic algorithm is one of the new design methods that show promising results in designing a number of complicated design specifications. It is the finding of this study that the genetic algorithm design method, through its optimization capability, can give more reliable and reproducible designs of any specifications. The design method in this study optimizes the thickness of each layer to get to the best possible solution. Its capability and unavoidable limitations in designing polarized and non-polarized edge filters from absorptive and dispersive materials is well demonstrated. It is also demonstrated that polarized and non-polarized designs from the genetic algorithm are reproducible with great success. This research has accomplished the great task of formulating a computer program using the genetic algorithm in a Matlab environment for the design of a reproducible polarized and non-polarized filters of any sort from any kind of materials
Secure image encryption algorithm design using a novel chaos based S-Box
International Nuclear Information System (INIS)
Çavuşoğlu, Ünal; Kaçar, Sezgin; Pehlivan, Ihsan; Zengin, Ahmet
2017-01-01
Highlights: • A new chaotic system is developed for creating S-Box and image encryption algorithm. • Chaos based random number generator is designed with the help of the new chaotic system. NIST tests are run on generated random numbers to verify randomness. • A new S-Box design algorithm is developed to create the chaos based S-Box to be utilized in encryption algorithm and performance tests are made. • The new developed S-Box based image encryption algorithm is introduced and image encryption application is carried out. • To show the quality and strong of the encryption process, security analysis are performed and compared with the AES and chaos algorithms. - Abstract: In this study, an encryption algorithm that uses chaos based S-BOX is developed for secure and speed image encryption. First of all, a new chaotic system is developed for creating S-Box and image encryption algorithm. Chaos based random number generator is designed with the help of the new chaotic system. Then, NIST tests are run on generated random numbers to verify randomness. A new S-Box design algorithm is developed to create the chaos based S-Box to be utilized in encryption algorithm and performance tests are made. As the next step, the new developed S-Box based image encryption algorithm is introduced in detail. Finally, image encryption application is carried out. To show the quality and strong of the encryption process, security analysis are performed. Proposed algorithm is compared with the AES and chaos algorithms. According to tests results, the proposed image encryption algorithm is secure and speed for image encryption application.
The design and results of an algorithm for intelligent ground vehicles
Duncan, Matthew; Milam, Justin; Tote, Caleb; Riggins, Robert N.
2010-01-01
This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for its 2009 Intelligent Ground Vehicle Competition (IGVC) robot called Anassa V. The BSC robotics team is comprised of undergraduate computer science, engineering technology, marketing students, and one robotics faculty advisor. The team has participated in IGVC since the year 2000. A major part of the design process that the BSC team uses each year for IGVC is a fully documented "Post-IGVC Analysis." Over the nine years since 2000, the lessons the students learned from these analyses have resulted in an ever-improving, highly successful autonomous algorithm. The algorithm employed in Anassa V is a culmination of past successes and new ideas, resulting in Anassa V earning several excellent IGVC 2009 performance awards, including third place overall. The paper will discuss all aspects of the design of this autonomous robotic system, beginning with the design process and ending with test results for both simulation and real environments.
Directory of Open Access Journals (Sweden)
Chocat Rudy
2015-01-01
Full Text Available The design of complex systems often induces a constrained optimization problem under uncertainty. An adaptation of CMA-ES(λ, μ optimization algorithm is proposed in order to efficiently handle the constraints in the presence of noise. The update mechanisms of the parametrized distribution used to generate the candidate solutions are modified. The constraint handling method allows to reduce the semi-principal axes of the probable research ellipsoid in the directions violating the constraints. The proposed approach is compared to existing approaches on three analytic optimization problems to highlight the efficiency and the robustness of the algorithm. The proposed method is used to design a two stage solid propulsion launch vehicle.
EGNAS: an exhaustive DNA sequence design algorithm
Directory of Open Access Journals (Sweden)
Kick Alfred
2012-06-01
Full Text Available Abstract Background The molecular recognition based on the complementary base pairing of deoxyribonucleic acid (DNA is the fundamental principle in the fields of genetics, DNA nanotechnology and DNA computing. We present an exhaustive DNA sequence design algorithm that allows to generate sets containing a maximum number of sequences with defined properties. EGNAS (Exhaustive Generation of Nucleic Acid Sequences offers the possibility of controlling both interstrand and intrastrand properties. The guanine-cytosine content can be adjusted. Sequences can be forced to start and end with guanine or cytosine. This option reduces the risk of “fraying” of DNA strands. It is possible to limit cross hybridizations of a defined length, and to adjust the uniqueness of sequences. Self-complementarity and hairpin structures of certain length can be avoided. Sequences and subsequences can optionally be forbidden. Furthermore, sequences can be designed to have minimum interactions with predefined strands and neighboring sequences. Results The algorithm is realized in a C++ program. TAG sequences can be generated and combined with primers for single-base extension reactions, which were described for multiplexed genotyping of single nucleotide polymorphisms. Thereby, possible foldback through intrastrand interaction of TAG-primer pairs can be limited. The design of sequences for specific attachment of molecular constructs to DNA origami is presented. Conclusions We developed a new software tool called EGNAS for the design of unique nucleic acid sequences. The presented exhaustive algorithm allows to generate greater sets of sequences than with previous software and equal constraints. EGNAS is freely available for noncommercial use at http://www.chm.tu-dresden.de/pc6/EGNAS.
Digital Image Encryption Algorithm Design Based on Genetic Hyperchaos
Directory of Open Access Journals (Sweden)
Jian Wang
2016-01-01
Full Text Available In view of the present chaotic image encryption algorithm based on scrambling (diffusion is vulnerable to choosing plaintext (ciphertext attack in the process of pixel position scrambling, we put forward a image encryption algorithm based on genetic super chaotic system. The algorithm, by introducing clear feedback to the process of scrambling, makes the scrambling effect related to the initial chaos sequence and the clear text itself; it has realized the image features and the organic fusion of encryption algorithm. By introduction in the process of diffusion to encrypt plaintext feedback mechanism, it improves sensitivity of plaintext, algorithm selection plaintext, and ciphertext attack resistance. At the same time, it also makes full use of the characteristics of image information. Finally, experimental simulation and theoretical analysis show that our proposed algorithm can not only effectively resist plaintext (ciphertext attack, statistical attack, and information entropy attack but also effectively improve the efficiency of image encryption, which is a relatively secure and effective way of image communication.
Design optimization of brushed permanent magnet D C motor by genetic algorithm
Amini, S
2002-01-01
Because of field winding replacement with permanent magnet in brushed permanent magnet D C (PMDC) motors, field losses are eliminated and the structure of the motor is more simple. Efficiency of these motors is therefore increased and the manufacturing process is simplified. Hence, these motors are commonly used in low power applications and their design and optimization is an important consideration. Genetic algorithms are proposed for design optimization of PMD motors because of their independence to objective function structure and its derivative. In this paper genetic algorithms are evaluated for PMDC motor design optimization. an introduction is first presented about PMDC motors, general design procedure and elements of their optimization. Genetic algorithms are then briefly described. Finally results of optimization by genetic algorithms are compared with the one obtained using a conventional method.
Design optimization of brushed permanent magnet D C motor by genetic algorithm
International Nuclear Information System (INIS)
Amini, S.; Oraee, H.
2002-01-01
Because of field winding replacement with permanent magnet in brushed permanent magnet D C (PMDC) motors, field losses are eliminated and the structure of the motor is more simple. Efficiency of these motors is therefore increased and the manufacturing process is simplified. Hence, these motors are commonly used in low power applications and their design and optimization is an important consideration. Genetic algorithms are proposed for design optimization of PMD motors because of their independence to objective function structure and its derivative. In this paper genetic algorithms are evaluated for PMDC motor design optimization. an introduction is first presented about PMDC motors, general design procedure and elements of their optimization. Genetic algorithms are then briefly described. Finally results of optimization by genetic algorithms are compared with the one obtained using a conventional method
Improved PSO algorithm based on chaos theory and its application to design flood hydrograph
Directory of Open Access Journals (Sweden)
Si-Fang Dong
2010-06-01
Full Text Available The deficiencies of basic particle swarm optimization (bPSO are its ubiquitous prematurity and its inability to seek the global optimal solution when optimizing complex high-dimensional functions. To overcome such deficiencies, the chaos-PSO (COSPSO algorithm was established by introducing the chaos optimization mechanism and a global particle stagnation-disturbance strategy into bPSO. In the improved algorithm, chaotic movement was adopted for the particles' initial movement trajectories to replace the former stochastic movement, and the chaos factor was used to guide the particles' path. When the global particles were stagnant, the disturbance strategy was used to keep the particles in motion. Five benchmark optimizations were introduced to test COSPSO, and they proved that COSPSO can remarkably improve efficiency in optimizing complex functions. Finally, a case study of COSPSO in calculating design flood hydrographs demonstrated the applicability of the improved algorithm.
Simulated annealing algorithm for reactor in-core design optimizations
International Nuclear Information System (INIS)
Zhong Wenfa; Zhou Quan; Zhong Zhaopeng
2001-01-01
A nuclear reactor must be optimized for in core fuel management to make full use of the fuel, to reduce the operation cost and to flatten the power distribution reasonably. The author presents a simulated annealing algorithm. The optimized objective function and the punishment function were provided for optimizing the reactor physics design. The punishment function was used to practice the simulated annealing algorithm. The practical design of the NHR-200 was calculated. The results show that the K eff can be increased by 2.5% and the power distribution can be flattened
A synthesis/design optimization algorithm for Rankine cycle based energy systems
International Nuclear Information System (INIS)
Toffolo, Andrea
2014-01-01
The algorithm presented in this work has been developed to search for the optimal topology and design parameters of a set of Rankine cycles forming an energy system that absorbs/releases heat at different temperature levels and converts part of the absorbed heat into electricity. This algorithm can deal with several applications in the field of energy engineering: e.g., steam cycles or bottoming cycles in combined/cogenerative plants, steam networks, low temperature organic Rankine cycles. The main purpose of this algorithm is to overcome the limitations of the search space introduced by the traditional mixed-integer programming techniques, which assume that possible solutions are derived from a single superstructure embedding them all. The algorithm presented in this work is a hybrid evolutionary/traditional optimization algorithm organized in two levels. A complex original codification of the topology and the intensive design parameters of the system is managed by the upper level evolutionary algorithm according to the criteria set by the HEATSEP method, which are used for the first time to automatically synthesize a “basic” system configuration from a set of elementary thermodynamic cycles. The lower SQP (sequential quadratic programming) algorithm optimizes the objective function(s) with respect to cycle mass flow rates only, taking into account the heat transfer feasibility constraint within the undefined heat transfer section. A challenging example of application is also presented to show the capabilities of the algorithm. - Highlights: • Energy systems based on Rankine cycles are used in many applications. • A hybrid algorithm is proposed to optimize the synthesis/design of such systems. • The topology of the candidate solutions is not limited by a superstructure. • Topology is managed by the genetic operators of the upper level algorithm. • The effectiveness of the algorithm is proved in a complex test case
Optimal Solution for VLSI Physical Design Automation Using Hybrid Genetic Algorithm
Directory of Open Access Journals (Sweden)
I. Hameem Shanavas
2014-01-01
Full Text Available In Optimization of VLSI Physical Design, area minimization and interconnect length minimization is an important objective in physical design automation of very large scale integration chips. The objective of minimizing the area and interconnect length would scale down the size of integrated chips. To meet the above objective, it is necessary to find an optimal solution for physical design components like partitioning, floorplanning, placement, and routing. This work helps to perform the optimization of the benchmark circuits with the above said components of physical design using hierarchical approach of evolutionary algorithms. The goal of minimizing the delay in partitioning, minimizing the silicon area in floorplanning, minimizing the layout area in placement, minimizing the wirelength in routing has indefinite influence on other criteria like power, clock, speed, cost, and so forth. Hybrid evolutionary algorithm is applied on each of its phases to achieve the objective. Because evolutionary algorithm that includes one or many local search steps within its evolutionary cycles to obtain the minimization of area and interconnect length. This approach combines a hierarchical design like genetic algorithm and simulated annealing to attain the objective. This hybrid approach can quickly produce optimal solutions for the popular benchmarks.
A strategy for quantum algorithm design assisted by machine learning
International Nuclear Information System (INIS)
Bang, Jeongho; Lee, Jinhyoung; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin
2014-01-01
We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum–classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch–Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method. (paper)
A strategy for quantum algorithm design assisted by machine learning
Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung
2014-07-01
We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.
GENETIC ALGORITHM IN OPTIMIZATION DESIGN OF INTERIOR PERMANENT MAGNET SYNCHRONOUS MOTOR
Directory of Open Access Journals (Sweden)
Phuong Le Ngo
2017-01-01
Full Text Available Classical method of designing electric motors help to achieve functional motor, but doesn’t ensure minimal cost in manufacturing and operating. Recently optimization is becoming an important part in modern electric motor design process. The objective of the optimization process is usually to minimize cost, energy loss, mass, or maximize torque and efficiency. Most of the requirements for electrical machine design are in contradiction to each other (reduction in volume or mass, improvement in efficiency etc.. Optimization in design permanent magnet synchronous motor (PMSM is a multi-objective optimization problem. There are two approaches for solving this problem, one of them is evolution algorithms, which gain a lot of attentions recently. For designing PMSM, evolution algorithms are more attractive approach. Genetic algorithm is one of the most common. This paper presents components and procedures of genetic algorithms, and its implementation on computer. In optimization process, analytical and finite element method are used together for better performance and precision. Result from optimization process is a set of solutions, from which engineer will choose one. This method was used to design a permanent magnet synchronous motor based on an asynchronous motor type АИР112МВ8.
Design optimization and analysis of selected thermal devices using self-adaptive Jaya algorithm
International Nuclear Information System (INIS)
Rao, R.V.; More, K.C.
2017-01-01
Highlights: • Self-adaptive Jaya algorithm is proposed for optimal design of thermal devices. • Optimization of heat pipe, cooling tower, heat sink and thermo-acoustic prime mover is presented. • Results of the proposed algorithm are better than the other optimization techniques. • The proposed algorithm may be conveniently used for the optimization of other devices. - Abstract: The present study explores the use of an improved Jaya algorithm called self-adaptive Jaya algorithm for optimal design of selected thermal devices viz; heat pipe, cooling tower, honeycomb heat sink and thermo-acoustic prime mover. Four different optimization case studies of the selected thermal devices are presented. The researchers had attempted the same design problems in the past using niched pareto genetic algorithm (NPGA), response surface method (RSM), leap-frog optimization program with constraints (LFOPC) algorithm, teaching-learning based optimization (TLBO) algorithm, grenade explosion method (GEM) and multi-objective genetic algorithm (MOGA). The results achieved by using self-adaptive Jaya algorithm are compared with those achieved by using the NPGA, RSM, LFOPC, TLBO, GEM and MOGA algorithms. The self-adaptive Jaya algorithm is proved superior as compared to the other optimization methods in terms of the results, computational effort and function evalutions.
Design Optimization of Tilting-Pad Journal Bearing Using a Genetic Algorithm
Directory of Open Access Journals (Sweden)
Hamit Saruhan
2004-01-01
Full Text Available This article focuses on the use of genetic algorithms in developing an efficient optimum design method for tilting pad bearings. The approach optimizes based on minimum film thickness, power loss, maximum film temperature, and a global objective. Results for a five tilting-pad preloaded bearing are presented to provide a comparison with more traditional optimum design methods such as the gradient-based global criterion method, and also to provide insight into the potential of genetic algorithms in the design of rotor bearings. Genetic algorithms are efficient search techniques based on the idea of natural selection and genetics. These robust methods have gained recognition as general problem solving techniques in many applications.
An Algorithm for the Mixed Transportation Network Design Problem.
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
An Algorithm for the Mixed Transportation Network Design Problem.
Directory of Open Access Journals (Sweden)
Xinyu Liu
Full Text Available This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA, for solving a mixed transportation network design problem (MNDP, which is generally expressed as a mathematical programming with equilibrium constraint (MPEC. The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE problem. The idea of the proposed solution algorithm (DDIA is to reduce the dimensions of the problem. A group of variables (discrete/continuous is fixed to optimize another group of variables (continuous/discrete alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems and DNDPs (discrete network design problems repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions. Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
Theory and Algorithms for Global/Local Design Optimization
National Research Council Canada - National Science Library
Watson, Layne T; Guerdal, Zafer; Haftka, Raphael T
2005-01-01
The motivating application for this research is the global/local optimal design of composite aircraft structures such as wings and fuselages, but the theory and algorithms are more widely applicable...
Theory and Algorithms for Global/Local Design Optimization
National Research Council Canada - National Science Library
Haftka, Raphael T
2004-01-01
... the component and overall design as well as on exploration of global optimization algorithms. In the former category, heuristic decomposition was followed with proof that it solves the original problem...
Optimal design of the heat pipe using TLBO (teaching–learning-based optimization) algorithm
International Nuclear Information System (INIS)
Rao, R.V.; More, K.C.
2015-01-01
Heat pipe is a highly efficient and reliable heat transfer component. It is a closed container designed to transfer a large amount of heat in system. Since the heat pipe operates on a closed two-phase cycle, the heat transfer capacity is greater than for solid conductors. Also, the thermal response time is less than with solid conductors. The three major elemental parts of the rotating heat pipe are: a cylindrical evaporator, a truncated cone condenser, and a fixed amount of working fluid. In this paper, a recently proposed new stochastic advanced optimization algorithm called TLBO (Teaching–Learning-Based Optimization) algorithm is used for single objective as well as multi-objective design optimization of heat pipe. It is easy to implement, does not make use of derivatives and it can be applied to unconstrained or constrained problems. Two examples of heat pipe are presented in this paper. The results of application of TLBO algorithm for the design optimization of heat pipe are compared with the NPGA (Niched Pareto Genetic Algorithm), GEM (Grenade Explosion Method) and GEO (Generalized External optimization). It is found that the TLBO algorithm has produced better results as compared to those obtained by using NPGA, GEM and GEO algorithms. - Highlights: • The TLBO (Teaching–Learning-Based Optimization) algorithm is used for the design and optimization of a heat pipe. • Two examples of heat pipe design and optimization are presented. • The TLBO algorithm is proved better than the other optimization algorithms in terms of results and the convergence
Designing algorithm visualization on mobile platform: The proposed guidelines
Supli, A. A.; Shiratuddin, N.
2017-09-01
This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively. Our previous review indicated that design guidelines of AV on mobile platform are still few. Mostly, previous guidelines of AV are developed for AV on desktop and website platform. In fact, mobile learning has been proved to enhance engagement in learning circumstances, and thus effect student's performance. In addition, the researchers highly recommend including UI design and Interactivity in designing effective AV system. However, the discussions of these two aspects in previous AV design guidelines are not comprehensive. The UI design in this paper describes the arrangement of AV features in mobile environment, whereas interactivity is about the active learning strategy features based on learning experiences (how to engage learners). Thus, this study main objective is to propose design guidelines of AV on mobile platform (AVOMP) that entails comprehensively UI design and interactivity aspects. These guidelines are developed through content analysis and comparative analysis from various related studies. These guidelines are useful for AV designers to help them constructing AVOMP for various topics on DSA.
Design and optimization of a bend-and-sweep compliant mechanism
International Nuclear Information System (INIS)
Tummala, Y; Frecker, M I; Wissa, A A; Hubbard Jr, J E
2013-01-01
A novel contact aided compliant mechanism called bend-and-sweep compliant mechanism is presented in this paper. This mechanism has nonlinear stiffness properties in two orthogonal directions. An angled compliant joint (ACJ) is the fundamental element of this mechanism. Geometric parameters of ACJs determine the stiffness of the compliant mechanism. This paper presents the design and optimization of bend-and-sweep compliant mechanism. A multi-objective optimization problem was formulated for design optimization of the bend-and-sweep compliant mechanism. The objectives of the optimization problem were to maximize or minimize the bending and sweep displacements, depending on the situation, while minimizing the von Mises stress and mass of each mechanism. This optimization problem was solved using NSGA-II (a genetic algorithm). The results of this optimization for a single ACJ during upstroke and downstroke are presented in this paper. Results of two different loading conditions used during optimization of a single ACJ for upstroke are presented. Finally, optimization results comparing the performance of compliant mechanisms with one and two ACJs are also presented. It can be inferred from these results that the number of ACJs and the design of each ACJ determines the stiffness of the bend-and-sweep compliant mechanism. These mechanisms can be used in various applications. The goal of this research is to improve the performance of ornithopters by passively morphing their wings. In order to achieve a bio-inspired wing gait called continuous vortex gait, the wings of the ornithopter need to bend, and sweep simultaneously. This can be achieved by inserting the bend-and-sweep compliant mechanism into the leading edge wing spar of the ornithopters. (paper)
Genetic Algorithm Design of a 3D Printed Heat Sink
Energy Technology Data Exchange (ETDEWEB)
Wu, Tong [ORNL; Ozpineci, Burak [ORNL; Ayers, Curtis William [ORNL
2016-01-01
In this paper, a genetic algorithm- (GA-) based approach is discussed for designing heat sinks based on total heat generation and dissipation for a pre-specified size andshape. This approach combines random iteration processesand genetic algorithms with finite element analysis (FEA) to design the optimized heat sink. With an approach that prefers survival of the fittest , a more powerful heat sink can bedesigned which can cool power electronics more efficiently. Some of the resulting designs can only be 3D printed due totheir complexity. In addition to describing the methodology, this paper also includes comparisons of different cases to evaluate the performance of the newly designed heat sinkcompared to commercially available heat sinks.
Chaotic logic gate: A new approach in set and design by genetic algorithm
International Nuclear Information System (INIS)
Beyki, Mahmood; Yaghoobi, Mahdi
2015-01-01
How to reconfigure a logic gate is an attractive subject for different applications. Chaotic systems can yield a wide variety of patterns and here we use this feature to produce a logic gate. This feature forms the basis for designing a dynamical computing device that can be rapidly reconfigured to become any wanted logical operator. This logic gate that can reconfigure to any logical operator when placed in its chaotic state is called chaotic logic gate. The reconfiguration realize by setting the parameter values of chaotic logic gate. In this paper we present mechanisms about how to produce a logic gate based on the logistic map in its chaotic state and genetic algorithm is used to set the parameter values. We use three well-known selection methods used in genetic algorithm: tournament selection, Roulette wheel selection and random selection. The results show the tournament selection method is the best method for set the parameter values. Further, genetic algorithm is a powerful tool to set the parameter values of chaotic logic gate
Application of genetic algorithm to control design
International Nuclear Information System (INIS)
Lee, Yoon Joon; Cho, Kyung Ho
1995-01-01
A classical PID controller is designed by applying the GA (Genetic Algorithm) which searches the optimal parameters through three major operators of reproduction, crossover and mutation under the given constraints. The GA could minimize the designer's interference and the whole design process could easily be automated. In contrast with other traditional PID design methods which allows for the system output responses only, the design with the GA can take account of the magnitude or the rate of change of control input together with the output responses, which reflects the more realistic situations. Compared with other PIDs designed by the traditional methods such as Ziegler and analytic, the PID by the GA shows the superior response characteristics to those of others with the least control input energy
Mathematical Model and Algorithm for the Reefer Mechanic Scheduling Problem at Seaports
Directory of Open Access Journals (Sweden)
Jiantong Zhang
2017-01-01
Full Text Available With the development of seaborne logistics, the international trade of goods transported in refrigerated containers is growing fast. Refrigerated containers, also known as reefers, are used in transportation of temperature sensitive cargo, such as perishable fruits. This trend brings new challenges to terminal managers, that is, how to efficiently arrange mechanics to plug and unplug power for the reefers (i.e., tasks at yards. This work investigates the reefer mechanics scheduling problem at container ports. To minimize the sum of the total tardiness of all tasks and the total working distance of all mechanics, we formulate a mathematical model. For the resolution of this problem, we propose a DE algorithm which is combined with efficient heuristics, local search strategies, and parameter adaption scheme. The proposed algorithm is tested and validated through numerical experiments. Computational results demonstrate the effectiveness and efficiency of the proposed algorithm.
Photovoltaic Cells Mppt Algorithm and Design of Controller Monitoring System
Meng, X. Z.; Feng, H. B.
2017-10-01
This paper combined the advantages of each maximum power point tracking (MPPT) algorithm, put forward a kind of algorithm with higher speed and higher precision, based on this algorithm designed a maximum power point tracking controller with ARM. The controller, communication technology and PC software formed a control system. Results of the simulation and experiment showed that the process of maximum power tracking was effective, and the system was stable.
A superlinear interior points algorithm for engineering design optimization
Herskovits, J.; Asquier, J.
1990-01-01
We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.
Blake, Alexander
2018-01-01
A cornerstone publication that covers the basic principles and practical considerations of design methodology for joints held by rivets, bolts, weld seams, and adhesive materials, Design of Mechanical Joints gives engineers the practical results and formulas they need for the preliminary design of mechanical joints, combining the essential topics of joint mechanics...strength of materials...and fracture control to provide a complete treatment of problems pertinent to the field of mechanical connections.
Lawton, Pat
2004-01-01
The objective of this work was to support the design of improved IUE NEWSIPS high dispersion extraction algorithms. The purpose of this work was to evaluate use of the Linearized Image (LIHI) file versus the Re-Sampled Image (SIHI) file, evaluate various extraction, and design algorithms for evaluation of IUE High Dispersion spectra. It was concluded the use of the Re-Sampled Image (SIHI) file was acceptable. Since the Gaussian profile worked well for the core and the Lorentzian profile worked well for the wings, the Voigt profile was chosen for use in the extraction algorithm. It was found that the gamma and sigma parameters varied significantly across the detector, so gamma and sigma masks for the SWP detector were developed. Extraction code was written.
Designing synthetic networks in silico: a generalised evolutionary algorithm approach.
Smith, Robert W; van Sluijs, Bob; Fleck, Christian
2017-12-02
Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses.
Directory of Open Access Journals (Sweden)
N. M. Okasha
2016-04-01
Full Text Available In this paper, an approach for conducting a Reliability-Based Design Optimization (RBDO of truss structures with linked-discrete design variables is proposed. The sections of the truss members are selected from the AISC standard tables and thus the design variables that represent the properties of each section are linked. Latin hypercube sampling is used in the evaluation of the structural reliability. The improved firefly algorithm is used for the optimization solution process. It was found that in order to use the improved firefly algorithm for efficiently solving problems of reliability-based design optimization with linked-discrete design variables; it needs to be modified as proposed in this paper to accelerate its convergence.
Starting design for use in variance exchange algorithms | Iwundu ...
African Journals Online (AJOL)
A new method of constructing the initial design for use in variance exchange algorithms is presented. The method chooses support points to go into the design as measures of distances of the support points from the centre of the geometric region and of permutation-invariant sets. The initial design is as close as possible to ...
Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm
Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven
2010-05-01
Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.
Design and Implementation of the Automated Rendezvous Targeting Algorithms for Orion
DSouza, Christopher; Weeks, Michael
2010-01-01
The Orion vehicle will be designed to perform several rendezvous missions: rendezvous with the ISS in Low Earth Orbit (LEO), rendezvous with the EDS/Altair in LEO, a contingency rendezvous with the ascent stage of the Altair in Low Lunar Orbit (LLO) and a contingency rendezvous in LLO with the ascent and descent stage in the case of an aborted lunar landing. Therefore, it is not difficult to realize that each of these scenarios imposes different operational, timing, and performance constraints on the GNC system. To this end, a suite of on-board guidance and targeting algorithms have been designed to meet the requirement to perform the rendezvous independent of communications with the ground. This capability is particularly relevant for the lunar missions, some of which may occur on the far side of the moon. This paper will describe these algorithms which are designed to be structured and arranged in such a way so as to be flexible and able to safely perform a wide variety of rendezvous trajectories. The goal of the algorithms is not to merely fly one specific type of canned rendezvous profile. Conversely, it was designed from the start to be general enough such that any type of trajectory profile can be flown.(i.e. a coelliptic profile, a stable orbit rendezvous profile, and a expedited LLO rendezvous profile, etc) all using the same rendezvous suite of algorithms. Each of these profiles makes use of maneuver types which have been designed with dual goals of robustness and performance. They are designed to converge quickly under dispersed conditions and they are designed to perform many of the functions performed on the ground today. The targeting algorithms consist of a phasing maneuver (NC), an altitude adjust maneuver (NH), and plane change maneuver (NPC), a coelliptic maneuver (NSR), a Lambert targeted maneuver, and several multiple-burn targeted maneuvers which combine one of more of these algorithms. The derivation and implementation of each of these
Nuclear power control system design using genetic algorithm
International Nuclear Information System (INIS)
Lee, Yoon Joon; Cho, Kyung Ho
1996-01-01
The genetic algorithm(GA) is applied to the design of the nuclear power control system. The reactor control system model is described in the LQR configuration. The LQR system order is increased to make the tracking system. The key parameters of the design are weighting matrices, and these are usually determined through numerous simulations in the conventional design. To determine the more objective and optimal weightings, the improved GA is applied. The results show that the weightings determined by the GA yield the better system responses than those obtained by the conventional design method
Artificial neural networks and evolutionary algorithms in engineering design
T. Velsker; M. Eerme; J. Majak; M. Pohlak; K. Karjust
2011-01-01
Purpose: Purpose of this paper is investigation of optimization strategies eligible for solving complex engineering design problems. An aim is to develop numerical algorithms for solving optimal design problems which may contain real and integer variables, a number of local extremes, linear- and non-linear constraints and multiple optimality criteria.Design/methodology/approach: The methodology proposed for solving optimal design problems is based on integrated use of meta-modeling techniques...
Scalable Algorithms for Adaptive Statistical Designs
Directory of Open Access Journals (Sweden)
Robert Oehmke
2000-01-01
Full Text Available We present a scalable, high-performance solution to multidimensional recurrences that arise in adaptive statistical designs. Adaptive designs are an important class of learning algorithms for a stochastic environment, and we focus on the problem of optimally assigning patients to treatments in clinical trials. While adaptive designs have significant ethical and cost advantages, they are rarely utilized because of the complexity of optimizing and analyzing them. Computational challenges include massive memory requirements, few calculations per memory access, and multiply-nested loops with dynamic indices. We analyze the effects of various parallelization options, and while standard approaches do not work well, with effort an efficient, highly scalable program can be developed. This allows us to solve problems thousands of times more complex than those solved previously, which helps make adaptive designs practical. Further, our work applies to many other problems involving neighbor recurrences, such as generalized string matching.
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
Lohn, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris; Norvig, Peter (Technical Monitor)
2000-01-01
We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.
Optimal Design of a Centrifugal Compressor Impeller Using Evolutionary Algorithms
Directory of Open Access Journals (Sweden)
Soo-Yong Cho
2012-01-01
Full Text Available An optimization study was conducted on a centrifugal compressor. Eight design variables were chosen from the control points for the Bezier curves which widely influenced the geometric variation; four design variables were selected to optimize the flow passage between the hub and the shroud, and other four design variables were used to improve the performance of the impeller blade. As an optimization algorithm, an artificial neural network (ANN was adopted. Initially, the design of experiments was applied to set up the initial data space of the ANN, which was improved during the optimization process using a genetic algorithm. If a result of the ANN reached a higher level, that result was re-calculated by computational fluid dynamics (CFD and was applied to develop a new ANN. The prediction difference between the ANN and CFD was consequently less than 1% after the 6th generation. Using this optimization technique, the computational time for the optimization was greatly reduced and the accuracy of the optimization algorithm was increased. The efficiency was improved by 1.4% without losing the pressure ratio, and Pareto-optimal solutions of the efficiency versus the pressure ratio were obtained through the 21st generation.
Differential Evolution Algorithm with Self-Adaptive Population Resizing Mechanism
Directory of Open Access Journals (Sweden)
Xu Wang
2013-01-01
Full Text Available A differential evolution (DE algorithm with self-adaptive population resizing mechanism, SapsDE, is proposed to enhance the performance of DE by dynamically choosing one of two mutation strategies and tuning control parameters in a self-adaptive manner. More specifically, more appropriate mutation strategies along with its parameter settings can be determined adaptively according to the previous status at different stages of the evolution process. To verify the performance of SapsDE, 17 benchmark functions with a wide range of dimensions, and diverse complexities are used. Nonparametric statistical procedures were performed for multiple comparisons between the proposed algorithm and five well-known DE variants from the literature. Simulation results show that SapsDE is effective and efficient. It also exhibits much more superiorresultsthan the other five algorithms employed in the comparison in most of the cases.
Yelk, Joseph; Sukharev, Maxim; Seideman, Tamar
2008-08-14
An optimal control approach based on multiple parameter genetic algorithms is applied to the design of plasmonic nanoconstructs with predetermined optical properties and functionalities. We first develop nanoscale metallic lenses that focus an incident plane wave onto a prespecified, spatially confined spot. Our results illustrate the mechanism of energy flow through wires and cavities. Next we design a periodic array of silver particles to modify the polarization of an incident, linearly polarized plane wave in a desired fashion while localizing the light in space. The results provide insight into the structural features that determine the birefringence properties of metal nanoparticles and their arrays. Of the variety of potential applications that may be envisioned, we note the design of nanoscale light sources with controllable coherence and polarization properties that could serve for coherent control of molecular, electronic, or electromechanical dynamics in the nanoscale.
A new collage steganographic algorithm using cartoon design
Yi, Shuang; Zhou, Yicong; Pun, Chi-Man; Chen, C. L. Philip
2014-02-01
Existing collage steganographic methods suffer from low payload of embedding messages. To improve the payload while providing a high level of security protection to messages, this paper introduces a new collage steganographic algorithm using cartoon design. It embeds messages into the least significant bits (LSBs) of color cartoon objects, applies different permutations to each object, and adds objects to a cartoon cover image to obtain the stego image. Computer simulations and comparisons demonstrate that the proposed algorithm shows significantly higher capacity of embedding messages compared with existing collage steganographic methods.
A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules.
Daeyaert, Frits; Deem, Micheal W
2017-01-01
We have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Fuel pin design algorithm for conceptual design studies
International Nuclear Information System (INIS)
Uselman, J.P.
1979-01-01
Two models are available which are currently verified by part of the requirements and which are adaptable as algorithms for the complete range. Fuel thermal performance is described by the HEDL SIEX model. Cladding damage and total deformation are determined by the GE GRO-II structural analysis code. A preliminary fuel pin performance model for analysis of (U, P/sub U/)O 2 pins in the COROPT core conceptual design system has been constructed by combining the key elements of SIEX and GRO-II. This memo describes the resulting pin performance model and its interfacing with COROPT system. Some exemplary results are presented
An exact algorithm for optimal MAE stack filter design.
Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior
2007-02-01
We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.
Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design.
Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco
2016-11-23
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms.
Theoretical and numerical study of an optimum design algorithm
International Nuclear Information System (INIS)
Destuynder, Philippe.
1976-08-01
This work can be separated into two main parts. First, the behavior of the solution of an elliptic variational equation is analyzed when the domain is submitted to a small perturbation. The case of inequations is also considered. Secondly the previous results are used for deriving an optimum design algorithm. This algorithm was suggested by the center-method proposed by Huard. Numerical results show the superiority of the method on other different optimization techniques [fr
Game mechanics : advanced game design
Adams, Ernest; Dormans, Joris
2012-01-01
Game Mechanics is aimed at game design students and industry professionals who want to improve their understanding of how to design, build, and test the mechanics of a game. Game Mechanics will show you how to design, test, and tune the core mechanics of a game—any game, from a huge role-playing
GST-PRIME: an algorithm for genome-wide primer design.
Leister, Dario; Varotto, Claudio
2007-01-01
The profiling of mRNA expression based on DNA arrays has become a powerful tool to study genome-wide transcription of genes in a number of organisms. GST-PRIME is a software package created to facilitate large-scale primer design for the amplification of probes to be immobilized on arrays for transcriptome analyses, even though it can be also applied in low-throughput approaches. GST-PRIME allows highly efficient, direct amplification of gene-sequence tags (GSTs) from genomic DNA (gDNA), starting from annotated genome or transcript sequences. GST-PRIME provides a customer-friendly platform for automatic primer design, and despite the relative simplicity of the algorithm, experimental tests in the model plant species Arabidopsis thaliana confirmed the reliability of the software. This chapter describes the algorithm used for primer design, its input and output files, and the installation of the standalone package and its use.
Genetic algorithms and Monte Carlo simulation for optimal plant design
International Nuclear Information System (INIS)
Cantoni, M.; Marseguerra, M.; Zio, E.
2000-01-01
We present an approach to the optimal plant design (choice of system layout and components) under conflicting safety and economic constraints, based upon the coupling of a Monte Carlo evaluation of plant operation with a Genetic Algorithms-maximization procedure. The Monte Carlo simulation model provides a flexible tool, which enables one to describe relevant aspects of plant design and operation, such as standby modes and deteriorating repairs, not easily captured by analytical models. The effects of deteriorating repairs are described by means of a modified Brown-Proschan model of imperfect repair which accounts for the possibility of an increased proneness to failure of a component after a repair. The transitions of a component from standby to active, and vice versa, are simulated using a multiplicative correlation model. The genetic algorithms procedure is demanded to optimize a profit function which accounts for the plant safety and economic performance and which is evaluated, for each possible design, by the above Monte Carlo simulation. In order to avoid an overwhelming use of computer time, for each potential solution proposed by the genetic algorithm, we perform only few hundreds Monte Carlo histories and, then, exploit the fact that during the genetic algorithm population evolution, the fit chromosomes appear repeatedly many times, so that the results for the solutions of interest (i.e. the best ones) attain statistical significance
An algorithm, implementation and execution ontology design pattern
Lawrynowicz, A.; Esteves, D.; Panov, P.; Soru, T.; Dzeroski, S.; Vanschoren, J.
2016-01-01
This paper describes an ontology design pattern for modeling algorithms, their implementations and executions. This pattern is derived from the research results on data mining/machine learning ontologies, but is more generic. We argue that the proposed pattern will foster the development of
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments
Harman, Radoslav; Filová , Lenka; Richtarik, Peter
2018-01-01
We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.
A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments
Harman, Radoslav
2018-01-17
We propose a class of subspace ascent methods for computing optimal approximate designs that covers both existing as well as new and more efficient algorithms. Within this class of methods, we construct a simple, randomized exchange algorithm (REX). Numerical comparisons suggest that the performance of REX is comparable or superior to the performance of state-of-the-art methods across a broad range of problem structures and sizes. We focus on the most commonly used criterion of D-optimality that also has applications beyond experimental design, such as the construction of the minimum volume ellipsoid containing a given set of data-points. For D-optimality, we prove that the proposed algorithm converges to the optimum. We also provide formulas for the optimal exchange of weights in the case of the criterion of A-optimality. These formulas enable one to use REX for computing A-optimal and I-optimal designs.
Design of PID Controller Simulator based on Genetic Algorithm
Directory of Open Access Journals (Sweden)
Fahri VATANSEVER
2013-08-01
Full Text Available PID (Proportional Integral and Derivative controllers take an important place in the field of system controlling. Various methods such as Ziegler-Nichols, Cohen-Coon, Chien Hrones Reswick (CHR and Wang-Juang-Chan are available for the design of such controllers benefiting from the system time and frequency domain data. These controllers are in compliance with system properties under certain criteria suitable to the system. Genetic algorithms have become widely used in control system applications in parallel to the advances in the field of computer and artificial intelligence. In this study, PID controller designs have been carried out by means of classical methods and genetic algorithms and comparative results have been analyzed. For this purpose, a graphical user interface program which can be used for educational purpose has been developed. For the definite (entered transfer functions, the suitable P, PI and PID controller coefficients have calculated by both classical methods and genetic algorithms and many parameters and responses of the systems have been compared and presented numerically and graphically
Hardware Design Considerations for Edge-Accelerated Stereo Correspondence Algorithms
Directory of Open Access Journals (Sweden)
Christos Ttofis
2012-01-01
Full Text Available Stereo correspondence is a popular algorithm for the extraction of depth information from a pair of rectified 2D images. Hence, it has been used in many computer vision applications that require knowledge about depth. However, stereo correspondence is a computationally intensive algorithm and requires high-end hardware resources in order to achieve real-time processing speed in embedded computer vision systems. This paper presents an overview of the use of edge information as a means to accelerate hardware implementations of stereo correspondence algorithms. The presented approach restricts the stereo correspondence algorithm only to the edges of the input images rather than to all image points, thus resulting in a considerable reduction of the search space. The paper highlights the benefits of the edge-directed approach by applying it to two stereo correspondence algorithms: an SAD-based fixed-support algorithm and a more complex adaptive support weight algorithm. Furthermore, we present design considerations about the implementation of these algorithms on reconfigurable hardware and also discuss issues related to the memory structures needed, the amount of parallelism that can be exploited, the organization of the processing blocks, and so forth. The two architectures (fixed-support based versus adaptive-support weight based are compared in terms of processing speed, disparity map accuracy, and hardware overheads, when both are implemented on a Virtex-5 FPGA platform.
High mechanical advantage design of six-bar Stephenson mechanism for servo mechanical presses
Directory of Open Access Journals (Sweden)
Jianguo Hu
2016-06-01
Full Text Available This article proposed a two-phase design scheme of Stephenson six-bar working mechanisms for servo mechanical presses with high mechanical advantage. In the qualitative design phase, first, a Stephenson six-bar mechanism with a slide was derived from Stephenson six-bar kinematic chains. Second, based on the instant center analysis method, the relationship between mechanical advantage and some special instant centers was founded, and accordingly a primary mechanism configuration with high mechanical advantage was designed qualitatively. Then, a parameterized prototype model was established, and the influences of design parameters toward slide kinematical characteristics were analyzed. In the quantitative design phase, a multi-objective optimization model, aiming at high mechanical advantage and dwelling characteristics, was built, and a case design was done to find optimal dimensions. Finally, simulations based on the software ADAMS were conducted to compare the transmission characteristics of the optimized working mechanism with that of slide-crank mechanism and symmetrical toggle mechanism, and an experimental press was made to validate the design scheme. The simulation and experiment results show that, compared with general working mechanisms, the Stephenson six-bar working mechanism has higher mechanical advantage and better dwelling characteristics, reducing capacities and costs of servo motors effectively.
Design of sparse Halbach magnet arrays for portable MRI using a genetic algorithm.
Cooley, Clarissa Zimmerman; Haskell, Melissa W; Cauley, Stephen F; Sappo, Charlotte; Lapierre, Cristen D; Ha, Christopher G; Stockmann, Jason P; Wald, Lawrence L
2018-01-01
Permanent magnet arrays offer several attributes attractive for the development of a low-cost portable MRI scanner for brain imaging. They offer the potential for a relatively lightweight, low to mid-field system with no cryogenics, a small fringe field, and no electrical power requirements or heat dissipation needs. The cylindrical Halbach array, however, requires external shimming or mechanical adjustments to produce B 0 fields with standard MRI homogeneity levels (e.g., 0.1 ppm over FOV), particularly when constrained or truncated geometries are needed, such as a head-only magnet where the magnet length is constrained by the shoulders. For portable scanners using rotation of the magnet for spatial encoding with generalized projections, the spatial pattern of the field is important since it acts as the encoding field. In either a static or rotating magnet, it will be important to be able to optimize the field pattern of cylindrical Halbach arrays in a way that retains construction simplicity. To achieve this, we present a method for designing an optimized cylindrical Halbach magnet using the genetic algorithm to achieve either homogeneity (for standard MRI applications) or a favorable spatial encoding field pattern (for rotational spatial encoding applications). We compare the chosen designs against a standard, fully populated sparse Halbach design, and evaluate optimized spatial encoding fields using point-spread-function and image simulations. We validate the calculations by comparing to the measured field of a constructed magnet. The experimentally implemented design produced fields in good agreement with the predicted fields, and the genetic algorithm was successful in improving the chosen metrics. For the uniform target field, an order of magnitude homogeneity improvement was achieved compared to the un-optimized, fully populated design. For the rotational encoding design the resolution uniformity is improved by 95% compared to a uniformly populated design.
Mechanical design engineering handbook
Childs, Peter R N
2013-01-01
Mechanical Design Engineering Handbook is a straight-talking and forward-thinking reference covering the design, specification, selection, use and integration of machine elements fundamental to a wide range of engineering applications. Develop or refresh your mechanical design skills in the areas of bearings, shafts, gears, seals, belts and chains, clutches and brakes, springs, fasteners, pneumatics and hydraulics, amongst other core mechanical elements, and dip in for principles, data and calculations as needed to inform and evaluate your on-the-job decisions. Covering the full spectrum
Design of synthetic biological logic circuits based on evolutionary algorithm.
Chuang, Chia-Hua; Lin, Chun-Liang; Chang, Yen-Chang; Jennawasin, Tanagorn; Chen, Po-Kuei
2013-08-01
The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose.
Application of an imperialist competitive algorithm to the design of a linear induction motor
International Nuclear Information System (INIS)
Lucas, Caro; Nasiri-Gheidari, Zahra; Tootoonchian, Farid
2010-01-01
In this paper a novel optimization algorithm based on imperialist competitive algorithm (ICA) is used for the design of a low speed single sided linear induction motor (LIM). This type of motors is used increasingly in industrial process specially in transportation systems. In these applications having high efficiency with high power factor is very important. So in this paper the objective function of design is presented considering both efficiency and power factor. Finally the results of ICA are compared with the ones of genetic algorithm and conventional design. Comparison shows the success of ICA for design of LIMs.
Rules Extraction with an Immune Algorithm
Directory of Open Access Journals (Sweden)
Deqin Yan
2007-12-01
Full Text Available In this paper, a method of extracting rules with immune algorithms from information systems is proposed. Designing an immune algorithm is based on a sharing mechanism to extract rules. The principle of sharing and competing resources in the sharing mechanism is consistent with the relationship of sharing and rivalry among rules. In order to extract rules efficiently, a new concept of flexible confidence and rule measurement is introduced. Experiments demonstrate that the proposed method is effective.
International Nuclear Information System (INIS)
Toffolo, A.; Lazzaretto, A.
2002-01-01
Thermoeconomic analyses in thermal system design are always focused on the economic objective. However, knowledge of only the economic minimum may not be sufficient in the decision making process, since solutions with a higher thermodynamic efficiency, in spite of small increases in total costs, may result in much more interesting designs due to changes in energy market prices or in energy policies. This paper suggests how to perform a multi-objective optimization in order to find solutions that simultaneously satisfy exergetic and economic objectives. This corresponds to a search for the set of Pareto optimal solutions with respect to the two competing objectives. The optimization process is carried out by an evolutionary algorithm, that features a new diversity preserving mechanism using as a test case the well-known CGAM problem. (author)
Zakoldaev, D. A.; Shukalov, A. V.; Zharinov, I. O.; Zharinov, O. O.
2018-05-01
The task of the algorithm of choosing the type of mechanical assembly production of instrument making enterprises of Industry 4.0 is being studied. There is a comparison of two project algorithms for Industry 3.0 and Industry 4.0. The algorithm of choosing the type of mechanical assembly production of instrument making enterprises of Industry 4.0 is based on the technological route analysis of the manufacturing process in a company equipped with cyber and physical systems. This algorithm may give some project solutions selected from the primary part or the auxiliary one of the production. The algorithm decisive rules are based on the optimal criterion.
A structured representation for parallel algorithm design on multicomputers
International Nuclear Information System (INIS)
Sun, Xian-He; Ni, L.M.
1991-01-01
Traditionally, parallel algorithms have been designed by brute force methods and fine-tuned on each architecture to achieve high performance. Rather than studying the design case by case, a systematic approach is proposed. A notation is first developed. Using this notation, most of the frequently used scientific and engineering applications can be presented by simple formulas. The formulas constitute the structured representation of the corresponding applications. The structured representation is simple, adequate and easy to understand. They also contain sufficient information about uneven allocation and communication latency degradations. With the structured representation, applications can be compared, classified and partitioned. Some of the basic building blocks, called computation models, of frequently used applications are identified and studied. Most applications are combinations of some computation models. The structured representation relates general applications to computation models. Studying computation models leads to a guideline for efficient parallel algorithm design for general applications. 6 refs., 7 figs
Solution Algorithm for a New Bi-Level Discrete Network Design Problem
Directory of Open Access Journals (Sweden)
Qun Chen
2013-12-01
Full Text Available A new discrete network design problem (DNDP was pro-posed in this paper, where the variables can be a series of integers rather than just 0-1. The new DNDP can determine both capacity improvement grades of reconstruction roads and locations and capacity grades of newly added roads, and thus complies with the practical projects where road capacity can only be some discrete levels corresponding to the number of lanes of roads. This paper designed a solution algorithm combining branch-and-bound with Hooke-Jeeves algorithm, where feasible integer solutions are recorded in searching the process of Hooke-Jeeves algorithm, lend -ing itself to determine the upper bound of the upper-level problem. The thresholds for branch cutting and ending were set for earlier convergence. Numerical examples are given to demonstrate the efficiency of the proposed algorithm.
Optimum Design of Gravity Retaining Walls Using Charged System Search Algorithm
Directory of Open Access Journals (Sweden)
S. Talatahari
2012-01-01
Full Text Available This study focuses on the optimum design retaining walls, as one of the familiar types of the retaining walls which may be constructed of stone masonry, unreinforced concrete, or reinforced concrete. The material cost is one of the major factors in the construction of gravity retaining walls therefore, minimizing the weight or volume of these systems can reduce the cost. To obtain an optimal seismic design of such structures, this paper proposes a method based on a novel meta-heuristic algorithm. The algorithm is inspired by the Coulomb's and Gauss’s laws of electrostatics in physics, and it is called charged system search (CSS. In order to evaluate the efficiency of this algorithm, an example is utilized. Comparing the results of the retaining wall designs obtained by the other methods illustrates a good performance of the CSS. In this paper, we used the Mononobe-Okabe method which is one of the pseudostatic approaches to determine the dynamic earth pressure.
Application of mapping crossover genetic algorithm in nuclear power equipment optimization design
International Nuclear Information System (INIS)
Li Guijiang; Yan Changqi; Wang Jianjun; Liu Chengyang
2013-01-01
Genetic algorithm (GA) has been widely applied in nuclear engineering. An improved method, named the mapping crossover genetic algorithm (MCGA), was developed aiming at improving the shortcomings of traditional genetic algorithm (TGA). The optimal results of benchmark problems show that MCGA has better optimizing performance than TGA. MCGA was applied to the reactor coolant pump optimization design. (authors)
Foudray, Angela Marie Klohs
Detecting, quantifying and visualizing biochemical mechanism in a living system without perturbing function is the goal of the instrument and algorithms designed in this thesis. Biochemical mechanisms of cells have long been known to be dependent on the signals they receive from their environment. Studying biological processes of cells in-vitro can vastly distort their function, since you are removing them from their natural chemical signaling environment. Mice have become the biological system of choice for various areas of biomedical research due to their genetic and physiological similarities with humans, the relatively low cost of their care, and their quick breeding cycle. Drug development and efficacy assessment along with disease detection, management, and mechanism research all have benefited from the use of small animal models of human disease. A high resolution, high sensitivity, three-dimensional (3D) positioning positron emission tomography (PET) detector system was designed through device characterization and Monte Carlo simulation. Position-sensitive avalanche photodiodes (PSAPDs) were characterized in various packaging configurations; coupled to various configurations of lutetium oxyorthosilicate (LSO) scintillation crystals. Forty novelly packaged final design devices were constructed and characterized, each providing characteristics superior to commercially available scintillation detectors used in small animal imaging systems: ˜1mm crystal identification, 14-15% of 511 keV energy resolution, and averaging 1.9 to 5.6 ns coincidence time resolution. A closed-cornered box-shaped detector configuration was found to provide optimal photon sensitivity (˜10.5% in the central plane) using dual LSO-PSAPD scintillation detector modules and Monte Carlo simulation. Standard figures of merit were used to determine optimal system acquisition parameters. A realistic model for constituent devices was developed for understanding the signals reported by the
MICRONEEDLE STRUCTURE DESIGN AND OPTIMIZATION USING GENETIC ALGORITHM
N. A. ISMAIL; S. C. NEOH; N. SABANI; B. N. TAIB
2015-01-01
This paper presents a Genetic Algorithm (GA) based microneedle design and analysis. GA is an evolutionary optimization technique that mimics the natural biological evolution. The design of microneedle structure considers the shape of microneedle, material used, size of the array, the base of microneedle, the lumen base, the height of microneedle, the height of the lumen, and the height of the drug container or reservoir. The GA is executed in conjunction with ANSYS simulation system to assess...
An Adaptive Tradeoff Algorithm for Multi-issue SLA Negotiation
Son, Seokho; Sim, Kwang Mong
Since participants in a Cloud may be independent bodies, mechanisms are necessary for resolving different preferences in leasing Cloud services. Whereas there are currently mechanisms that support service-level agreement negotiation, there is little or no negotiation support for concurrent price and timeslot for Cloud service reservations. For the concurrent price and timeslot negotiation, a tradeoff algorithm to generate and evaluate a proposal which consists of price and timeslot proposal is necessary. The contribution of this work is thus to design an adaptive tradeoff algorithm for multi-issue negotiation mechanism. The tradeoff algorithm referred to as "adaptive burst mode" is especially designed to increase negotiation speed and total utility and to reduce computational load by adaptively generating concurrent set of proposals. The empirical results obtained from simulations carried out using a testbed suggest that due to the concurrent price and timeslot negotiation mechanism with adaptive tradeoff algorithm: 1) both agents achieve the best performance in terms of negotiation speed and utility; 2) the number of evaluations of each proposal is comparatively lower than previous scheme (burst-N).
Evolving spiking neural networks: a novel growth algorithm exhibits unintelligent design
Schaffer, J. David
2015-06-01
Spiking neural networks (SNNs) have drawn considerable excitement because of their computational properties, believed to be superior to conventional von Neumann machines, and sharing properties with living brains. Yet progress building these systems has been limited because we lack a design methodology. We present a gene-driven network growth algorithm that enables a genetic algorithm (evolutionary computation) to generate and test SNNs. The genome for this algorithm grows O(n) where n is the number of neurons; n is also evolved. The genome not only specifies the network topology, but all its parameters as well. Experiments show the algorithm producing SNNs that effectively produce a robust spike bursting behavior given tonic inputs, an application suitable for central pattern generators. Even though evolution did not include perturbations of the input spike trains, the evolved networks showed remarkable robustness to such perturbations. In addition, the output spike patterns retain evidence of the specific perturbation of the inputs, a feature that could be exploited by network additions that could use this information for refined decision making if required. On a second task, a sequence detector, a discriminating design was found that might be considered an example of "unintelligent design"; extra non-functional neurons were included that, while inefficient, did not hamper its proper functioning.
Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs
Directory of Open Access Journals (Sweden)
Haijian Chen
2015-01-01
Full Text Available In recent years, Massive Open Online Courses (MOOCs are very popular among college students and have a powerful impact on academic institutions. In the MOOCs environment, knowledge discovery and knowledge sharing are very important, which currently are often achieved by ontology techniques. In building ontology, automatic extraction technology is crucial. Because the general methods of text mining algorithm do not have obvious effect on online course, we designed automatic extracting course knowledge points (AECKP algorithm for online course. It includes document classification, Chinese word segmentation, and POS tagging for each document. Vector Space Model (VSM is used to calculate similarity and design the weight to optimize the TF-IDF algorithm output values, and the higher scores will be selected as knowledge points. Course documents of “C programming language” are selected for the experiment in this study. The results show that the proposed approach can achieve satisfactory accuracy rate and recall rate.
DEFF Research Database (Denmark)
Nica, Florin Valentin Traian; Ritchie, Ewen; Leban, Krisztina Monika
2013-01-01
, genetic algorithm and particle swarm are shortly presented in this paper. These two algorithms are tested to determine their performance on five different benchmark test functions. The algorithms are tested based on three requirements: precision of the result, number of iterations and calculation time....... Both algorithms are also tested on an analytical design process of a Transverse Flux Permanent Magnet Generator to observe their performances in an electrical machine design application.......Nowadays the requirements imposed by the industry and economy ask for better quality and performance while the price must be maintained in the same range. To achieve this goal optimization must be introduced in the design process. Two of the best known optimization algorithms for machine design...
Multiscale Monte Carlo algorithms in statistical mechanics and quantum field theory
Energy Technology Data Exchange (ETDEWEB)
Lauwers, P G
1990-12-01
Conventional Monte Carlo simulation algorithms for models in statistical mechanics and quantum field theory are afflicted by problems caused by their locality. They become highly inefficient if investigations of critical or nearly-critical systems, i.e., systems with important large scale phenomena, are undertaken. We present two types of multiscale approaches that alleveate problems of this kind: Stochastic cluster algorithms and multigrid Monte Carlo simulation algorithms. Another formidable computational problem in simulations of phenomenologically relevant field theories with fermions is the need for frequently inverting the Dirac operator. This inversion can be accelerated considerably by means of deterministic multigrid methods, very similar to the ones used for the numerical solution of differential equations. (orig.).
Algorithm design of liquid lens inspection system
Hsieh, Lu-Lin; Wang, Chun-Chieh
2008-08-01
In mobile lens domain, the glass lens is often to be applied in high-resolution requirement situation; but the glass zoom lens needs to be collocated with movable machinery and voice-coil motor, which usually arises some space limits in minimum design. In high level molding component technology development, the appearance of liquid lens has become the focus of mobile phone and digital camera companies. The liquid lens sets with solid optical lens and driving circuit has replaced the original components. As a result, the volume requirement is decreased to merely 50% of the original design. Besides, with the high focus adjusting speed, low energy requirement, high durability, and low-cost manufacturing process, the liquid lens shows advantages in the competitive market. In the past, authors only need to inspect the scrape defect made by external force for the glass lens. As to the liquid lens, authors need to inspect the state of four different structural layers due to the different design and structure. In this paper, authors apply machine vision and digital image processing technology to administer inspections in the particular layer according to the needs of users. According to our experiment results, the algorithm proposed can automatically delete non-focus background, extract the region of interest, find out and analyze the defects efficiently in the particular layer. In the future, authors will combine the algorithm of the system with automatic-focus technology to implement the inside inspection based on the product inspective demands.
High Precision Edge Detection Algorithm for Mechanical Parts
Duan, Zhenyun; Wang, Ning; Fu, Jingshun; Zhao, Wenhui; Duan, Boqiang; Zhao, Jungui
2018-04-01
High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.
Izumi, K. H.; Thompson, J. L.; Groce, J. L.; Schwab, R. W.
1986-01-01
The design requirements for a 4D path definition algorithm are described. These requirements were developed for the NASA ATOPS as an extension of the Local Flow Management/Profile Descent algorithm. They specify the processing flow, functional and data architectures, and system input requirements, and recommended the addition of a broad path revision (reinitialization) function capability. The document also summarizes algorithm design enhancements and the implementation status of the algorithm on an in-house PDP-11/70 computer. Finally, the requirements for the pilot-computer interfaces, the lateral path processor, and guidance and steering function are described.
New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.
Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng
2016-05-16
The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.
Model-based fault diagnosis techniques design schemes, algorithms, and tools
Ding, Steven
2008-01-01
The objective of this book is to introduce basic model-based FDI schemes, advanced analysis and design algorithms, and the needed mathematical and control theory tools at a level for graduate students and researchers as well as for engineers. This is a textbook with extensive examples and references. Most methods are given in the form of an algorithm that enables a direct implementation in a programme. Comparisons among different methods are included when possible.
Mechanical design of DNA nanostructures
Castro, Carlos E.; Su, Hai-Jun; Marras, Alexander E.; Zhou, Lifeng; Johnson, Joshua
2015-03-01
Structural DNA nanotechnology is a rapidly emerging field that has demonstrated great potential for applications such as single molecule sensing, drug delivery, and templating molecular components. As the applications of DNA nanotechnology expand, a consideration of their mechanical behavior is becoming essential to understand how these structures will respond to physical interactions. This review considers three major avenues of recent progress in this area: (1) measuring and designing mechanical properties of DNA nanostructures, (2) designing complex nanostructures based on imposed mechanical stresses, and (3) designing and controlling structurally dynamic nanostructures. This work has laid the foundation for mechanically active nanomachines that can generate, transmit, and respond to physical cues in molecular systems.Structural DNA nanotechnology is a rapidly emerging field that has demonstrated great potential for applications such as single molecule sensing, drug delivery, and templating molecular components. As the applications of DNA nanotechnology expand, a consideration of their mechanical behavior is becoming essential to understand how these structures will respond to physical interactions. This review considers three major avenues of recent progress in this area: (1) measuring and designing mechanical properties of DNA nanostructures, (2) designing complex nanostructures based on imposed mechanical stresses, and (3) designing and controlling structurally dynamic nanostructures. This work has laid the foundation for mechanically active nanomachines that can generate, transmit, and respond to physical cues in molecular systems. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr07153k
The Great Deluge Algorithm applied to a nuclear reactor core design optimization problem
International Nuclear Information System (INIS)
Sacco, Wagner F.; Oliveira, Cassiano R.E. de
2005-01-01
The Great Deluge Algorithm (GDA) is a local search algorithm introduced by Dueck. It is an analogy with a flood: the 'water level' rises continuously and the proposed solution must lie above the 'surface' in order to survive. The crucial parameter is the 'rain speed', which controls convergence of the algorithm similarly to Simulated Annealing's annealing schedule. This algorithm is applied to the reactor core design optimization problem, which consists in adjusting several reactor cell parameters, such as dimensions, enrichment and materials, in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering restrictions on the average thermal flux, criticality and sub-moderation. This problem was previously attacked by the canonical genetic algorithm (GA) and by a Niching Genetic Algorithm (NGA). NGAs were designed to force the genetic algorithm to maintain a heterogeneous population throughout the evolutionary process, avoiding the phenomenon known as genetic drift, where all the individuals converge to a single solution. The results obtained by the Great Deluge Algorithm are compared to those obtained by both algorithms mentioned above. The three algorithms are submitted to the same computational effort and GDA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem. One of the great advantages of this algorithm over the GA is that it does not require special operators for discrete optimization. (author)
Directory of Open Access Journals (Sweden)
Hyo Seon Park
2014-01-01
Full Text Available Since genetic algorithm-based optimization methods are computationally expensive for practical use in the field of structural optimization, a resizing technique-based hybrid genetic algorithm for the drift design of multistory steel frame buildings is proposed to increase the convergence speed of genetic algorithms. To reduce the number of structural analyses required for the convergence, a genetic algorithm is combined with a resizing technique that is an efficient optimal technique to control the drift of buildings without the repetitive structural analysis. The resizing technique-based hybrid genetic algorithm proposed in this paper is applied to the minimum weight design of three steel frame buildings. To evaluate the performance of the algorithm, optimum weights, computational times, and generation numbers from the proposed algorithm are compared with those from a genetic algorithm. Based on the comparisons, it is concluded that the hybrid genetic algorithm shows clear improvements in convergence properties.
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
Long, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris
2000-01-01
Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency
Lapidoth, Gideon D; Baran, Dror; Pszolla, Gabriele M; Norn, Christoffer; Alon, Assaf; Tyka, Michael D; Fleishman, Sarel J
2015-08-01
Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function--essential to exert control over all polypeptide degrees of freedom--remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in five cases interface sequence identity is above 30%, and in four of those the backbone conformation at the core of the antibody binding surface is within 1 Å root-mean square deviation from the natural antibodies. Designs recapitulate polar interaction networks observed in natural complexes, and amino acid sidechain rigidity at the designed binding surface, which is likely important for affinity and specificity, is high compared to previous design studies. In designed anti-lysozyme antibodies, complementarity-determining regions (CDRs) at the periphery of the interface, such as L1 and H2, show greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, potentially enhancing affinity and specificity. © 2015 Wiley Periodicals, Inc.
Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm
Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui
2017-05-01
The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.
Aiyoshi, Eitaro; Masuda, Kazuaki
On the basis of market fundamentalism, new types of social systems with the market mechanism such as electricity trading markets and carbon dioxide (CO2) emission trading markets have been developed. However, there are few textbooks in science and technology which present the explanation that Lagrange multipliers can be interpreted as market prices. This tutorial paper explains that (1) the steepest descent method for dual problems in optimization, and (2) Gauss-Seidel method for solving the stationary conditions of Lagrange problems with market principles, can formulate the mechanism of market pricing, which works even in the information-oriented modern society. The authors expect readers to acquire basic knowledge on optimization theory and algorithms related to economics and to utilize them for designing the mechanism of more complicated markets.
Optimal design of link systems using successive zooming genetic algorithm
Kwon, Young-Doo; Sohn, Chang-hyun; Kwon, Soon-Bum; Lim, Jae-gyoo
2009-07-01
Link-systems have been around for a long time and are still used to control motion in diverse applications such as automobiles, robots and industrial machinery. This study presents a procedure involving the use of a genetic algorithm for the optimal design of single four-bar link systems and a double four-bar link system used in diesel engine. We adopted the Successive Zooming Genetic Algorithm (SZGA), which has one of the most rapid convergence rates among global search algorithms. The results are verified by experiment and the Recurdyn dynamic motion analysis package. During the optimal design of single four-bar link systems, we found in the case of identical input/output (IO) angles that the initial and final configurations show certain symmetry. For the double link system, we introduced weighting factors for the multi-objective functions, which minimize the difference between output angles, providing balanced engine performance, as well as the difference between final output angle and the desired magnitudes of final output angle. We adopted a graphical method to select a proper ratio between the weighting factors.
OSPREY: protein design with ensembles, flexibility, and provable algorithms.
Gainza, Pablo; Roberts, Kyle E; Georgiev, Ivelin; Lilien, Ryan H; Keedy, Daniel A; Chen, Cheng-Yu; Reza, Faisal; Anderson, Amy C; Richardson, David C; Richardson, Jane S; Donald, Bruce R
2013-01-01
We have developed a suite of protein redesign algorithms that improves realistic in silico modeling of proteins. These algorithms are based on three characteristics that make them unique: (1) improved flexibility of the protein backbone, protein side-chains, and ligand to accurately capture the conformational changes that are induced by mutations to the protein sequence; (2) modeling of proteins and ligands as ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal protein design search, guaranteeing that the computational predictions are optimal with respect to the input model. Here, we illustrate the importance of these three characteristics. We then describe OSPREY, a protein redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental validation, in several biomedically relevant settings. We show in detail how OSPREY has been used to predict resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application. OSPREY is free and open source under a Lesser GPL license. The latest version is OSPREY 2.0. The program, user manual, and source code are available at www.cs.duke.edu/donaldlab/software.php. osprey@cs.duke.edu. Copyright © 2013 Elsevier Inc. All rights reserved.
Foundations of digital signal processing theory, algorithms and hardware design
Gaydecki, Patrick
2005-01-01
An excellent introductory text, this book covers the basic theoretical, algorithmic and real-time aspects of digital signal processing (DSP). Detailed information is provided on off-line, real-time and DSP programming and the reader is effortlessly guided through advanced topics such as DSP hardware design, FIR and IIR filter design and difference equation manipulation.
CAS algorithm-based optimum design of PID controller in AVR system
International Nuclear Information System (INIS)
Zhu Hui; Li Lixiang; Zhao Ying; Guo Yu; Yang Yixian
2009-01-01
This paper presents a novel design method for determining the optimal PID controller parameters of an automatic voltage regulator (AVR) system using the chaotic ant swarm (CAS) algorithm. In the tuning process of parameters, the CAS algorithm is iterated to give the optimal parameters of the PID controller based on the fitness theory, where the position vector of each ant in the CAS algorithm corresponds to the parameter vector of the PID controller. The proposed CAS-PID controllers can ensure better control system performance with respect to the reference input in comparison with GA-PID controllers. Numerical simulations are provided to verify the effectiveness and feasibility of PID controller based on CAS algorithm.
Advanced hybrid query tree algorithm based on slotted backoff mechanism in RFID
Directory of Open Access Journals (Sweden)
XIE Xiaohui
2013-12-01
Full Text Available The merits of performance quality for a RFID system are determined by the effectiveness of tag anti-collision algorithm.Many algorithms for RFID system of tag identification have been proposed,but they all have obvious weaknesses,such as slow speed of identification,unstable and so on.The existing algorithms can be divided into two groups,one is based on ALOHA and another is based on query tree.This article is based on the hybrid query tree algorithm,combined with a slotted backoff mechanism and a specific encoding (Manchester encoding.The number of value“1” in every three consecutive bits of tags is used to determine the tag response time slots,which will greatly reduce the time slot of the collision and improve the recognition efficiency.
ALGORITHMIC FACILITIES AND SOFTWARE FOR VIRTUAL DESIGN OF ANTI-BLOCK AND COUNTER-SLIPPING SYSTEMS
Directory of Open Access Journals (Sweden)
N. N. Hurski
2009-01-01
Full Text Available The paper considers algorithms of designing a roadway covering for virtual test of mobile machine movement dynamics; an algorithm of forming actual values of forces/moments in «road–wheel–car» contact and their derivatives, and also a software for virtual designing of mobile machine dynamics.
An algorithm for the design and tuning of RF accelerating structures with variable cell lengths
Lal, Shankar; Pant, K. K.
2018-05-01
An algorithm is proposed for the design of a π mode standing wave buncher structure with variable cell lengths. It employs a two-parameter, multi-step approach for the design of the structure with desired resonant frequency and field flatness. The algorithm, along with analytical scaling laws for the design of the RF power coupling slot, makes it possible to accurately design the structure employing a freely available electromagnetic code like SUPERFISH. To compensate for machining errors, a tuning method has been devised to achieve desired RF parameters for the structure, which has been qualified by the successful tuning of a 7-cell buncher to π mode frequency of 2856 MHz with field flatness algorithm and tuning method have demonstrated the feasibility of developing an S-band accelerating structure for desired RF parameters with a relatively relaxed machining tolerance of ∼ 25 μm. This paper discusses the algorithm for the design and tuning of an RF accelerating structure with variable cell lengths.
Optimized design of embedded DSP system hardware supporting complex algorithms
Li, Yanhua; Wang, Xiangjun; Zhou, Xinling
2003-09-01
The paper presents an optimized design method for a flexible and economical embedded DSP system that can implement complex processing algorithms as biometric recognition, real-time image processing, etc. It consists of a floating-point DSP, 512 Kbytes data RAM, 1 Mbytes FLASH program memory, a CPLD for achieving flexible logic control of input channel and a RS-485 transceiver for local network communication. Because of employing a high performance-price ratio DSP TMS320C6712 and a large FLASH in the design, this system permits loading and performing complex algorithms with little algorithm optimization and code reduction. The CPLD provides flexible logic control for the whole DSP board, especially in input channel, and allows convenient interface between different sensors and DSP system. The transceiver circuit can transfer data between DSP and host computer. In the paper, some key technologies are also introduced which make the whole system work efficiently. Because of the characters referred above, the hardware is a perfect flat for multi-channel data collection, image processing, and other signal processing with high performance and adaptability. The application section of this paper presents how this hardware is adapted for the biometric identification system with high identification precision. The result reveals that this hardware is easy to interface with a CMOS imager and is capable of carrying out complex biometric identification algorithms, which require real-time process.
Design and Large-Scale Evaluation of Educational Games for Teaching Sorting Algorithms
Battistella, Paulo Eduardo; von Wangenheim, Christiane Gresse; von Wangenheim, Aldo; Martina, Jean Everson
2017-01-01
The teaching of sorting algorithms is an essential topic in undergraduate computing courses. Typically the courses are taught through traditional lectures and exercises involving the implementation of the algorithms. As an alternative, this article presents the design and evaluation of three educational games for teaching Quicksort and Heapsort.…
Mechanical design of machine components
Ugural, Ansel C
2015-01-01
Mechanical Design of Machine Components, Second Edition strikes a balance between theory and application, and prepares students for more advanced study or professional practice. It outlines the basic concepts in the design and analysis of machine elements using traditional methods, based on the principles of mechanics of materials. The text combines the theory needed to gain insight into mechanics with numerical methods in design. It presents real-world engineering applications, and reveals the link between basic mechanics and the specific design of machine components and machines. Divided into three parts, this revised text presents basic background topics, deals with failure prevention in a variety of machine elements and covers applications in design of machine components as well as entire machines. Optional sections treating special and advanced topics are also included.Key Features of the Second Edition:Incorporates material that has been completely updated with new chapters, problems, practical examples...
International Nuclear Information System (INIS)
Ohtsuki, Yukiyoshi
2010-01-01
In this paper, molecular quantum computation is numerically studied with the quantum search algorithm (Grover's algorithm) by means of optimal control simulation. Qubits are implemented in the vibronic states of I 2 , while gate operations are realized by optimally designed laser pulses. The methodological aspects of the simulation are discussed in detail. We show that the algorithm for solving a gate pulse-design problem has the same mathematical form as a state-to-state control problem in the density matrix formalism, which provides monotonically convergent algorithms as an alternative to the Krotov method. The sequential irradiation of separately designed gate pulses leads to the population distribution predicted by Grover's algorithm. The computational accuracy is reduced by the imperfect quality of the pulse design and by the electronic decoherence processes that are modeled by the non-Markovian master equation. However, as long as we focus on the population distribution of the vibronic qubits, we can search a target state with high probability without introducing error-correction processes during the computation. A generalized gate pulse-design scheme to explicitly include decoherence effects is outlined, in which we propose a new objective functional together with its solution algorithm that guarantees monotonic convergence.
Automatic design of decision-tree induction algorithms tailored to flexible-receptor docking data.
Barros, Rodrigo C; Winck, Ana T; Machado, Karina S; Basgalupp, Márcio P; de Carvalho, André C P L F; Ruiz, Duncan D; de Souza, Osmar Norberto
2012-11-21
This paper addresses the prediction of the free energy of binding of a drug candidate with enzyme InhA associated with Mycobacterium tuberculosis. This problem is found within rational drug design, where interactions between drug candidates and target proteins are verified through molecular docking simulations. In this application, it is important not only to correctly predict the free energy of binding, but also to provide a comprehensible model that could be validated by a domain specialist. Decision-tree induction algorithms have been successfully used in drug-design related applications, specially considering that decision trees are simple to understand, interpret, and validate. There are several decision-tree induction algorithms available for general-use, but each one has a bias that makes it more suitable for a particular data distribution. In this article, we propose and investigate the automatic design of decision-tree induction algorithms tailored to particular drug-enzyme binding data sets. We investigate the performance of our new method for evaluating binding conformations of different drug candidates to InhA, and we analyze our findings with respect to decision tree accuracy, comprehensibility, and biological relevance. The empirical analysis indicates that our method is capable of automatically generating decision-tree induction algorithms that significantly outperform the traditional C4.5 algorithm with respect to both accuracy and comprehensibility. In addition, we provide the biological interpretation of the rules generated by our approach, reinforcing the importance of comprehensible predictive models in this particular bioinformatics application. We conclude that automatically designing a decision-tree algorithm tailored to molecular docking data is a promising alternative for the prediction of the free energy from the binding of a drug candidate with a flexible-receptor.
Majorization arrow in quantum-algorithm design
International Nuclear Information System (INIS)
Latorre, J.I.; Martin-Delgado, M.A.
2002-01-01
We apply majorization theory to study the quantum algorithms known so far and find that there is a majorization principle underlying the way they operate. Grover's algorithm is a neat instance of this principle where majorization works step by step until the optimal target state is found. Extensions of this situation are also found in algorithms based in quantum adiabatic evolution and the family of quantum phase-estimation algorithms, including Shor's algorithm. We state that in quantum algorithms the time arrow is a majorization arrow
High Precision Edge Detection Algorithm for Mechanical Parts
Directory of Open Access Journals (Sweden)
Duan Zhenyun
2018-04-01
Full Text Available High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.
Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers.
Church, Philip C; Goscinski, Andrzej; Holt, Kathryn; Inouye, Michael; Ghoting, Amol; Makarychev, Konstantin; Reumann, Matthias
2011-01-01
The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.
Design Optimization of Space Launch Vehicles Using a Genetic Algorithm
National Research Council Canada - National Science Library
Bayley, Douglas J
2007-01-01
.... A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost...
Directory of Open Access Journals (Sweden)
Chung-Ta Li
2014-01-01
Full Text Available We propose a species-based hybrid of the electromagnetism-like mechanism (EM and back-propagation algorithms (SEMBP for an interval type-2 fuzzy neural system with asymmetric membership functions (AIT2FNS design. The interval type-2 asymmetric fuzzy membership functions (IT2 AFMFs and the TSK-type consequent part are adopted to implement the network structure in AIT2FNS. In addition, the type reduction procedure is integrated into an adaptive network structure to reduce computational complexity. Hence, the AIT2FNS can enhance the approximation accuracy effectively by using less fuzzy rules. The AIT2FNS is trained by the SEMBP algorithm, which contains the steps of uniform initialization, species determination, local search, total force calculation, movement, and evaluation. It combines the advantages of EM and back-propagation (BP algorithms to attain a faster convergence and a lower computational complexity. The proposed SEMBP algorithm adopts the uniform method (which evenly scatters solution agents over the feasible solution region and the species technique to improve the algorithm’s ability to find the global optimum. Finally, two illustrative examples of nonlinear systems control are presented to demonstrate the performance and the effectiveness of the proposed AIT2FNS with the SEMBP algorithm.
Reactor controller design using genetic algorithm with simulated annealing
International Nuclear Information System (INIS)
Willjuice Iruthyarajan, M.
2012-01-01
Many reactor control design work, specifically the problem of synthesis and optimization of reactor networks involving the classical reaction schemes was studied, considering a superstructure formed by a CSTR and a PFR and their possible arrangements. A genetic algorithm was proposed, together with a systematic procedure. Two case studies were solved with the proposed systematic. Both of them present similar results than the published in the literature. The first case studied was the Trambouze reaction scheme. Although selectivity values are smaller then the values published in the referred papers, the reactors system combined volume is always minor them the other ones. The second case studied was the Van de Vusse reaction scheme. In this case, the obtained value for the total volume is always minor then the considered papers. One can conclude that when compared with the other works presented in the literature results are compatible and very interesting. The developed algorithms can be used as a good alternative for reactor networks design and optimization problem
Verifiably Truthful Mechanisms
DEFF Research Database (Denmark)
Branzei, Simina; Procaccia, Ariel D.
2015-01-01
the computational sense). Our approach involves three steps: (i) specifying the structure of mechanisms, (ii) constructing a verification algorithm, and (iii) measuring the quality of verifiably truthful mechanisms. We demonstrate this approach using a case study: approximate mechanism design without money...
Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm
Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung
2016-07-01
In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.
A novel method to design S-box based on chaotic map and genetic algorithm
International Nuclear Information System (INIS)
Wang, Yong; Wong, Kwok-Wo; Li, Changbing; Li, Yang
2012-01-01
The substitution box (S-box) is an important component in block encryption algorithms. In this Letter, the problem of constructing S-box is transformed to a Traveling Salesman Problem and a method for designing S-box based on chaos and genetic algorithm is proposed. Since the proposed method makes full use of the traits of chaotic map and evolution process, stronger S-box is obtained. The results of performance test show that the presented S-box has good cryptographic properties, which justify that the proposed algorithm is effective in generating strong S-boxes. -- Highlights: ► The problem of constructing S-box is transformed to a Traveling Salesman Problem. ► We present a new method for designing S-box based on chaos and genetic algorithm. ► The proposed algorithm is effective in generating strong S-boxes.
A novel method to design S-box based on chaotic map and genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Wang, Yong, E-mail: wangyong_cqupt@163.com [State Key Laboratory of Power Transmission Equipment and System Security and New Technology, Chongqing University, Chongqing 400044 (China); Key Laboratory of Electronic Commerce and Logistics, Chongqing University of Posts and Telecommunications, Chongqing 400065 (China); Wong, Kwok-Wo [Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong (Hong Kong); Li, Changbing [Key Laboratory of Electronic Commerce and Logistics, Chongqing University of Posts and Telecommunications, Chongqing 400065 (China); Li, Yang [Department of Automatic Control and Systems Engineering, The University of Sheffield, Mapping Street, S1 3DJ (United Kingdom)
2012-01-30
The substitution box (S-box) is an important component in block encryption algorithms. In this Letter, the problem of constructing S-box is transformed to a Traveling Salesman Problem and a method for designing S-box based on chaos and genetic algorithm is proposed. Since the proposed method makes full use of the traits of chaotic map and evolution process, stronger S-box is obtained. The results of performance test show that the presented S-box has good cryptographic properties, which justify that the proposed algorithm is effective in generating strong S-boxes. -- Highlights: ► The problem of constructing S-box is transformed to a Traveling Salesman Problem. ► We present a new method for designing S-box based on chaos and genetic algorithm. ► The proposed algorithm is effective in generating strong S-boxes.
Design of Supply Chain Networks with Supply Disruptions using Genetic Algorithm
Taha, Raghda; Abdallah, Khaled; Sadek, Yomma; El-Kharbotly, Amin; Afia, Nahid
2014-01-01
The design of supply chain networks subject to disruptions is tackled. A genetic algorithm with the objective of minimizing the design cost and regret cost is developed to achieve a reliable supply chain network. The improvement of supply chain network reliability is measured against the supply chain cost.
Gravitation search algorithm: Application to the optimal IIR filter design
Directory of Open Access Journals (Sweden)
Suman Kumar Saha
2014-01-01
Full Text Available This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA for the design of 8th order Infinite Impulse Response (IIR, low pass (LP, high pass (HP, band pass (BP and band stop (BS filters considering various non-linear characteristics of the filter design problems. This paper also adopts a novel fitness function in order to improve the stop band attenuation to a great extent. In GSA, law of gravity and mass interactions among different particles are adopted for handling the non-linear IIR filter design optimization problem. In this optimization technique, searcher agents are the collection of masses and interactions among them are governed by the Newtonian gravity and the laws of motion. The performances of the GSA based IIR filter designs have proven to be superior as compared to those obtained by real coded genetic algorithm (RGA and standard Particle Swarm Optimization (PSO. Extensive simulation results affirm that the proposed approach using GSA outperforms over its counterparts not only in terms of quality output, i.e., sharpness at cut-off, smaller pass band ripple, higher stop band attenuation, but also the fastest convergence speed with assured stability.
A robust controller design method for feedback substitution schemes using genetic algorithms
Energy Technology Data Exchange (ETDEWEB)
Trujillo, Mirsha M; Hadjiloucas, Sillas; Becerra, Victor M, E-mail: s.hadjiloucas@reading.ac.uk [Cybernetics, School of Systems Engineering, University of Reading, RG6 6AY (United Kingdom)
2011-08-17
Controllers for feedback substitution schemes demonstrate a trade-off between noise power gain and normalized response time. Using as an example the design of a controller for a radiometric transduction process subjected to arbitrary noise power gain and robustness constraints, a Pareto-front of optimal controller solutions fulfilling a range of time-domain design objectives can be derived. In this work, we consider designs using a loop shaping design procedure (LSDP). The approach uses linear matrix inequalities to specify a range of objectives and a genetic algorithm (GA) to perform a multi-objective optimization for the controller weights (MOGA). A clonal selection algorithm is used to further provide a directed search of the GA towards the Pareto front. We demonstrate that with the proposed methodology, it is possible to design higher order controllers with superior performance in terms of response time, noise power gain and robustness.
Directory of Open Access Journals (Sweden)
Ali Akbar Hasani
2016-11-01
Full Text Available In this paper, a comprehensive model is proposed to design a network for multi-period, multi-echelon, and multi-product inventory controlled the supply chain. Various marketing strategies and guerrilla marketing approaches are considered in the design process under the static competition condition. The goal of the proposed model is to efficiently respond to the customers’ demands in the presence of the pre-existing competitors and the price inelasticity of demands. The proposed optimization model considers multiple objectives that incorporate both market share and total profit of the considered supply chain network, simultaneously. To tackle the proposed multi-objective mixed-integer nonlinear programming model, an efficient hybrid meta-heuristic algorithm is developed that incorporates a Taguchi-based non-dominated sorting genetic algorithm-II and a particle swarm optimization. A variable neighborhood decomposition search is applied to enhance a local search process of the proposed hybrid solution algorithm. Computational results illustrate that the proposed model and solution algorithm are notably efficient in dealing with the competitive pressure by adopting the proper marketing strategies.
Directory of Open Access Journals (Sweden)
Kazem Mohammadi- Aghdam
2015-10-01
Full Text Available This paper proposes the application of a new version of the heuristic particle swarm optimization (PSO method for designing water distribution networks (WDNs. The optimization problem of looped water distribution networks is recognized as an NP-hard combinatorial problem which cannot be easily solved using traditional mathematical optimization techniques. In this paper, the concept of dynamic swarm size is considered in an attempt to increase the convergence speed of the original PSO algorithm. In this strategy, the size of the swarm is dynamically changed according to the iteration number of the algorithm. Furthermore, a novel mutation approach is introduced to increase the diversification property of the PSO and to help the algorithm to avoid trapping in local optima. The new version of the PSO algorithm is called dynamic mutated particle swarm optimization (DMPSO. The proposed DMPSO is then applied to solve WDN design problems. Finally, two illustrative examples are used for comparison to verify the efficiency of the proposed DMPSO as compared to other intelligent algorithms.
Multiobjective pressurized water reactor reload core design by nondominated genetic algorithm search
International Nuclear Information System (INIS)
Parks, G.T.
1996-01-01
The design of pressurized water reactor reload cores is not only a formidable optimization problem but also, in many instances, a multiobjective problem. A genetic algorithm (GA) designed to perform true multiobjective optimization on such problems is described. Genetic algorithms simulate natural evolution. They differ from most optimization techniques by searching from one group of solutions to another, rather than from one solution to another. New solutions are generated by breeding from existing solutions. By selecting better (in a multiobjective sense) solutions as parents more often, the population can be evolved to reveal the trade-off surface between the competing objectives. An example illustrating the effectiveness of this novel method is presented and analyzed. It is found that in solving a reload design problem the algorithm evaluates a similar number of loading patterns to other state-of-the-art methods, but in the process reveals much more information about the nature of the problem being solved. The actual computational cost incurred depends on the core simulator used; the GA itself is code independent
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Design considerations for mechanical snubbers
International Nuclear Information System (INIS)
Severud, L.K.; Summers, G.D.
1980-03-01
The use of mechanical snubbers to restrain piping during an earthquake event is becoming more common in design of nuclear power plants. The design considerations and qualification procedures for mechanical snubbers used on the Fast Flux Test Facility will be presented. Design precautions and requirements for both normal operation and seismic operation are necessary. Effects of environmental vibration (nonseismic) induced through the piping by pump shaft imbalance and fluid flow oscillations will be addressed. Also, the snubber dynamic characteristics of interest to design and snubber design application considerations will be discussed
Optimization design for the stepped impedance transformer based on the genetic algorithm
International Nuclear Information System (INIS)
Zou Dehui; Lai Wanchang; Qiu Dong
2007-01-01
This paper introduces the basic principium and mathematic model of the stepped impedance transformer, then puts the emphasis on comparing two kinds of design methods of the stepped impedance transformer. The design results are simulated by EDA, which indicates that genetic algorithm design is better than Chebyshev integrated design in the term of the most reflect coefficient's module. (authors)
A Novel Adaptive Particle Swarm Optimization Algorithm with Foraging Behavior in Optimization Design
Directory of Open Access Journals (Sweden)
Liu Yan
2018-01-01
Full Text Available The method of repeated trial and proofreading is generally used to the convention reducer design, but these methods is low efficiency and the size of the reducer is often large. Aiming the problems, this paper presents an adaptive particle swarm optimization algorithm with foraging behavior, in this method, the bacterial foraging process is introduced into the adaptive particle swarm optimization algorithm, which can provide the function of particle chemotaxis, swarming, reproduction, elimination and dispersal, to improve the ability of local search and avoid premature behavior. By test verification through typical function and the application of the optimization design in the structure of the reducer with discrete and continuous variables, the results are shown that the new algorithm has the advantages of good reliability, strong searching ability and high accuracy. It can be used in engineering design, and has a strong applicability.
Design of 2-D Recursive Filters Using Self-adaptive Mutation Differential Evolution Algorithm
Directory of Open Access Journals (Sweden)
Lianghong Wu
2011-08-01
Full Text Available This paper investigates a novel approach to the design of two-dimensional recursive digital filters using differential evolution (DE algorithm. The design task is reformulated as a constrained minimization problem and is solved by an Self-adaptive Mutation DE algorithm (SAMDE, which adopts an adaptive mutation operator that combines with the advantages of the DE/rand/1/bin strategy and the DE/best/2/bin strategy. As a result, its convergence performance is improved greatly. Numerical experiment results confirm the conclusion. The proposedSAMDE approach is effectively applied to test a numerical example and is compared with previous design methods. The computational experiments show that the SAMDE approach can obtain better results than previous design methods.
Reasoning about Grover's Quantum Search Algorithm using Probabilistic wp
Butler, M.J.; Hartel, Pieter H.
Grover's search algorithm is designed to be executed on a quantum mechanical computer. In this paper, the probabilistic wp-calculus is used to model and reason about Grover's algorithm. It is demonstrated that the calculus provides a rigorous programming notation for modelling this and other quantum
Energy-aware system design algorithms and architectures
Kyung, Chong-Min
2011-01-01
Power consumption becomes the most important design goal in a wide range of electronic systems. There are two driving forces towards this trend: continuing device scaling and ever increasing demand of higher computing power. First, device scaling continues to satisfy Moore’s law via a conventional way of scaling (More Moore) and a new way of exploiting the vertical integration (More than Moore). Second, mobile and IT convergence requires more computing power on the silicon chip than ever. Cell phones are now evolving towards mobile PC. PCs and data centers are becoming commodities in house and a must in industry. Both supply enabled by device scaling and demand triggered by the convergence trend realize more computation on chip (via multi-core, integration of diverse functionalities on mobile SoCs, etc.) and finally more power consumption incurring power-related issues and constraints. Energy-Aware System Design: Algorithms and Architectures provides state-of-the-art ideas for low power design methods from ...
Deformation mechanisms in ferritic/martensitic steels and the impact on mechanical design
International Nuclear Information System (INIS)
Ghoniem, Nasr M.; Po, Giacomo; Sharafat, Shahram
2013-01-01
Structural steels for nuclear applications have undergone rapid development during the past few decades, thanks to a combination of trial-and-error, mechanism-based optimization, and multiscale modeling approaches. Deformation mechanisms are shown to be intimately related to mechanical design via dominant plastic deformation modes. Because mechanical design rules are mostly based on failure modes associated with plastic strain damage accumulation, we present here the fundamental deformation mechanisms for Ferritic/Martensitic (F/M) steels, and delineate their operational range of temperature and stress. The connection between deformation mechanisms, failure modes, and mechanical design is shown through application of design rules. A specific example is given for the alloy F82H utilized in the design of a Test Blanket Module (TBM) in the International Thermonuclear Experimental Reactor (ITER), where several constitutive equations are developed for design-related mechanical properties
Deformation mechanisms in ferritic/martensitic steels and the impact on mechanical design
Energy Technology Data Exchange (ETDEWEB)
Ghoniem, Nasr M., E-mail: ghoniem@seas.ucla.edu; Po, Giacomo; Sharafat, Shahram
2013-10-15
Structural steels for nuclear applications have undergone rapid development during the past few decades, thanks to a combination of trial-and-error, mechanism-based optimization, and multiscale modeling approaches. Deformation mechanisms are shown to be intimately related to mechanical design via dominant plastic deformation modes. Because mechanical design rules are mostly based on failure modes associated with plastic strain damage accumulation, we present here the fundamental deformation mechanisms for Ferritic/Martensitic (F/M) steels, and delineate their operational range of temperature and stress. The connection between deformation mechanisms, failure modes, and mechanical design is shown through application of design rules. A specific example is given for the alloy F82H utilized in the design of a Test Blanket Module (TBM) in the International Thermonuclear Experimental Reactor (ITER), where several constitutive equations are developed for design-related mechanical properties.
Designing algorithms using CAD technologies
Directory of Open Access Journals (Sweden)
Alin IORDACHE
2008-01-01
Full Text Available A representative example of eLearning-platform modular application, Ã¢Â€Â˜Logical diagramsÃ¢Â€Â™, is intended to be a useful learning and testing tool for the beginner programmer, but also for the more experienced one. The problem this application is trying to solve concerns young programmers who forget about the fundamentals of this domain, algorithmic. Logical diagrams are a graphic representation of an algorithm, which uses different geometrical figures (parallelograms, rectangles, rhombuses, circles with particular meaning that are called blocks and connected between them to reveal the flow of the algorithm. The role of this application is to help the user build the diagram for the algorithm and then automatically generate the C code and test it.
Thomson, Martin J.; Waddie, Andrew J.; Taghizadeh, Mohammad R.
2006-04-01
We present a genetic algorithm with small population sizes for the design of diffraction gratings in the rigorous domain. A general crossover and mutation scheme is defined, forming fifteen offspring from 3 parents, which enables the algorithm to be used for designing gratings with diverse optical properties by careful definition of the merit function. The initial parents are randomly selected and the parents of the subsequent generations are selected by survival of the fittest. The performance of the algorithm is demonstrated by designing diffraction gratings with specific application to high power laser beam lines. Gratings are designed that act as beam deflectors, polarisers, polarising beam splitters, harmonic separation gratings and pulse compression gratings. By imposing fabrication constraints within the design process, we determine which of these elements have true potential for application within high power laser beam lines.
Directory of Open Access Journals (Sweden)
Y. Gholipour
Full Text Available This paper focuses on a metamodel-based design optimization algorithm. The intention is to improve its computational cost and convergence rate. Metamodel-based optimization method introduced here, provides the necessary means to reduce the computational cost and convergence rate of the optimization through a surrogate. This algorithm is a combination of a high quality approximation technique called Inverse Distance Weighting and a meta-heuristic algorithm called Harmony Search. The outcome is then polished by a semi-tabu search algorithm. This algorithm adopts a filtering system and determines solution vectors where exact simulation should be applied. The performance of the algorithm is evaluated by standard truss design problems and there has been a significant decrease in the computational effort and improvement of convergence rate.
An Improved Fruit Fly Optimization Algorithm Inspired from Cell Communication Mechanism
Directory of Open Access Journals (Sweden)
Chuncai Xiao
2015-01-01
Full Text Available Fruit fly optimization algorithm (FOA invented recently is a new swarm intelligence method based on fruit fly’s foraging behaviors and has been shown to be competitive with existing evolutionary algorithms, such as particle swarm optimization (PSO algorithm. However, there are still some disadvantages in the FOA, such as low convergence precision, easily trapped in a local optimum value at the later evolution stage. This paper presents an improved FOA based on the cell communication mechanism (CFOA, by considering the information of the global worst, mean, and best solutions into the search strategy to improve the exploitation. The results from a set of numerical benchmark functions show that the CFOA outperforms the FOA and the PSO in most of the experiments. Further, the CFOA is applied to optimize the controller for preoxidation furnaces in carbon fibers production. Simulation results demonstrate the effectiveness of the CFOA.
Directory of Open Access Journals (Sweden)
Abdulbaset El Hadi Saad
2017-10-01
Full Text Available Advanced global optimization algorithms have been continuously introduced and improved to solve various complex design optimization problems for which the objective and constraint functions can only be evaluated through computation intensive numerical analyses or simulations with a large number of design variables. The often implicit, multimodal, and ill-shaped objective and constraint functions in high-dimensional and “black-box” forms demand the search to be carried out using low number of function evaluations with high search efficiency and good robustness. This work investigates the performance of six recently introduced, nature-inspired global optimization methods: Artificial Bee Colony (ABC, Firefly Algorithm (FFA, Cuckoo Search (CS, Bat Algorithm (BA, Flower Pollination Algorithm (FPA and Grey Wolf Optimizer (GWO. These approaches are compared in terms of search efficiency and robustness in solving a set of representative benchmark problems in smooth-unimodal, non-smooth unimodal, smooth multimodal, and non-smooth multimodal function forms. In addition, four classic engineering optimization examples and a real-life complex mechanical system design optimization problem, floating offshore wind turbines design optimization, are used as additional test cases representing computationally-expensive black-box global optimization problems. Results from this comparative study show that the ability of these global optimization methods to obtain a good solution diminishes as the dimension of the problem, or number of design variables increases. Although none of these methods is universally capable, the study finds that GWO and ABC are more efficient on average than the other four in obtaining high quality solutions efficiently and consistently, solving 86% and 80% of the tested benchmark problems, respectively. The research contributes to future improvements of global optimization methods.
Directory of Open Access Journals (Sweden)
Xie Xiang
2007-01-01
Full Text Available In order to decrease the communication bandwidth and save the transmitting power in the wireless endoscopy capsule, this paper presents a new near-lossless image compression algorithm based on the Bayer format image suitable for hardware design. This algorithm can provide low average compression rate ( bits/pixel with high image quality (larger than dB for endoscopic images. Especially, it has low complexity hardware overhead (only two line buffers and supports real-time compressing. In addition, the algorithm can provide lossless compression for the region of interest (ROI and high-quality compression for other regions. The ROI can be selected arbitrarily by varying ROI parameters. In addition, the VLSI architecture of this compression algorithm is also given out. Its hardware design has been implemented in m CMOS process.
MICRONEEDLE STRUCTURE DESIGN AND OPTIMIZATION USING GENETIC ALGORITHM
Directory of Open Access Journals (Sweden)
N. A. ISMAIL
2015-07-01
Full Text Available This paper presents a Genetic Algorithm (GA based microneedle design and analysis. GA is an evolutionary optimization technique that mimics the natural biological evolution. The design of microneedle structure considers the shape of microneedle, material used, size of the array, the base of microneedle, the lumen base, the height of microneedle, the height of the lumen, and the height of the drug container or reservoir. The GA is executed in conjunction with ANSYS simulation system to assess the design specifications. The GA uses three operators which are reproduction, crossover and mutation to manipulate the genetic composition of the population. In this research, the microneedle is designed to meet a number of significant specifications such as nodal displacement, strain energy, equivalent stress and flow rate of the fluid / drug that flow through its channel / lumen. A comparison study is conducted to investigate the design of microneedle structure with and without the implementation of GA model. The results showed that GA is able to optimize the design parameters of microneedle and is capable to achieve the required specifications with better performance.
Yang, Yan-Pu; Chen, Deng-Kai; Gu, Rong; Gu, Yu-Feng; Yu, Sui-Huai
2016-01-01
Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design.
Mechanical engineers' handbook, design, instrumentation, and controls
Kutz, Myer
2015-01-01
Full coverage of electronics, MEMS, and instrumentation andcontrol in mechanical engineering This second volume of Mechanical Engineers' Handbookcovers electronics, MEMS, and instrumentation and control, givingyou accessible and in-depth access to the topics you'll encounterin the discipline: computer-aided design, product design formanufacturing and assembly, design optimization, total qualitymanagement in mechanical system design, reliability in themechanical design process for sustainability, life-cycle design,design for remanufacturing processes, signal processing, dataacquisition and dis
Postigo, Sergio; Schmidt, Hendrik; Rohlmann, Antonius; Putzier, Michael; Simón, Antonio; Duda, Georg; Checa, Sara
2014-04-11
Lumbar interbody fusion cages are commonly used to treat painful spinal degeneration and instability by achieving bony fusion. Many different cage designs exist, however the effect of cage morphology and material properties on the fusion process remains largely unknown. This finite element model study aims to investigate the influence of different cage designs on bone fusion using two mechano-regulation algorithms of tissue formation. It could be observed that different cages play a distinct key role in the mechanical conditions within the fusion region and therefore regulate the time course of the fusion process. Copyright © 2014 Elsevier Ltd. All rights reserved.
Natural selection and algorithmic design of mRNA.
Cohen, Barry; Skiena, Steven
2003-01-01
Messenger RNA (mRNA) sequences serve as templates for proteins according to the triplet code, in which each of the 4(3) = 64 different codons (sequences of three consecutive nucleotide bases) in RNA either terminate transcription or map to one of the 20 different amino acids (or residues) which build up proteins. Because there are more codons than residues, there is inherent redundancy in the coding. Certain residues (e.g., tryptophan) have only a single corresponding codon, while other residues (e.g., arginine) have as many as six corresponding codons. This freedom implies that the number of possible RNA sequences coding for a given protein grows exponentially in the length of the protein. Thus nature has wide latitude to select among mRNA sequences which are informationally equivalent, but structurally and energetically divergent. In this paper, we explore how nature takes advantage of this freedom and how to algorithmically design structures more energetically favorable than have been built through natural selection. In particular: (1) Natural Selection--we perform the first large-scale computational experiment comparing the stability of mRNA sequences from a variety of organisms to random synonymous sequences which respect the codon preferences of the organism. This experiment was conducted on over 27,000 sequences from 34 microbial species with 36 genomic structures. We provide evidence that in all genomic structures highly stable sequences are disproportionately abundant, and in 19 of 36 cases highly unstable sequences are disproportionately abundant. This suggests that the stability of mRNA sequences is subject to natural selection. (2) Artificial Selection--motivated by these biological results, we examine the algorithmic problem of designing the most stable and unstable mRNA sequences which code for a target protein. We give a polynomial-time dynamic programming solution to the most stable sequence problem (MSSP), which is asymptotically no more complex
A novel hybrid genetic algorithm for optimal design of IPM machines for electric vehicle
Wang, Aimeng; Guo, Jiayu
2017-12-01
A novel hybrid genetic algorithm (HGA) is proposed to optimize the rotor structure of an IPM machine which is used in EV application. The finite element (FE) simulation results of the HGA design is compared with the genetic algorithm (GA) design and those before optimized. It is shown that the performance of the IPMSM is effectively improved by employing the GA and HGA, especially by HGA. Moreover, higher flux-weakening capability and less magnet usage are also obtained. Therefore, the validity of HGA method in IPMSM optimization design is verified.
Logic hybrid simulation-optimization algorithm for distillation design
Caballero Suárez, José Antonio
2014-01-01
In this paper, we propose a novel algorithm for the rigorous design of distillation columns that integrates a process simulator in a generalized disjunctive programming formulation. The optimal distillation column, or column sequence, is obtained by selecting, for each column section, among a set of column sections with different number of theoretical trays. The selection of thermodynamic models, properties estimation etc., are all in the simulation environment. All the numerical issues relat...
Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm
Pak, Chan-gi; Li, Wesley
2009-01-01
Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) to automate analysis and design process by leveraging existing tools to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic, and hypersonic aircraft. This is a promising technology, but faces many challenges in large-scale, real-world application. This report describes current approaches, recent results, and challenges for multidisciplinary design, analysis, and optimization as demonstrated by experience with the Ikhana fire pod design.!
Shape Synthesis in Mechanical Design
C. P. Teng; S. Bai; J. Angeles
2007-01-01
The shaping of structural elements in the area of mechanical design is a recurrent problem. The mechanical designer, as a rule, chooses what is believed to be the “simplest” shapes, such as the geometric primitives: lines, circles and, occasionally, conics. The use of higher-order curves is usually not even considered, not to speak of other curves than polynomials. However, the simplest geometric shapes are not necessarily the most suitable when the designed element must withstand loads that ...
Design of intelligent locks based on the triple KeeLoq algorithm
Directory of Open Access Journals (Sweden)
Huibin Chen
2016-04-01
Full Text Available KeeLoq algorithm with high security was usually used in wireless codec. Its security lack is indicated in this article according to the detailed rationale and the introduction of previous attack researches. Taking examples from Triple Data Encryption Standard algorithm, the triple KeeLoq codec algorithm was first proposed. Experimental results showed that the algorithm would not reduce powerful rolling effect and in consideration of limited computing power of embedded microcontroller three 64-bit keys were suitable to increase the crack difficulties and further improved its security. The method was applied to intelligent door access system for experimental verification. 16F690 extended Bluetooth or WiFi interface was employed to design the lock system on door. Key application was constructed on Android platform. The wireless communication between the lock on door and Android key application employed triple KeeLoq algorithm to ensure the higher security. Due to flexibility and multiformity (an Android key application with various keys of software-based keys, the solution owned overwhelmed advantages of low cost, high security, humanity, and green environmental protection.
A Double Evolutionary Pool Memetic Algorithm for Examination Timetabling Problems
Directory of Open Access Journals (Sweden)
Yu Lei
2014-01-01
Full Text Available A double evolutionary pool memetic algorithm is proposed to solve the examination timetabling problem. To improve the performance of the proposed algorithm, two evolutionary pools, that is, the main evolutionary pool and the secondary evolutionary pool, are employed. The genetic operators have been specially designed to fit the examination timetabling problem. A simplified version of the simulated annealing strategy is designed to speed the convergence of the algorithm. A clonal mechanism is introduced to preserve population diversity. Extensive experiments carried out on 12 benchmark examination timetabling instances show that the proposed algorithm is able to produce promising results for the uncapacitated examination timetabling problem.
Exploring design tradeoffs of a distributed algorithm for cosmic ray event detection
Yousaf, S.; Bakhshi, R.; van Steen, M.; Voulgaris, S.; Kelley, J. L.
2013-03-01
Many sensor networks, including large particle detector arrays measuring high-energy cosmic-ray air showers, traditionally rely on centralised trigger algorithms to find spatial and temporal coincidences of individual nodes. Such schemes suffer from scalability problems, especially if the nodes communicate wirelessly or have bandwidth limitations. However, nodes which instead communicate with each other can, in principle, use a distributed algorithm to find coincident events themselves without communication with a central node. We present such an algorithm and consider various design tradeoffs involved, in the context of a potential trigger for the Auger Engineering Radio Array (AERA).
Design of Low Power Algorithms for Automatic Embedded Analysis of Patch ECG Signals
DEFF Research Database (Denmark)
Saadi, Dorthe Bodholt
, several different cable-free wireless patch-type ECG recorders have recently reached the market. One of these recorders is the ePatch designed by the Danish company DELTA. The extended monitoring period available with the patch recorders has demonstrated to increase the diagnostic yield of outpatient ECG....... Such algorithms could allow the real-time transmission of clinically relevant information to a central monitoring station. The first step in embedded ECG interpretation is the automatic detection of each individual heartbeat. An important part of this project was therefore to design a novel algorithm...
Energy Technology Data Exchange (ETDEWEB)
Wang, Cheng-Der, E-mail: jdwang@iner.gov.tw [Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan, ROC (China); Lin, Chaung [National Tsing Hua University, Department of Engineering and System Science, 101, Section 2, Kuang Fu Road, Hsinchu 30013, Taiwan (China)
2013-02-15
Highlights: ► The PSO algorithm was adopted to automatically design a BWR CRP. ► The local search procedure was added to improve the result of PSO algorithm. ► The results show that the obtained CRP is the same good as that in the previous work. -- Abstract: This study developed a method for the automatic design of a boiling water reactor (BWR) control rod pattern (CRP) using the particle swarm optimization (PSO) algorithm. The PSO algorithm is more random compared to the rank-based ant system (RAS) that was used to solve the same BWR CRP design problem in the previous work. In addition, the local search procedure was used to make improvements after PSO, by adding the single control rod (CR) effect. The design goal was to obtain the CRP so that the thermal limits and shutdown margin would satisfy the design requirement and the cycle length, which is implicitly controlled by the axial power distribution, would be acceptable. The results showed that the same acceptable CRP found in the previous work could be obtained.
Understanding Mechanical Design with Respect to Manufacturability
Mondell, Skyler
2010-01-01
At the NASA Prototype Development Laboratory in Kennedy Space Center, Fl, several projects concerning different areas of mechanical design were undertaken in order to better understand the relationship between mechanical design and manufacturabiIity. The assigned projects pertained specifically to the NASA Space Shuttle, Constellation, and Expendable Launch Vehicle programs. During the work term, mechanical design practices relating to manufacturing processes were learned and utilized in order to obtain an understanding of mechanical design with respect to manufacturability.
New design algorithm and reliability testing of solar powered near ...
African Journals Online (AJOL)
New design algorithm and reliability testing of solar powered near-space flight vehicle for defense and security. ... To overcome this problem, we propose a pseudo-satellite system where telecommunication devices are carried on a perpetually flying solar aircraft cruising at stratospheric altitude. Our aircraft will combine ...
Design of a centrifugal compressor impeller using multi-objective optimization algorithm
International Nuclear Information System (INIS)
Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong; Choi, Jae Ho
2009-01-01
This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with ε-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.
Design of a centrifugal compressor impeller using multi-objective optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong [Inha University, Incheon (Korea, Republic of); Choi, Jae Ho [Samsung Techwin Co., Ltd., Changwon (Korea, Republic of)
2009-07-01
This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with {epsilon}-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.
Optimal Design of Pumped Pipeline Systems Using Genetic Algorithm and Mathematical Optimization
Directory of Open Access Journals (Sweden)
Mohammadhadi Afshar
2007-12-01
Full Text Available In recent years, much attention has been paid to the optimal design of pipeline systems. In this study, the problem of pipeline system optimal design has been solved through genetic algorithm and mathematical optimization. Pipe diameters and their thicknesses are considered as decision variables to be designed in a manner that water column separation and excessive pressures are avoided in the event of pump failure. Capabilities of the genetic algorithm and the mathematical programming method are compared for the problem under consideration. For simulation of transient streams, explicit characteristic method is used in which devices such as pumps are defined as boundary conditions of the equations defining the hydraulic behavior of pipe segments. The problem of optimal design of pipeline systems is a constrained problem which is converted to an unconstrained optimization problem using an external penalty function approach. The efficiency of the proposed approaches is verified in one example and the results are presented.
Huynh, Trong-Phuoc; Hwang, Chao-Lung; Yang, Shu-Ti
2017-12-01
This experimental study evaluated the performance of normal ordinary Portland cement (OPC) concrete and high-performance concrete (HPC) that were designed by the conventional method (ACI) and densified mixture design algorithm (DMDA) method, respectively. Engineering properties and durability performance of both the OPC and HPC samples were studied using the tests of workability, compressive strength, water absorption, ultrasonic pulse velocity, and electrical surface resistivity. Test results show that the HPC performed good fresh property and further showed better performance in terms of strength and durability as compared to the OPC.
Automatic boiling water reactor loading pattern design using ant colony optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Wang, C.-D. [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China); Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China)], E-mail: jdwang@iner.gov.tw; Lin Chaung [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China)
2009-08-15
An automatic boiling water reactor (BWR) loading pattern (LP) design methodology was developed using the rank-based ant system (RAS), which is a variant of the ant colony optimization (ACO) algorithm. To reduce design complexity, only the fuel assemblies (FAs) of one eight-core positions were determined using the RAS algorithm, and then the corresponding FAs were loaded into the other parts of the core. Heuristic information was adopted to exclude the selection of the inappropriate FAs which will reduce search space, and thus, the computation time. When the LP was determined, Haling cycle length, beginning of cycle (BOC) shutdown margin (SDM), and Haling end of cycle (EOC) maximum fraction of limit for critical power ratio (MFLCPR) were calculated using SIMULATE-3 code, which were used to evaluate the LP for updating pheromone of RAS. The developed design methodology was demonstrated using FAs of a reference cycle of the BWR6 nuclear power plant. The results show that, the designed LP can be obtained within reasonable computation time, and has a longer cycle length than that of the original design.
DEFF Research Database (Denmark)
Saadi, Dorthe Bodholt; Egstrup, Kenneth; Branebjerg, Jens
2012-01-01
We have designed and optimized an automatic QRS complex detection algorithm for electrocardiogram (ECG) signals recorded with the DELTA ePatch platform. The algorithm is able to automatically switch between single-channel and multi-channel analysis mode. This preliminary study includes data from ...
Zenil, Hector
2018-02-18
To extract and learn representations leading to generative mechanisms from data, especially without making arbitrary decisions and biased assumptions, is a central challenge in most areas of scientific research particularly in connection to current major limitations of influential topics and methods of machine and deep learning as they have often lost sight of the model component. Complex data is usually produced by interacting sources with different mechanisms. Here we introduce a parameter-free model-based approach, based upon the seminal concept of Algorithmic Probability, that decomposes an observation and signal into its most likely algorithmic generative mechanisms. Our methods use a causal calculus to infer model representations. We demonstrate the method ability to distinguish interacting mechanisms and deconvolve them, regardless of whether the objects produce strings, space-time evolution diagrams, images or networks. We numerically test and evaluate our method and find that it can disentangle observations from discrete dynamic systems, random and complex networks. We think that these causal inference techniques can contribute as key pieces of information for estimations of probability distributions complementing other more statistical-oriented techniques that otherwise lack model inference capabilities.
Mechanical Design of Spacecraft
1962-01-01
In the spring of 1962, engineers from the Engineering Mechanics Division of the Jet Propulsion Laboratory gave a series of lectures on spacecraft design at the Engineering Design seminars conducted at the California Institute of Technology. Several of these lectures were subsequently given at Stanford University as part of the Space Technology seminar series sponsored by the Department of Aeronautics and Astronautics. Presented here are notes taken from these lectures. The lectures were conceived with the intent of providing the audience with a glimpse of the activities of a few mechanical engineers who are involved in designing, building, and testing spacecraft. Engineering courses generally consist of heavily idealized problems in order to allow the more efficient teaching of mathematical technique. Students, therefore, receive a somewhat limited exposure to actual engineering problems, which are typified by more unknowns than equations. For this reason it was considered valuable to demonstrate some of the problems faced by spacecraft designers, the processes used to arrive at solutions, and the interactions between the engineer and the remainder of the organization in which he is constrained to operate. These lecture notes are not so much a compilation of sophisticated techniques of analysis as they are a collection of examples of spacecraft hardware and associated problems. They will be of interest not so much to the experienced spacecraft designer as to those who wonder what part the mechanical engineer plays in an effort such as the exploration of space.
Shape Synthesis in Mechanical Design
Directory of Open Access Journals (Sweden)
C. P. Teng
2007-01-01
Full Text Available The shaping of structural elements in the area of mechanical design is a recurrent problem. The mechanical designer, as a rule, chooses what is believed to be the “simplest” shapes, such as the geometric primitives: lines, circles and, occasionally, conics. The use of higher-order curves is usually not even considered, not to speak of other curves than polynomials. However, the simplest geometric shapes are not necessarily the most suitable when the designed element must withstand loads that can lead to failure-prone stress concentrations. Indeed, as mechanical designers have known for a while, stress concentrations occur, first and foremost, by virtue of either dramatic changes in curvature or extremely high values thereof. As an alternative, we propose here the use of smooth curves that can be simply generated using standard concepts such as non-parametric cubic splines. These curves can be readily used to produce either extruded surfaces or surfaces of revolution.
An optimized outlier detection algorithm for jury-based grading of engineering design projects
DEFF Research Database (Denmark)
Thompson, Mary Kathryn; Espensen, Christina; Clemmensen, Line Katrine Harder
2016-01-01
This work characterizes and optimizes an outlier detection algorithm to identify potentially invalid scores produced by jury members while grading engineering design projects. The paper describes the original algorithm and the associated adjudication process in detail. The impact of the various...... (the base rule and the three additional conditions) play a role in the algorithm's performance and should be included in the algorithm. Because there is significant interaction between the base rule and the additional conditions, many acceptable combinations that balance the FPR and FNR can be found......, but no true optimum seems to exist. The performance of the best optimizations and the original algorithm are similar. Therefore, it should be possible to choose new coefficient values for jury populations in other cultures and contexts logically and empirically without a full optimization as long...
Design of a fuzzy differential evolution algorithm to predict non-deposition sediment transport
Ebtehaj, Isa; Bonakdari, Hossein
2017-12-01
Since the flow entering a sewer contains solid matter, deposition at the bottom of the channel is inevitable. It is difficult to understand the complex, three-dimensional mechanism of sediment transport in sewer pipelines. Therefore, a method to estimate the limiting velocity is necessary for optimal designs. Due to the inability of gradient-based algorithms to train Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for non-deposition sediment transport prediction, a new hybrid ANFIS method based on a differential evolutionary algorithm (ANFIS-DE) is developed. The training and testing performance of ANFIS-DE is evaluated using a wide range of dimensionless parameters gathered from the literature. The input combination used to estimate the densimetric Froude number ( Fr) parameters includes the volumetric sediment concentration ( C V ), ratio of median particle diameter to hydraulic radius ( d/R), ratio of median particle diameter to pipe diameter ( d/D) and overall friction factor of sediment ( λ s ). The testing results are compared with the ANFIS model and regression-based equation results. The ANFIS-DE technique predicted sediment transport at limit of deposition with lower root mean square error (RMSE = 0.323) and mean absolute percentage of error (MAPE = 0.065) and higher accuracy ( R 2 = 0.965) than the ANFIS model and regression-based equations.
Thickness determination in textile material design: dynamic modeling and numerical algorithms
International Nuclear Information System (INIS)
Xu, Dinghua; Ge, Meibao
2012-01-01
Textile material design is of paramount importance in the study of functional clothing design. It is therefore important to determine the dynamic heat and moisture transfer characteristics in the human body–clothing–environment system, which directly determine the heat–moisture comfort level of the human body. Based on a model of dynamic heat and moisture transfer with condensation in porous fabric at low temperature, this paper presents a new inverse problem of textile thickness determination (IPTTD). Adopting the idea of the least-squares method, we formulate the IPTTD into a function minimization problem. By means of the finite-difference method, quasi-solution method and direct search method for one-dimensional minimization problems, we construct iterative algorithms of the approximated solution for the IPTTD. Numerical simulation results validate the formulation of the IPTTD and demonstrate the effectiveness of the proposed numerical algorithms. (paper)
On the impact of communication complexity in the design of parallel numerical algorithms
Gannon, D.; Vanrosendale, J.
1984-01-01
This paper describes two models of the cost of data movement in parallel numerical algorithms. One model is a generalization of an approach due to Hockney, and is suitable for shared memory multiprocessors where each processor has vector capabilities. The other model is applicable to highly parallel nonshared memory MIMD systems. In the second model, algorithm performance is characterized in terms of the communication network design. Techniques used in VLSI complexity theory are also brought in, and algorithm independent upper bounds on system performance are derived for several problems that are important to scientific computation.
Stolarski, Tadeusz
1999-01-01
""Tribology in Machine Design is strongly recommended for machine designers, and engineers and scientists interested in tribology. It should be in the engineering library of companies producing mechanical equipment.""Applied Mechanics ReviewTribology in Machine Design explains the role of tribology in the design of machine elements. It shows how algorithms developed from the basic principles of tribology can be used in a range of practical applications within mechanical devices and systems.The computer offers today's designer the possibility of greater stringen
Testing block subdivision algorithms on block designs
Wiseman, Natalie; Patterson, Zachary
2016-01-01
Integrated land use-transportation models predict future transportation demand taking into account how households and firms arrange themselves partly as a function of the transportation system. Recent integrated models require parcels as inputs and produce household and employment predictions at the parcel scale. Block subdivision algorithms automatically generate parcel patterns within blocks. Evaluating block subdivision algorithms is done by way of generating parcels and comparing them to those in a parcel database. Three block subdivision algorithms are evaluated on how closely they reproduce parcels of different block types found in a parcel database from Montreal, Canada. While the authors who developed each of the algorithms have evaluated them, they have used their own metrics and block types to evaluate their own algorithms. This makes it difficult to compare their strengths and weaknesses. The contribution of this paper is in resolving this difficulty with the aim of finding a better algorithm suited to subdividing each block type. The proposed hypothesis is that given the different approaches that block subdivision algorithms take, it's likely that different algorithms are better adapted to subdividing different block types. To test this, a standardized block type classification is used that consists of mutually exclusive and comprehensive categories. A statistical method is used for finding a better algorithm and the probability it will perform well for a given block type. Results suggest the oriented bounding box algorithm performs better for warped non-uniform sites, as well as gridiron and fragmented uniform sites. It also produces more similar parcel areas and widths. The Generalized Parcel Divider 1 algorithm performs better for gridiron non-uniform sites. The Straight Skeleton algorithm performs better for loop and lollipop networks as well as fragmented non-uniform and warped uniform sites. It also produces more similar parcel shapes and patterns.
Computational issues in alternating projection algorithms for fixed-order control design
DEFF Research Database (Denmark)
Beran, Eric Bengt; Grigoriadis, K.
1997-01-01
Alternating projection algorithms have been introduced recently to solve fixed-order controller design problems described by linear matrix inequalities and non-convex coupling rank constraints. In this work, an extensive numerical experimentation using proposed benchmark fixed-order control design...... examples is used to indicate the computational efficiency of the method. These results indicate that the proposed alternating projections are effective in obtaining low-order controllers for small and medium order problems...
Reliability design of mechanical systems a guide for mechanical and civil engineers
Woo, Seongwoo
2017-01-01
This book describes basic reliability concepts – parametric ALT plan, failure mechanism and design, and reliability testing with acceleration factor and sample size equation. A generalized life-stress failure model with a new effort concept has been derived and recommended to calculate the acceleration factor of the mechanical system. The new sample size equation with the acceleration factor has also been derived to carry out the parametric ALT. This new parametric ALT should help a mechanical/civil engineer to uncover the design parameters affecting reliability during the design process of the mechanical system. Consequently, it should help companies to improve product reliability and avoid recalls due to the product/structure failures in the field. As the improper or missing design parameters in the design phase are experimentally identified by this new reliability design method - parametric ALT, the mechanical/civil engineering system might improve in reliability by the increase in lifetime and the reduc...
The methods and algorithms for designing complex three-dimensional robots
International Nuclear Information System (INIS)
Solovjev, A.E.; Naumov, V.B.
1996-01-01
For automation designing by the Robotics laboratory were executed some fundamental and applied researches. This researching allowed to create rational mathematical model for numeric modeling with real-time simulation. In the mathematical model used set of equations of rigid body's motion in Lagrange's form and set of Appel's equations taking into consideration holonomic and non-holonomic connections. In present article are considered methods and algorithms of dynamic modeling of a system of rigid bodies for robotics task and brief description of the package Computer Aided Engineering for Industrial Robots, based on considered algorithms. So far as, in researching of robots the dynamic tasks (direct and inverse) are more interesting than another tasks, authors pay attention just on these problems
Directory of Open Access Journals (Sweden)
Giegerich Robert
2004-08-01
Full Text Available Abstract Background The general problem of RNA secondary structure prediction under the widely used thermodynamic model is known to be NP-complete when the structures considered include arbitrary pseudoknots. For restricted classes of pseudoknots, several polynomial time algorithms have been designed, where the O(n6time and O(n4 space algorithm by Rivas and Eddy is currently the best available program. Results We introduce the class of canonical simple recursive pseudoknots and present an algorithm that requires O(n4 time and O(n2 space to predict the energetically optimal structure of an RNA sequence, possible containing such pseudoknots. Evaluation against a large collection of known pseudoknotted structures shows the adequacy of the canonization approach and our algorithm. Conclusions RNA pseudoknots of medium size can now be predicted reliably as well as efficiently by the new algorithm.
Mechanical Design of Superconducting Accelerator Magnets
International Nuclear Information System (INIS)
Toral, F
2014-01-01
This paper is about the mechanical design of superconducting accelerator magnets. First, we give a brief review of the basic concepts and terms. In the following sections, we describe the particularities of the mechanical design of different types of superconducting accelerator magnets: solenoids, costheta, superferric, and toroids. Special attention is given to the pre-stress principle, which aims to avoid the appearance of tensile stresses in the superconducting coils. A case study on a compact superconducting cyclotron summarizes the main steps and the guidelines that should be followed for a proper mechanical design. Finally, we present some remarks on the measurement techniques
Mechanical Design of Superconducting Accelerator Magnets
Toral, Fernando
2014-07-17
This paper is about the mechanical design of superconducting accelerator magnets. First, we give a brief review of the basic concepts and terms. In the following sections, we describe the particularities of the mechanical design of different types of superconducting accelerator magnets: solenoids, costheta, superferric, and toroids. Special attention is given to the pre-stress principle, which aims to avoid the appearance of tensile stresses in the superconducting coils. A case study on a compact superconducting cyclotron summarizes the main steps and the guidelines that should be followed for a proper mechanical design. Finally, we present some remarks on the measurement techniques.
Mechanical Design of Superconducting Accelerator Magnets
Energy Technology Data Exchange (ETDEWEB)
Toral, F [Madrid, CIEMAT (Spain)
2014-07-01
This paper is about the mechanical design of superconducting accelerator magnets. First, we give a brief review of the basic concepts and terms. In the following sections, we describe the particularities of the mechanical design of different types of superconducting accelerator magnets: solenoids, costheta, superferric, and toroids. Special attention is given to the pre-stress principle, which aims to avoid the appearance of tensile stresses in the superconducting coils. A case study on a compact superconducting cyclotron summarizes the main steps and the guidelines that should be followed for a proper mechanical design. Finally, we present some remarks on the measurement techniques.
IVVS probe mechanical concept design
Energy Technology Data Exchange (ETDEWEB)
Rossi, Paolo, E-mail: paolo.rossi@enea.it; Neri, Carlo; De Collibus, Mario Ferri; Mugnaini, Giampiero; Pollastrone, Fabio; Crescenzi, Fabio
2015-10-15
Highlights: • ENEA designed, developed and tested a laser based In Vessel Viewing System (IVVS). • IVVS mechanical design has been revised from 2011 to 2013 to meet ITER requirements. • Main improvements are piezoceramic actuators and a step focus system. • Successful qualification activities validated the concept design for ITER environment. - Abstract: ENEA has been deeply involved in the design, development and testing of a laser based In Vessel Viewing System (IVVS) required for the inspection of ITER plasma-facing components. The IVVS probe shall be deployed into the vacuum vessel, providing high resolution images and metrology measurements to detect damages and possible erosion. ENEA already designed and manufactured an IVVS probe prototype based on a rad-hard concept and driven by commercial micro-step motors, which demonstrated satisfying viewing and metrology performances at room conditions. The probe sends a laser beam through a reflective rotating prism. By rotating the axes of the prism, the probe can scan all the environment points except those present in a shadow cone and the backscattered light signal is then processed to measure the intensity level (viewing) and the distance from the probe (metrology). During the last years, in order to meet all the ITER environmental conditions, such as high vacuum, gamma radiation lifetime dose up to 5 MGy, cumulative neutron fluence of about 2.3 × 10{sup 17} n/cm{sup 2}, temperature of 120 °C and magnetic field of 8 T, the probe mechanical design was significantly revised introducing a new actuating system based on piezo-ceramic actuators and improved with a new step focus system. The optical and mechanical schemes have been then modified and refined to meet also the geometrical constraints. The paper describes the mechanical concept design solutions adopted in order to fulfill IVVS probe functional performance requirements considering ITER working environment and geometrical constraints.
Problems of structural mechanics in nuclear design
International Nuclear Information System (INIS)
Patwardhan, V.M.; Kakodkar, Anil
1975-01-01
A very careful and detailed stress analysis of nuclear presure vessels and components is essential for ensuring the safety and integrity of nuclear power plants. The nuclear designer, therefore, relies heavily on structural mechanics for application of the most advanced stress analysis techniques to practical design problems. The paper reviews the inter-relation between structural mechanics and nuclear design and discusses a few of the specific structural mechanics problems faced by the nuclear designers in the Department of Atomic Energy, India. (author)
Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design Processes
Rogers, James L.; McCulley, Collin M.; Bloebaum, Christina L.
1996-01-01
The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.
Directory of Open Access Journals (Sweden)
Ion BULAC
2013-05-01
Full Text Available Due to technical deviations, in the elements of the 4R spatial spherical mechanism appear efforts thatadditionally loads the mechanism, efforts that can be determined with the calculation algorithm that will bepresented in this paper
Highway Passenger Transport Based Express Parcel Service Network Design: Model and Algorithm
Directory of Open Access Journals (Sweden)
Yuan Jiang
2017-01-01
Full Text Available Highway passenger transport based express parcel service (HPTB-EPS is an emerging business that uses unutilised room of coach trunk to ship parcels between major cities. While it is reaping more and more express market, the managers are facing difficult decisions to design the service network. This paper investigates the HPTB-EPS network design problem and analyses the time-space characteristics of such network. A mixed-integer programming model is formulated integrating the service decision, frequency, and network flow distribution. To solve the model, a decomposition-based heuristic algorithm is designed by decomposing the problem as three steps: construction of service network, service path selection, and distribution of network flow. Numerical experiment using real data from our partner company demonstrates the effectiveness of our model and algorithm. We found that our solution could reduce the total cost by up to 16.3% compared to the carrier’s solution. The sensitivity analysis demonstrates the robustness and flexibility of the solutions of the model.
Homotopy Algorithm for Fixed Order Mixed H2/H(infinity) Design
Whorton, Mark; Buschek, Harald; Calise, Anthony J.
1996-01-01
Recent developments in the field of robust multivariable control have merged the theories of H-infinity and H-2 control. This mixed H-2/H-infinity compensator formulation allows design for nominal performance by H-2 norm minimization while guaranteeing robust stability to unstructured uncertainties by constraining the H-infinity norm. A key difficulty associated with mixed H-2/H-infinity compensation is compensator synthesis. A homotopy algorithm is presented for synthesis of fixed order mixed H-2/H-infinity compensators. Numerical results are presented for a four disk flexible structure to evaluate the efficiency of the algorithm.
Nonequilibrium molecular dynamics theory, algorithms and applications
Todd, Billy D
2017-01-01
Written by two specialists with over twenty-five years of experience in the field, this valuable text presents a wide range of topics within the growing field of nonequilibrium molecular dynamics (NEMD). It introduces theories which are fundamental to the field - namely, nonequilibrium statistical mechanics and nonequilibrium thermodynamics - and provides state-of-the-art algorithms and advice for designing reliable NEMD code, as well as examining applications for both atomic and molecular fluids. It discusses homogenous and inhomogenous flows and pays considerable attention to highly confined fluids, such as nanofluidics. In addition to statistical mechanics and thermodynamics, the book covers the themes of temperature and thermodynamic fluxes and their computation, the theory and algorithms for homogenous shear and elongational flows, response theory and its applications, heat and mass transport algorithms, applications in molecular rheology, highly confined fluids (nanofluidics), the phenomenon of slip and...
Analyses for designing objects in mechanical design
International Nuclear Information System (INIS)
Nakajima, Norihiro; Miyamura, Hiroko N.; Kawakami, Yoshiaki; Kawamura, Takuma
2015-01-01
Defining factors to induce the damage that can be assumed in the mechanical structures, it is a loaded work to analyze a damage possibility point derived by the assumption phenomenon that can occur is, but it is the important designing process. Taking factors caused by the earthquake as an example, and simulating the phenomenon that can be assumed, the computational result was analyzed with information visualization. A damage possibility point by analyzing the result mathematically. The illustration of analytical results may give points to designers as means for a designer to recognize a damage possibility point from the sensitivity of the designer. (author)
Integrating Thermal Tools Into the Mechanical Design Process
Tsuyuki, Glenn T.; Siebes, Georg; Novak, Keith S.; Kinsella, Gary M.
1999-01-01
The intent of mechanical design is to deliver a hardware product that meets or exceeds customer expectations, while reducing cycle time and cost. To this end, an integrated mechanical design process enables the idea of parallel development (concurrent engineering). This represents a shift from the traditional mechanical design process. With such a concurrent process, there are significant issues that have to be identified and addressed before re-engineering the mechanical design process to facilitate concurrent engineering. These issues also assist in the integration and re-engineering of the thermal design sub-process since it resides within the entire mechanical design process. With these issues in mind, a thermal design sub-process can be re-defined in a manner that has a higher probability of acceptance, thus enabling an integrated mechanical design process. However, the actual implementation is not always problem-free. Experience in applying the thermal design sub-process to actual situations provides the evidence for improvement, but more importantly, for judging the viability and feasibility of the sub-process.
Directory of Open Access Journals (Sweden)
Rachmad Vidya Wicaksana Putra
2012-09-01
Full Text Available In the literature, several approaches of designing a DCT/IDCT-based image compression system have been proposed. In this paper, we present a new RTL design approach with as main focus developing a DCT/IDCT-based image compression architecture using a self-created algorithm. This algorithm can efficiently minimize the amount of shifter-adders to substitute multipliers. We call this new algorithm the multiplication from Common Binary Expression (mCBE Algorithm. Besides this algorithm, we propose alternative quantization numbers, which can be implemented simply as shifters in digital hardware. Mostly, these numbers can retain a good compressed-image quality compared to JPEG recommendations. These ideas lead to our design being small in circuit area, multiplierless, and low in complexity. The proposed 8-point 1D-DCT design has only six stages, while the 8-point 1D-IDCT design has only seven stages (one stage being defined as equal to the delay of one shifter or 2-input adder. By using the pipelining method, we can achieve a high-speed architecture with latency as a trade-off consideration. The design has been synthesized and can reach a speed of up to 1.41ns critical path delay (709.22MHz.
DEFF Research Database (Denmark)
Larsen, Niels Vesterdal
2007-01-01
A printed drooping dipole array is designed and constructed. The design is based on a genetic algorithm optimisation procedure used in conjunction with the software programme AWAS. By optimising the array G/T for specific combinations of scan angles and frequencies an optimum design is obtained...
Chen, Tinggui; Xiao, Renbin
2014-01-01
Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.
Design of a Ground-Launched Ballistic Missile Interceptor Using a Genetic Algorithm
National Research Council Canada - National Science Library
Anderson, Murray
1999-01-01
...) minimize maximum U-loading. In 50 generations the genetic algorithm was able to develop two basic types of external aerodynamic designs that performed nearly the same, with miss distances less than 1.0 foot...
Mechanical Design Features of PGSFR NSSS
International Nuclear Information System (INIS)
Park, Chang-Gyu; Koo, Gyeong-Hoi; Cho, Jae-Hun; Kim, Sung-Kyun
2016-01-01
The NSSS(Nuclear Steam Supply System) is composed of PHTS(Primary Heat Transport System), IHTS (Intermediate Heat Transport System), and SGS(Steam Generation System). And, DHRS(Decay Heat Removal System) adopts both the active and passive systems for diversity. The structures including components and piping should be designed to ensure the structural integrity for their design life against mechanical and operational loads. In this study, the mechanical design features for the structures and components that make up PGSFR NSSS are described. The mechanical design features of structures and components for a PGSFR NSSS are described. The structures are being designed to maintain the structural integrity for their design lifetime by considering the high temperature operating condition. The decay heat removal system(DHRS) removes all reactor decay heat in two ways; active type(ADHRS) and passive type(PDHRS). ADHRS consists of DHX, blower, FHX, circulation pump, and expansion tank. But PDHRS consists of DHX, AHX, and expansion tank. FHX is a finned-tube-type sodium-to-air heat exchanger whereas AHX is a helical-type sodium-to-air heat exchanger
Mechanical Design Features of PGSFR NSSS
Energy Technology Data Exchange (ETDEWEB)
Park, Chang-Gyu; Koo, Gyeong-Hoi; Cho, Jae-Hun; Kim, Sung-Kyun [KAERI, Daejeon (Korea, Republic of)
2016-05-15
The NSSS(Nuclear Steam Supply System) is composed of PHTS(Primary Heat Transport System), IHTS (Intermediate Heat Transport System), and SGS(Steam Generation System). And, DHRS(Decay Heat Removal System) adopts both the active and passive systems for diversity. The structures including components and piping should be designed to ensure the structural integrity for their design life against mechanical and operational loads. In this study, the mechanical design features for the structures and components that make up PGSFR NSSS are described. The mechanical design features of structures and components for a PGSFR NSSS are described. The structures are being designed to maintain the structural integrity for their design lifetime by considering the high temperature operating condition. The decay heat removal system(DHRS) removes all reactor decay heat in two ways; active type(ADHRS) and passive type(PDHRS). ADHRS consists of DHX, blower, FHX, circulation pump, and expansion tank. But PDHRS consists of DHX, AHX, and expansion tank. FHX is a finned-tube-type sodium-to-air heat exchanger whereas AHX is a helical-type sodium-to-air heat exchanger.
Directory of Open Access Journals (Sweden)
Rachmad Vidya Wicaksana Putra
2016-06-01
Full Text Available Convolutional encoding and data decoding are fundamental processes in convolutional error correction. One of the most popular error correction methods in decoding is the Viterbi algorithm. It is extensively implemented in many digital communication applications. Its VLSI design challenges are about area, speed, power, complexity and configurability. In this research, we specifically propose a VLSI architecture for a configurable and low-complexity design of a hard-decision Viterbi decoding algorithm. The configurable and low-complexity design is achieved by designing a generic VLSI architecture, optimizing each processing element (PE at the logical operation level and designing a conditional adapter. The proposed design can be configured for any predefined number of trace-backs, only by changing the trace-back parameter value. Its computational process only needs N + 2 clock cycles latency, with N is the number of trace-backs. Its configurability function has been proven for N = 8, N = 16, N = 32 and N = 64. Furthermore, the proposed design was synthesized and evaluated in Xilinx and Altera FPGA target boards for area consumption and speed performance.
An Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm
Directory of Open Access Journals (Sweden)
Huan-Yu Lin
2012-01-01
Full Text Available For test-sheet composition systems, it is important to adaptively compose test sheets with diverse conceptual scopes, discrimination and difficulty degrees to meet various assessment requirements during real learning situations. Computation time and item exposure rate also influence performance and item bank security. Therefore, this study proposes an Adaptive Test Sheet Generation (ATSG mechanism, where a Candidate Item Selection Strategy adaptively determines candidate test items and conceptual granularities according to desired conceptual scopes, and an Aggregate Objective Function applies Genetic Algorithm (GA to figure out the approximate solution of mixed integer programming problem for the test-sheet composition. Experimental results show that the ATSG mechanism can efficiently, precisely generate test sheets to meet the various assessment requirements than existing ones. Furthermore, according to experimental finding, Fractal Time Series approach can be applied to analyze the self-similarity characteristics of GA’s fitness scores for improving the quality of the test-sheet composition in the near future.
A Computer Environment for Beginners' Learning of Sorting Algorithms: Design and Pilot Evaluation
Kordaki, M.; Miatidis, M.; Kapsampelis, G.
2008-01-01
This paper presents the design, features and pilot evaluation study of a web-based environment--the SORTING environment--for the learning of sorting algorithms by secondary level education students. The design of this environment is based on modeling methodology, taking into account modern constructivist and social theories of learning while at…
Directory of Open Access Journals (Sweden)
Jie Zhang
2013-01-01
Full Text Available In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.
Zhang, Jie; Wang, Yuping; Feng, Junhong
2013-01-01
In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.
Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li
2014-01-01
To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement.
Planar articulated mechanism design by graph theoretical enumeration
DEFF Research Database (Denmark)
Kawamoto, A; Bendsøe, Martin P.; Sigmund, Ole
2004-01-01
This paper deals with design of articulated mechanisms using a truss-based ground-structure representation. By applying a graph theoretical enumeration approach we can perform an exhaustive analysis of all possible topologies for a test example for which we seek a symmetric mechanism. This guaran....... This guarantees that one can identify the global optimum solution. The result underlines the importance of mechanism topology and gives insight into the issues specific to articulated mechanism designs compared to compliant mechanism designs....
International Nuclear Information System (INIS)
Semwal, Girish; Rastogi, Vipul
2014-01-01
We present design optimization of wavelength filters based on long period waveguide gratings (LPWGs) using the adaptive particle swarm optimization (APSO) technique. We demonstrate optimization of the LPWG parameters for single-band, wide-band and dual-band rejection filters for testing the convergence of APSO algorithms. After convergence tests on the algorithms, the optimization technique has been implemented to design more complicated application specific filters such as erbium doped fiber amplifier (EDFA) amplified spontaneous emission (ASE) flattening, erbium doped waveguide amplifier (EDWA) gain flattening and pre-defined broadband rejection filters. The technique is useful for designing and optimizing the parameters of LPWGs to achieve complicated application specific spectra. (paper)
Teaching learning based optimization algorithm and its engineering applications
Rao, R Venkata
2016-01-01
Describing a new optimization algorithm, the “Teaching-Learning-Based Optimization (TLBO),” in a clear and lucid style, this book maximizes reader insights into how the TLBO algorithm can be used to solve continuous and discrete optimization problems involving single or multiple objectives. As the algorithm operates on the principle of teaching and learning, where teachers influence the quality of learners’ results, the elitist version of TLBO algorithm (ETLBO) is described along with applications of the TLBO algorithm in the fields of electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics and biotechnology. The book offers a valuable resource for scientists, engineers and practitioners involved in the development and usage of advanced optimization algorithms.
Malicious Botnet Survivability Mechanism Evolution Forecasting by Means of a Genetic Algorithm
Directory of Open Access Journals (Sweden)
Nikolaj Goranin
2012-04-01
Full Text Available Botnets are considered to be among the most dangerous modern malware types and the biggest current threats to global IT infrastructure. Botnets are rapidly evolving, and therefore forecasting their survivability strategies is important for the development of countermeasure techniques. The article propose the botnet-oriented genetic algorithm based model framework, which aimed at forecasting botnet survivability mechanisms. The model may be used as a framework for forecasting the evolution of other characteristics. The efficiency of different survivability mechanisms is evaluated by applying the proposed fitness function. The model application area also covers scientific botnet research and modelling tasks.
Burt, Adam O.; Tinker, Michael L.
2014-01-01
In this paper, genetic algorithm based and gradient-based topology optimization is presented in application to a real hardware design problem. Preliminary design of a planetary lander mockup structure is accomplished using these methods that prove to provide major weight savings by addressing the structural efficiency during the design cycle. This paper presents two alternative formulations of the topology optimization problem. The first is the widely-used gradient-based implementation using commercially available algorithms. The second is formulated using genetic algorithms and internally developed capabilities. These two approaches are applied to a practical design problem for hardware that has been built, tested and proven to be functional. Both formulations converged on similar solutions and therefore were proven to be equally valid implementations of the process. This paper discusses both of these formulations at a high level.
STAR PIXEL detector mechanical design
Energy Technology Data Exchange (ETDEWEB)
Wieman, H H; Anderssen, E; Greiner, L; Matis, H S; Ritter, H G; Sun, X; Szelezniak, M [Lawrence Berkeley National Laboratory, Berkeley, CA 94720 (United States)], E-mail: hhwieman@lbl.gov
2009-05-15
A high resolution pixel detector is being designed for the STAR [1] experiment at RHIC. This device will use MAPS as the detector element and will have a pointing accuracy of {approx}25 microns. We will be reporting on the mechanical design required to support this resolution. The radiation length of the first layer ({approx}0.3% X{sub 0}) and its distance from the interaction point (2.5 cm) determines the resolution. The design makes use of air cooling and thin carbon composite structures to limit the radiation length. The mechanics are being developed to achieve spatial calibrations and stability to 20 microns and to permit rapid detector replacement in event of radiation damage or other potential failures from operation near the beam.
Design and implementation of adaptive inverse control algorithm for a micro-hand control system
Directory of Open Access Journals (Sweden)
Wan-Cheng Wang
2014-01-01
Full Text Available The Letter proposes an online tuned adaptive inverse position control algorithm for a micro-hand. First, the configuration of the micro-hand is discussed. Next, a kinematic analysis of the micro-hand is investigated and then the relationship between the rotor position of micro-permanent magnet synchronous motor and the tip of the micro-finger is derived. After that, an online tuned adaptive inverse control algorithm, which includes an adaptive inverse model and an adaptive inverse control, is designed. The online tuned adaptive inverse control algorithm has better performance than the proportional–integral control algorithm does. In addition, to avoid damaging the object during the grasping process, an online force control algorithm is proposed here as well. An embedded micro-computer, cRIO-9024, is used to realise the whole position control algorithm and the force control algorithm by using software. As a result, the hardware circuit is very simple. Experimental results show that the proposed system can provide fast transient responses, good load disturbance responses, good tracking responses and satisfactory grasping responses.
The Mechanical Design for the LHC Collimators
Bertarelli, A; Assmann, R W; Chiaveri, Enrico; Kurtyka, T; Mayer, M; Perret, R; Sievers, P
2004-01-01
The design of the LHC collimators must comply with the very demanding specifications entailed by the highly energetic beam handled in the LHC: these requirements impose a temperature on the collimating jaws not exceeding 50ºC in steady operations and an unparalleled overall geometrical stability of 25 micro-m on a 1200 mm span. At the same time, the design phase must meet the challenging deadlines required by the general time schedule. To respond to these tough and sometimes conflicting constraints, the chosen design appeals to a mixture of traditional and innovative technologies, largely drawing from LEP collimator experience. The specifications impose a low-Z material for the collimator jaws, directing the design towards such graphite or such novel materials as 3-d Carbon/carbon composites. An accurate mechanical design has allowed to considerably reduce mechanical play and optimize geometrical stability. Finally, all mechanical studies were supported by in-depth thermo-mechanical analysis concerning tempe...
Design of planar articulated mechanisms using branch and bound
DEFF Research Database (Denmark)
Stolpe, Mathias; Kawamoto, Atsushi
2004-01-01
This paper considers an optimization model and a solution method for the design of two-dimensional mechanical mechanisms. The mechanism design problem is modeled as a nonconvex mixed integer program which allows the optimal topology and geometry of the mechanism to be determined simultaneously...... and that buckling is prevented. The feasible set of the design problem is described by nonlinear differentiable and non-differentiable constraints as well as nonlinear matrix inequalities. To solve the mechanism design problem a branch and bound method based on convex relaxations is developed. To guarantee...... mechanism design problems of realistic size to global optimality....
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
Energy Technology Data Exchange (ETDEWEB)
Hirata, M.H.; Marco Filho, F. de [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia
1990-12-31
Procedures for the design of the main mechanical components of a wind system were developed. One of the main concerns was related to the possibility of its use in small micro-computers. This goal was reached and an APPLE II computer was used. The resulting algorithm permits a friendly interaction between man and machine. 5 refs., 12 figs
Ushijima, Timothy T.; Yeh, William W.-G.
2013-10-01
An optimal experimental design algorithm is developed to select locations for a network of observation wells that provide maximum information about unknown groundwater pumping in a confined, anisotropic aquifer. The design uses a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. The formulated optimization problem is non-convex and contains integer variables necessitating a combinatorial search. Given a realistic large-scale model, the size of the combinatorial search required can make the problem difficult, if not impossible, to solve using traditional mathematical programming techniques. Genetic algorithms (GAs) can be used to perform the global search; however, because a GA requires a large number of calls to a groundwater model, the formulated optimization problem still may be infeasible to solve. As a result, proper orthogonal decomposition (POD) is applied to the groundwater model to reduce its dimensionality. Then, the information matrix in the full model space can be searched without solving the full model. Results from a small-scale test case show identical optimal solutions among the GA, integer programming, and exhaustive search methods. This demonstrates the GA's ability to determine the optimal solution. In addition, the results show that a GA with POD model reduction is several orders of magnitude faster in finding the optimal solution than a GA using the full model. The proposed experimental design algorithm is applied to a realistic, two-dimensional, large-scale groundwater problem. The GA converged to a solution for this large-scale problem.
Design Principles and Algorithms for Air Traffic Arrival Scheduling
Erzberger, Heinz; Itoh, Eri
2014-01-01
This report presents design principles and algorithms for building a real-time scheduler of arrival aircraft based on a first-come-first-served (FCFS) scheduling protocol. The algorithms provide the conceptual and computational foundation for the Traffic Management Advisor (TMA) of the Center/terminal radar approach control facilities (TRACON) automation system, which comprises a set of decision support tools for managing arrival traffic at major airports in the United States. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high-altitude airspace far away from the airport and low-altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time. This report is a revision of an earlier paper first presented as part of an Advisory Group for Aerospace Research and Development (AGARD) lecture series in September 1995. The authors, during vigorous discussions over the details of this paper, felt it was important to the air-trafficmanagement (ATM) community to revise and extend the original 1995 paper, providing more detail and clarity and thereby allowing future researchers to understand this foundational work as the basis for the TMA's scheduling algorithms.
Zhao, Li; Chen, Chunxia; Li, Bei; Dong, Li; Guo, Yingqiang; Xiao, Xijun; Zhang, Eryong; Qin, Li
2014-01-01
Objective To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement. Methods We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms. Results A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88–4.38 mg/day) than the low-dose range (warfarin dose prediction and in the low-dose and the ideal-dose ranges. Conclusions All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement. PMID:24728385
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Energy Technology Data Exchange (ETDEWEB)
Gould, Nathan [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States); Hendy, Oliver [Department of Biology, The College of New Jersey, Ewing, NJ (United States); Papamichail, Dimitris, E-mail: papamicd@tcnj.edu [Department of Computer Science, The College of New Jersey, Ewing, NJ (United States)
2014-10-06
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
Computational Tools and Algorithms for Designing Customized Synthetic Genes
International Nuclear Information System (INIS)
Gould, Nathan; Hendy, Oliver; Papamichail, Dimitris
2014-01-01
Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein-coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review, we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
HYLIFE-II reactor chamber mechanical design
International Nuclear Information System (INIS)
House, P.A.
1992-01-01
Mechanical design features of the reactor chamber for the HYLIFE-11 inertial confinement fusion power plant are presented. A combination of oscillating and steady, molten salt streams are used for shielding and blast protection. The system is designed for an 8 Hz repetition rate. Beam path clearing, between shots, is accomplished with the oscillating flow. The mechanism for generating the oscillating streams is described. A design configuration of the vessel wall allows adequate cooling and provides extra shielding to reduce thermal stresses to tolerable levels. The bottom portion of the reactor chamber is designed to minimize splash back of the high velocity (20 m/s) salt streams and also recover up to half of the dynamic head
Schema Design and Normalization Algorithm for XML Databases Model
Directory of Open Access Journals (Sweden)
Samir Abou El-Seoud
2009-06-01
Full Text Available In this paper we study the problem of schema design and normalization in XML databases model. We show that, like relational databases, XML documents may contain redundant information, and this redundancy may cause update anomalies. Furthermore, such problems are caused by certain functional dependencies among paths in the document. Based on our research works, in which we presented the functional dependencies and normal forms of XML Schema, we present the decomposition algorithm for converting any XML Schema into normalized one, that satisfies X-BCNF.
Directory of Open Access Journals (Sweden)
Yi Zhang
2012-01-01
Full Text Available In consideration of the significant role the brake plays in ensuring the fast and safe running of vehicles, and since the present parameter optimization design models of brake are far from the practical application, this paper proposes a multiobjective optimization model of drum brake, aiming at maximizing the braking efficiency and minimizing the volume and temperature rise of drum brake. As the commonly used optimization algorithms are of some deficiency, we present a differential evolution cellular multiobjective genetic algorithm (DECell by introducing differential evolution strategy into the canonical cellular genetic algorithm for tackling this problem. For DECell, the gained Pareto front could be as close as possible to the exact Pareto front, and also the diversity of nondominated individuals could be better maintained. The experiments on the test functions reveal that DECell is of good performance in solving high-dimension nonlinear multiobjective problems. And the results of optimizing the new brake model indicate that DECell obviously outperforms the compared popular algorithm NSGA-II concerning the number of obtained brake design parameter sets, the speed, and stability for finding them.
Optimization Algorithms for Calculation of the Joint Design Point in Parallel Systems
DEFF Research Database (Denmark)
Enevoldsen, I.; Sørensen, John Dalsgaard
1992-01-01
In large structures it is often necessary to estimate the reliability of the system by use of parallel systems. Optimality criteria-based algorithms for calculation of the joint design point in a parallel system are described and efficient active set strategies are developed. Three possible...
Mechanical design of electric motors
Tong, Wei
2014-01-01
Rapid increases in energy consumption and emphasis on environmental protection have posed challenges for the motor industry, as has the design and manufacture of highly efficient, reliable, cost-effective, energy-saving, quiet, precisely controlled, and long-lasting electric motors.Suitable for motor designers, engineers, and manufacturers, as well as maintenance personnel, undergraduate and graduate students, and academic researchers, Mechanical Design of Electric Motors provides in-depth knowledge of state-of-the-art design methods and developments of electric motors. From motor classificati
A Novel Spectrum Scheduling Scheme with Ant Colony Optimization Algorithm
Directory of Open Access Journals (Sweden)
Liping Liu
2018-01-01
Full Text Available Cognitive radio is a promising technology for improving spectrum utilization, which allows cognitive users access to the licensed spectrum while primary users are absent. In this paper, we design a resource allocation framework based on graph theory for spectrum assignment in cognitive radio networks. The framework takes into account the constraints that interference for primary users and possible collision among cognitive users. Based on the proposed model, we formulate a system utility function to maximize the system benefit. Based on the proposed model and objective problem, we design an improved ant colony optimization algorithm (IACO from two aspects: first, we introduce differential evolution (DE process to accelerate convergence speed by monitoring mechanism; then we design a variable neighborhood search (VNS process to avoid the algorithm falling into the local optimal. Simulation results demonstrate that the improved algorithm achieves better performance.
Directory of Open Access Journals (Sweden)
Zhen GAO
2010-08-01
Full Text Available In this paper, a novel multidimensional accelerometer is proposed based on fully decoupled compliant parallel mechanism. Three separated chains, which are served as the elastic body, are perpendicular to each other for sensing the kinetic information in different directions without decoupling process. As the crucial part of the whole sensor structure, the revolute and prismatic joints in three pairwise orthogonal branches of the parallel mechanism are manufactured with the alloy aluminium as flexure hinge-based compliant joints. The structure development is first introduced, followed by the comprehensive finite-element analysis including the strain of the sensitive legs, modal analysis for total deformation under different frequency, and the performance of harmonic response. Then, the shape optimization is conducted to reduce the unnecessary parts. Compliance optimization with particle swarm algorithm is implemented to redesign the dimension of the sensitive legs. The research supplies a new viewpoint for the mechanical design of physical sensor, especially acceleration sensor.
Energy Technology Data Exchange (ETDEWEB)
Jayalal, M.L., E-mail: jayalal@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Kumar, L. Satish, E-mail: satish@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Jehadeesan, R., E-mail: jeha@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Rajeswari, S., E-mail: raj@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Satya Murty, S.A.V., E-mail: satya@igcar.gov.in [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India); Balasubramaniyan, V.; Chetal, S.C. [Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, Tamil Nadu (India)
2011-10-15
Highlights: > We model design optimization of a vital reactor component using Genetic Algorithm. > Real-parameter Genetic Algorithm is used for steam condenser optimization study. > Comparison analysis done with various Genetic Algorithm related mechanisms. > The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.
Directory of Open Access Journals (Sweden)
Dawid Połap
2017-09-01
Full Text Available In the proposed article, we present a nature-inspired optimization algorithm, which we called Polar Bear Optimization Algorithm (PBO. The inspiration to develop the algorithm comes from the way polar bears hunt to survive in harsh arctic conditions. These carnivorous mammals are active all year round. Frosty climate, unfavorable to other animals, has made polar bears adapt to the specific mode of exploration and hunting in large areas, not only over ice but also water. The proposed novel mathematical model of the way polar bears move in the search for food and hunt can be a valuable method of optimization for various theoretical and practical problems. Optimization is very similar to nature, similarly to search for optimal solutions for mathematical models animals search for optimal conditions to develop in their natural environments. In this method. we have used a model of polar bear behaviors as a search engine for optimal solutions. Proposed simulated adaptation to harsh winter conditions is an advantage for local and global search, while birth and death mechanism controls the population. Proposed PBO was evaluated and compared to other meta-heuristic algorithms using sample test functions and some classical engineering problems. Experimental research results were compared to other algorithms and analyzed using various parameters. The analysis allowed us to identify the leading advantages which are rapid recognition of the area by the relevant population and efficient birth and death mechanism to improve global and local search within the solution space.
A methodology for the geometric design of heat recovery steam generators applying genetic algorithms
International Nuclear Information System (INIS)
Durán, M. Dolores; Valdés, Manuel; Rovira, Antonio; Rincón, E.
2013-01-01
This paper shows how the geometric design of heat recovery steam generators (HRSG) can be achieved. The method calculates the product of the overall heat transfer coefficient (U) by the area of the heat exchange surface (A) as a function of certain thermodynamic design parameters of the HRSG. A genetic algorithm is then applied to determine the best set of geometric parameters which comply with the desired UA product and, at the same time, result in a small heat exchange area and low pressure losses in the HRSG. In order to test this method, the design was applied to the HRSG of an existing plant and the results obtained were compared with the real exchange area of the steam generator. The findings show that the methodology is sound and offers reliable results even for complex HRSG designs. -- Highlights: ► The paper shows a methodology for the geometric design of heat recovery steam generators. ► Calculates product of the overall heat transfer coefficient by heat exchange area as a function of certain HRSG thermodynamic design parameters. ► It is a complement for the thermoeconomic optimization method. ► Genetic algorithms are used for solving the optimization problem
The design of control algorithm for automatic start-up model of HWRR
International Nuclear Information System (INIS)
Guo Wenqi
1990-01-01
The design of control algorithm for automatic start-up model of HWRR (Heavy Water Research Reactor), the calculation of μ value and the application of digital compensator are described. Finally The flow diagram of the automatic start-up and digital compensator program for HWRR are given
Design of Wire Antennas by Using an Evolved Particle Swarm Optimization Algorithm
Lepelaars, E.S.A.M.; Zwamborn, A.P.M.; Rogovic, A.; Marasini, C.; Monorchio, A.
2007-01-01
A Particle Swarm Optimization (PSO) algorithm has been used in conjunction with a full-wave numerical code based on the Method of Moments (MoM) to design and optimize wire antennas. The PSO is a robust stochastic evolutionary numerical technique that is very effective in optimizing multidimensional
Mitigation of mechanical loads of NREL 5MW wind turbine tower
International Nuclear Information System (INIS)
Nam, Yoonsu; Im, Chang Hee
2012-01-01
As the size of a wind turbine increases, the mechanical structure has to have an increasing mechanical stiffness that is sufficient to withstand mechanical fatigue loads over a lifespan of more than 20 years. However, this leads to a heavier mechanical design, which means a high material cost during wind turbine manufacturing. Therefore, lightweight design of a wind turbine is an important design constraint. Usually, a lightweight mechanical structure has low damping. Therefore, if it is subjected to a disturbance, it will oscillate continuously. This study deals with the active damping control of a wind turbine tower. An algorithm that mitigates the mechanical loads of a wind turbine tower is introduced. The effectiveness of this algorithm is verified through a numerical simulation using GH Bladed, which is a commercial aero elastic code for wind turbines
Stiffness and damping in mechanical design
National Research Council Canada - National Science Library
Rivin, Eugene I
1999-01-01
... important conceptual issues are stiffness of mechanical structures and their components and damping in mechanical systems sensitive to and/or generating vibrations. Stiffness and strength are the most important criteria for many mechanical designs. However, although there are hundreds of books on various aspects of strength, and strength issues ar...
A preliminary design of mechanical device on industrial digital radiography equipment design
International Nuclear Information System (INIS)
Nur Khasan; Samuel Praptoyo
2015-01-01
A preliminary design of mechanical device on industrial digital radiography equipment has been done. this design is intended as a basis for the manufacture of complete facilities for the realization a prototype on industrial digital radiography equipment. the design and construction were carried out by paying attention to the general configuration of the basic design in which its mechanical design has several components with specific dimensions and heavy mass. this design consist of a main frame holder, flat panel detector support and hydraulic hand stacker for mounting the x-ray machine. this mechanical device design will then be fabricated to facilitate and assist work of digital radiographic retrieval. computer application programs sketch-up is used to draw this design and the analysis stress of autodesk inventor to analysis the strength construction design. the results of this design are the configuration drawing, sketch drawings of construction and the safety factor of construction design with a minimum value of 2.39 as well as a maximum value of 15 when to be simulated by the load 500 Kg which is 4 times of total workload. (author)
Directory of Open Access Journals (Sweden)
Yue Wu
2017-01-01
Full Text Available Firefly Algorithm (FA, for short is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly, development of structural topology optimization method and the basic principle of standard FA are introduced in detail. Then, in order to apply the algorithm to optimization problems with discrete variables, the initial positions of fireflies and the position updating formula are discretized. By embedding the random-weight and enhancing the attractiveness, the performance of this algorithm is improved, and thus an Improved Firefly Algorithm (IFA, for short is proposed. Furthermore, using size variables which are capable of including topology variables and size and topology optimization for trusses with discrete variables is formulated based on the Ground Structure Approach. The essential techniques of variable elastic modulus technology and geometric construction analysis are applied in the structural analysis process. Subsequently, an optimization method for the size and topological design of trusses based on the IFA is introduced. Finally, two numerical examples are shown to verify the feasibility and efficiency of the proposed method by comparing with different deterministic methods.
International Nuclear Information System (INIS)
Alpman, Emre
2014-01-01
The effect of selecting the twist angle and chord length distributions on the wind turbine blade design was investigated by performing aerodynamic optimization of a two-bladed stall regulated horizontal axis wind turbine. Twist angle and chord length distributions were defined using Bezier curve using 3, 5, 7 and 9 control points uniformly distributed along the span. Optimizations performed using a micro-genetic algorithm with populations composed of 5, 10, 15, 20 individuals showed that, the number of control points clearly affected the outcome of the process; however the effects were different for different population sizes. The results also showed the superiority of micro-genetic algorithm over a standard genetic algorithm, for the selected population sizes. Optimizations were also performed using a macroevolutionary algorithm and the resulting best blade design was compared with that yielded by micro-genetic algorithm
Design principles and algorithms for automated air traffic management
Erzberger, Heinz
1995-01-01
This paper presents design principles and algorithm for building a real time scheduler. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high altitude airspace far from the airport and low altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time.
Designing shields for KeV photons with genetic algorithms
International Nuclear Information System (INIS)
Asbury, Stephen; Holloway, James P.
2011-01-01
Shielding of x-ray sources and low energy gamma rays is often accomplished with lead aprons, comprising a thin layer (0.5 mm to 1 mm) of lead or similar high-Z material. In previous work the authors used Genetic Algorithms to explore the design of a shadow shield for space applications. Now those techniques have been applied to the problem of shielding humans from low energy gamma radiation. This paper uses a simple geometry to explore layering various materials as a method to reduce mass and dose for thin gamma shields. The genetic algorithms discover layers of materials with various Z is in fact more effective than an equivalent mass of Pb alone for lower energy gammas, but as the incident radiation energy increases the efficacy of such layering diminishes. The utility of varying Z for lower energy gammas is in part due to their complementary K-edges, where one material compensates for the transmission that would occur just below the K-edge in another material. (author)
Robust Design of Sounds in Mechanical Mechanisms
DEFF Research Database (Denmark)
Boegedal Jensen, Annemette; Munch, Natasja; Howard, Thomas J.
2015-01-01
mechanism consisting of a toothed rack and a click arm. First several geometries of the teeth and the click arm’s head were investigated to identify the most robust and repeatable design. It was found that a flat surface in the valleys between the teeth is very beneficial in relation to repeatability...
Design of compliant mechanisms with selective compliance
International Nuclear Information System (INIS)
Hasse, Alexander; Campanile, Lucio Flavio
2009-01-01
Conventional mechanisms provide a defined mobility, which expresses the number of degrees of freedom of the mechanism. This allows the system to be driven by a low number of control outputs. This property is virtually retained in the case of compliant mechanisms with lumped compliance, which are obtained by replacing the conventional hinges by solid-state ones. Compliant mechanisms with distributed compliance have, in general, an infinite number of degrees of freedom and therefore cannot guarantee defined kinematics. In this paper the concept of compliant mechanisms with selective compliance is introduced. This special class of compliant mechanisms combines the advantages of distributed compliance with the easy controllability of systems with defined kinematics. The task is accomplished by introducing a new design criterion based on a modal formulation. After this design criterion has been implemented in an optimization formulation for a formal optimization procedure, mechanisms are obtained in which a freely chosen deformation pattern is associated with a low deformation energy while other deformation patterns are considerably stiffer. Besides the description of the modal design criterion and the associated objective function, the sensitivity analysis of the objective function is presented and an application example is shown
Genetic algorithms for optimal design and control of adaptive structures
Ribeiro, R; Dias-Rodrigues, J; Vaz, M
2000-01-01
Future High Energy Physics experiments require the use of light and stable structures to support their most precise radiation detection elements. These large structures must be light, highly stable, stiff and radiation tolerant in an environment where external vibrations, high radiation levels, material aging, temperature and humidity gradients are not negligible. Unforeseen factors and the unknown result of the coupling of environmental conditions, together with external vibrations, may affect the position stability of the detectors and their support structures compromising their physics performance. Careful optimization of static and dynamic behavior must be an essential part of the engineering design. Genetic Algorithms ( GA) belong to the group of probabilistic algorithms, combining elements of direct and stochastic search. They are more robust than existing directed search methods with the advantage of maintaining a population of potential solutions. There is a class of optimization problems for which Ge...
Reduced scale PWR passive safety system designing by genetic algorithms
International Nuclear Information System (INIS)
Cunha, Joao J. da; Alvim, Antonio Carlos M.; Lapa, Celso Marcelo Franklin
2007-01-01
This paper presents the concept of 'Design by Genetic Algorithms (DbyGA)', applied to a new reduced scale system problem. The design problem of a passive thermal-hydraulic safety system, considering dimensional and operational constraints, has been solved. Taking into account the passive safety characteristics of the last nuclear reactor generation, a PWR core under natural circulation is used in order to demonstrate the methodology applicability. The results revealed that some solutions (reduced scale system DbyGA) are capable of reproducing, both accurately and simultaneously, much of the physical phenomena that occur in real scale and operating conditions. However, some aspects, revealed by studies of cases, pointed important possibilities to DbyGA methodological performance improvement
Design of the algorithm of photons migration in the multilayer skin structure
Bulykina, Anastasiia B.; Ryzhova, Victoria A.; Korotaev, Valery V.; Samokhin, Nikita Y.
2017-06-01
Design of approaches and methods of the oncological diseases diagnostics has special significance. It allows determining any kind of tumors at early stages. The development of optical and laser technologies provided increase of a number of methods allowing making diagnostic studies of oncological diseases. A promising area of biomedical diagnostics is the development of automated nondestructive testing systems for the study of the skin polarizing properties based on backscattered radiation detection. Specification of the examined tissue polarizing properties allows studying of structural properties change influenced by various pathologies. Consequently, measurement and analysis of the polarizing properties of the scattered optical radiation for the development of methods for diagnosis and imaging of skin in vivo appear relevant. The purpose of this research is to design the algorithm of photons migration in the multilayer skin structure. In this research, the algorithm of photons migration in the multilayer skin structure was designed. It is based on the use of the Monte Carlo method. Implemented Monte Carlo method appears as a tracking the paths of photons experiencing random discrete direction changes before they are released from the analyzed area or decrease their intensity to negligible levels. Modeling algorithm consists of the medium and the source characteristics generation, a photon generating considering spatial coordinates of the polar and azimuthal angles, the photon weight reduction calculating due to specular and diffuse reflection, the photon mean free path definition, the photon motion direction angle definition as a result of random scattering with a Henyey-Greenstein phase function, the medium's absorption calculation. Biological tissue is modeled as a homogeneous scattering sheet characterized by absorption, a scattering and anisotropy coefficients.
Computational Tools and Algorithms for Designing Customized Synthetic Genes
Directory of Open Access Journals (Sweden)
Nathan eGould
2014-10-01
Full Text Available Advances in DNA synthesis have enabled the construction of artificial genes, gene circuits, and genomes of bacterial scale. Freedom in de-novo design of synthetic constructs provides significant power in studying the impact of mutations in sequence features, and verifying hypotheses on the functional information that is encoded in nucleic and amino acids. To aid this goal, a large number of software tools of variable sophistication have been implemented, enabling the design of synthetic genes for sequence optimization based on rationally defined properties. The first generation of tools dealt predominantly with singular objectives such as codon usage optimization and unique restriction site incorporation. Recent years have seen the emergence of sequence design tools that aim to evolve sequences toward combinations of objectives. The design of optimal protein coding sequences adhering to multiple objectives is computationally hard, and most tools rely on heuristics to sample the vast sequence design space. In this review we study some of the algorithmic issues behind gene optimization and the approaches that different tools have adopted to redesign genes and optimize desired coding features. We utilize test cases to demonstrate the efficiency of each approach, as well as identify their strengths and limitations.
A Design of a Hybrid Non-Linear Control Algorithm
Directory of Open Access Journals (Sweden)
Farinaz Behrooz
2017-11-01
Full Text Available One of the high energy consuming devices in the buildings is the air-conditioning system. Designing a proper controller to consider the thermal comfort and simultaneously control the energy usage of the device will impact on the system energy efficiency and its performance. The aim of this study was to design a Multiple-Input and Multiple-Output (MIMO, non-linear, and intelligent controller on direct expansion air-conditioning system The control algorithm uses the Fuzzy Cognitive Map method as a main controller and the Generalized Predictive Control method is used for assigning the initial weights of the main controller. The results of the proposed controller shows that the controller was successfully designed and works in set point tracking and under disturbance rejection tests. The obtained results of the Generalized Predictive Control-Fuzzy Cognitive Map controller are compared with the previous MIMO Linear Quadratic Gaussian control design on the same direct expansion air-conditioning system under the same conditions. The comparative results indicate energy savings would be achieved with the proposed controller with long-term usage. Energy efficiency and thermal comfort conditions are achieved by the proposed controller.
International Nuclear Information System (INIS)
Jia Baoshan; Yu Jiyang; You Songbo
2005-01-01
This article focuses on the development of an improved genetic algorithm and its application in the optimal design of the ship nuclear reactor system, whose goal is to find a combination of system parameter values that minimize the mass or volume of the system given the power capacity requirement and safety criteria. An improved genetic algorithm (IGA) was developed using an 'average fitness value' grouping + 'specified survival probability' rank selection method and a 'separate-recombine' duplication operator. Combining with a simulated annealing algorithm (SAA) that continues the local search after the IGA reaches a satisfactory point, the algorithm gave satisfactory optimization results from both search efficiency and accuracy perspectives. This IGA-SAA algorithm successfully solved the design optimization problem of ship nuclear power system. It is an advanced and efficient methodology that can be applied to the similar optimization problems in other areas. (authors)
International Nuclear Information System (INIS)
Jayalal, M.L.; Kumar, L. Satish; Jehadeesan, R.; Rajeswari, S.; Satya Murty, S.A.V.; Balasubramaniyan, V.; Chetal, S.C.
2011-01-01
Highlights: → We model design optimization of a vital reactor component using Genetic Algorithm. → Real-parameter Genetic Algorithm is used for steam condenser optimization study. → Comparison analysis done with various Genetic Algorithm related mechanisms. → The results obtained are validated with the reference study results. - Abstract: This work explores the use of Real-parameter Genetic Algorithm and analyses its performance in the steam condenser (or Circulating Water System) optimization study of a 500 MW fast breeder nuclear reactor. Choice of optimum design parameters for condenser for a power plant from among a large number of technically viable combination is a complex task. This is primarily due to the conflicting nature of the economic implications of the different system parameters for maximizing the capitalized profit. In order to find the optimum design parameters a Real-parameter Genetic Algorithm model is developed and applied. The results obtained are validated with the reference study results.
Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong
2018-01-01
Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.
Numerical methods design, analysis, and computer implementation of algorithms
Greenbaum, Anne
2012-01-01
Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, and fractals. Filled with appealing examples that will motivate students, the textbook considers modern application areas, such as information retrieval and animation, and classical topics from physics and engineering. Exercises use MATLAB and promote understanding of computational results. The book gives instructors the flexibility to emphasize different aspects--design, analysis, or computer implementation--of numerical algorithms, depending on the background and interests of students. Designed for upper-division undergraduates in mathematics or computer science classes, the textbook assumes that students have prior knowledge of linear algebra and calculus, although these topics are reviewed in the text. Short discussions of the history of numerical methods are interspersed throughout the chapters. The book a...
Optimal Design of Low-Density SNP Arrays for Genomic Prediction: Algorithm and Applications.
Directory of Open Access Journals (Sweden)
Xiao-Lin Wu
Full Text Available Low-density (LD single nucleotide polymorphism (SNP arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for the optimal design of LD SNP chips. A multiple-objective, local optimization (MOLO algorithm was developed for design of optimal LD SNP chips that can be imputed accurately to medium-density (MD or high-density (HD SNP genotypes for genomic prediction. The objective function facilitates maximization of non-gap map length and system information for the SNP chip, and the latter is computed either as locus-averaged (LASE or haplotype-averaged Shannon entropy (HASE and adjusted for uniformity of the SNP distribution. HASE performed better than LASE with ≤1,000 SNPs, but required considerably more computing time. Nevertheless, the differences diminished when >5,000 SNPs were selected. Optimization was accomplished conditionally on the presence of SNPs that were obligated to each chromosome. The frame location of SNPs on a chip can be either uniform (evenly spaced or non-uniform. For the latter design, a tunable empirical Beta distribution was used to guide location distribution of frame SNPs such that both ends of each chromosome were enriched with SNPs. The SNP distribution on each chromosome was finalized through the objective function that was locally and empirically maximized. This MOLO algorithm was capable of selecting a set of approximately evenly-spaced and highly-informative SNPs, which in turn led to increased imputation accuracy compared with selection solely of evenly-spaced SNPs. Imputation accuracy increased with LD chip size, and imputation error rate was extremely low for chips with ≥3,000 SNPs. Assuming that genotyping or imputation error occurs at random, imputation error rate can be viewed as the upper limit for genomic prediction error. Our results show that about 25% of imputation error rate was propagated to genomic prediction in an Angus
Mechanical Design of Downhole Tractor Based on Two-Way Self-locking Mechanism
Fang, Delei; Shang, Jianzhong; Luo, Zirong; Wu, Guoheng; Liu, Yiying
2018-03-01
Based on the technology of horizontal well tractor, a kind of downhole tractor was developed which can realize Two-Way self-locking function. Aiming at the needs of horizontal well logging to realize the target of small size, high traction and high reliability, the tractor selects unique heart-shaped CAM as the locking mechanism. The motion principle of telescopic downhole tractor, the design of mechanical structure and locking principle of the locking mechanism are all analyzed. The mathematical expressions of traction are obtained by mechanical analysis of parallel support rod in the locking mechanism. The force analysis and contour design of the heart-shaped CAM are performed, which can lay the foundation for the development of tractor prototype.
Optimal Design of the Transverse Flux Machine Using a Fitted Genetic Algorithm with Real Parameters
DEFF Research Database (Denmark)
Argeseanu, Alin; Ritchie, Ewen; Leban, Krisztina Monika
2012-01-01
This paper applies a fitted genetic algorithm (GA) to the optimal design of transverse flux machine (TFM). The main goal is to provide a tool for the optimal design of TFM that is an easy to use. The GA optimizes the analytic basic design of two TFM topologies: the C-core and the U-core. First...
Directory of Open Access Journals (Sweden)
Chenlu Miao
2016-01-01
Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.
A general theory known as the WAste Reduction (WASR) algorithm has been developed to describe the flow and the generation of potential environmental impact through a chemical process. This theory integrates environmental impact assessment into chemical process design Potential en...
Masoumi, Massoud; Raissi, Farshid; Ahmadian, Mahmoud; Keshavarzi, Parviz
2006-01-01
We are proposing that the recently proposed semiconductor-nanowire-molecular architecture (CMOL) is an optimum platform to realize encryption algorithms. The basic modules for the advanced encryption standard algorithm (Rijndael) have been designed using CMOL architecture. The performance of this design has been evaluated with respect to chip area and speed. It is observed that CMOL provides considerable improvement over implementation with regular CMOS architecture even with a 20% defect rate. Pseudo-optimum gate placement and routing are provided for Rijndael building blocks and the possibility of designing high speed, attack tolerant and long key encryptions are discussed.
International Nuclear Information System (INIS)
Bieniawski, Z.T.
1996-01-01
A good designer needs not only knowledge for designing (technical know-how that is used to generate alternative design solutions) but also must have knowledge about designing (appropriate principles and systematic methodology to follow). Concepts such as open-quotes design for manufactureclose quotes or open-quotes concurrent engineeringclose quotes are widely used in the industry. In the field of rock engineering, only limited attention has been paid to the design process because design of structures in rock masses presents unique challenges to the designers as a result of the uncertainties inherent in characterization of geologic media. However, a stage has now been reached where we are be able to sufficiently characterize rock masses for engineering purposes and identify the rock mechanics issues involved but are still lacking engineering design principles and methodology to maximize our design performance. This paper discusses the principles and methodology of the engineering design process directed to integrating site characterization activities with design, construction and performance of an underground repository. Using the latest information from the Yucca Mountain Project on geology, rock mechanics and starter tunnel design, the current lack of integration is pointed out and it is shown how rock mechanics issues can be effectively interwoven with repository design through a systematic design process methodology leading to improved repository performance. In essence, the design process is seen as the use of design principles within an integrating design methodology, leading to innovative problem solving. In particular, a new concept of open-quotes Design for Constructibility and Performanceclose quotes is introduced. This is discussed with respect to ten rock mechanics issues identified for repository design and performance
Object-Oriented/Data-Oriented Design of a Direct Simulation Monte Carlo Algorithm
Liechty, Derek S.
2014-01-01
Over the past decade, there has been much progress towards improved phenomenological modeling and algorithmic updates for the direct simulation Monte Carlo (DSMC) method, which provides a probabilistic physical simulation of gas Rows. These improvements have largely been based on the work of the originator of the DSMC method, Graeme Bird. Of primary importance are improved chemistry, internal energy, and physics modeling and a reduction in time to solution. These allow for an expanded range of possible solutions In altitude and velocity space. NASA's current production code, the DSMC Analysis Code (DAC), is well-established and based on Bird's 1994 algorithms written in Fortran 77 and has proven difficult to upgrade. A new DSMC code is being developed in the C++ programming language using object-oriented and data-oriented design paradigms to facilitate the inclusion of the recent improvements and future development activities. The development efforts on the new code, the Multiphysics Algorithm with Particles (MAP), are described, and performance comparisons are made with DAC.
A genetic algorithm for the optimization of fiber angles in composite laminates
International Nuclear Information System (INIS)
Hwang, Shun Fa; Hsu, Ya Chu; Chen, Yuder
2014-01-01
A genetic algorithm for the optimization of composite laminates is proposed in this work. The well-known roulette selection criterion, one-point crossover operator, and uniform mutation operator are used in this genetic algorithm to create the next population. To improve the hill-climbing capability of the algorithm, adaptive mechanisms designed to adjust the probabilities of the crossover and mutation operators are included, and the elite strategy is enforced to ensure the quality of the optimum solution. The proposed algorithm includes a new operator called the elite comparison, which compares and uses the differences in the design variables of the two best solutions to find possible combinations. This genetic algorithm is tested in four optimization problems of composite laminates. Specifically, the effect of the elite comparison operator is evaluated. Results indicate that the elite comparison operator significantly accelerates the convergence of the algorithm, which thus becomes a good candidate for the optimization of composite laminates.
An Incremental High-Utility Mining Algorithm with Transaction Insertion
Gan, Wensheng; Zhang, Binbin
2015-01-01
Association-rule mining is commonly used to discover useful and meaningful patterns from a very large database. It only considers the occurrence frequencies of items to reveal the relationships among itemsets. Traditional association-rule mining is, however, not suitable in real-world applications since the purchased items from a customer may have various factors, such as profit or quantity. High-utility mining was designed to solve the limitations of association-rule mining by considering both the quantity and profit measures. Most algorithms of high-utility mining are designed to handle the static database. Fewer researches handle the dynamic high-utility mining with transaction insertion, thus requiring the computations of database rescan and combination explosion of pattern-growth mechanism. In this paper, an efficient incremental algorithm with transaction insertion is designed to reduce computations without candidate generation based on the utility-list structures. The enumeration tree and the relationships between 2-itemsets are also adopted in the proposed algorithm to speed up the computations. Several experiments are conducted to show the performance of the proposed algorithm in terms of runtime, memory consumption, and number of generated patterns. PMID:25811038
An Incremental High-Utility Mining Algorithm with Transaction Insertion
Directory of Open Access Journals (Sweden)
Jerry Chun-Wei Lin
2015-01-01
Full Text Available Association-rule mining is commonly used to discover useful and meaningful patterns from a very large database. It only considers the occurrence frequencies of items to reveal the relationships among itemsets. Traditional association-rule mining is, however, not suitable in real-world applications since the purchased items from a customer may have various factors, such as profit or quantity. High-utility mining was designed to solve the limitations of association-rule mining by considering both the quantity and profit measures. Most algorithms of high-utility mining are designed to handle the static database. Fewer researches handle the dynamic high-utility mining with transaction insertion, thus requiring the computations of database rescan and combination explosion of pattern-growth mechanism. In this paper, an efficient incremental algorithm with transaction insertion is designed to reduce computations without candidate generation based on the utility-list structures. The enumeration tree and the relationships between 2-itemsets are also adopted in the proposed algorithm to speed up the computations. Several experiments are conducted to show the performance of the proposed algorithm in terms of runtime, memory consumption, and number of generated patterns.
Mechanical testing - designers need: a view at component design and operations stages
International Nuclear Information System (INIS)
Shrivastava, S.K.
2007-01-01
Mechanical design of any component requires knowledge of values of various material properties which designer(s) make(s) use in designing the component. In design of nuclear power plant components, it assumes even greater importance in view of degree of precision and accuracy with which the values of various properties are required. This is in turn demands, high accuracy in testing machines and measuring methods. In this paper, attempt has been made to bring out that even from conventional tension test, how designer today looks for availability of engineering stress-strain diagram preferably through digitally acquired data points during the test from which he can derive values of Ramberg-Osgood parameters for use in fracture mechanics based analysis. Attempt has been also made to provide account of some of important fracture mechanics related tests which have been evolved in last two decades and designers need for evolution of simple test techniques to measure many more fracture mechanics related parameters as well as cater to constraints such as shape and size of material available from the components. Nuclear power plant has been primarily kept in view and ASME. Section III NB, ASME Section XI and relevant ASTM Standards have been taken as standard references. Further pressure retaining materials of pressure vessels/Reactor Pressure Vessels have been kept in view. (author)
Mechanical Design Handbook for Elastomers
Darlow, M.; Zorzi, E.
1986-01-01
Mechanical Design Handbook for Elastomers reviews state of art in elastomer-damper technology with particular emphasis on applications of highspeed rotor dampers. Self-contained reference but includes some theoretical discussion to help reader understand how and why dampers used for rotating machines. Handbook presents step-by-step procedure for design of elastomer dampers and detailed examples of actual elastomer damper applications.
Reliability and mechanical design
International Nuclear Information System (INIS)
Lemaire, Maurice
1997-01-01
A lot of results in mechanical design are obtained from a modelisation of physical reality and from a numerical solution which would lead to the evaluation of needs and resources. The goal of the reliability analysis is to evaluate the confidence which it is possible to grant to the chosen design through the calculation of a probability of failure linked to the retained scenario. Two types of analysis are proposed: the sensitivity analysis and the reliability analysis. Approximate methods are applicable to problems related to reliability, availability, maintainability and safety (RAMS)
Algorithms in Algebraic Geometry
Dickenstein, Alicia; Sommese, Andrew J
2008-01-01
In the last decade, there has been a burgeoning of activity in the design and implementation of algorithms for algebraic geometric computation. Some of these algorithms were originally designed for abstract algebraic geometry, but now are of interest for use in applications and some of these algorithms were originally designed for applications, but now are of interest for use in abstract algebraic geometry. The workshop on Algorithms in Algebraic Geometry that was held in the framework of the IMA Annual Program Year in Applications of Algebraic Geometry by the Institute for Mathematics and Its
Fan, Xiao-Ning; Zhi, Bo
2017-07-01
Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization (RBDO) offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliability strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reliability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its α-percentile performance, thereby avoiding convergence failure, calculation error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.
Directory of Open Access Journals (Sweden)
Andreas König
2009-11-01
Full Text Available The emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain of the computational system model still has to be assembled manually by experienced designers in a time and labor consuming process. In this research work, this challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multi-sensor systems employing multi-objective evolutionary computation are introduced. The proposed methodology tackles the challenge of rapid-prototyping of such systems under realization constraints and, additionally, includes features of system instance specific self-correction for sustained operation of a large volume and in a dynamically changing environment. The extension of these concepts to the reconfigurable hardware platform renders so called self-x sensor systems, which stands, e.g., for self-monitoring, -calibrating, -trimming, and -repairing/-healing systems. Selected experimental results prove the applicability and effectiveness of our proposed methodology and emerging tool. By our approach, competitive results were achieved with regard to classification accuracy, flexibility, and design speed under additional design constraints.
Autonomous Star Tracker Algorithms
DEFF Research Database (Denmark)
Betto, Maurizio; Jørgensen, John Leif; Kilsgaard, Søren
1998-01-01
Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances.......Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances....
Son, Min; Ko, Sangho; Koo, Jaye
2014-06-01
A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was applied, and the profile was calculated using Rao's method. One-dimensional heat transfer was assumed along the profile, and cooling channels were designed. For the gas-generator design, non-equilibrium properties were derived from a counterflow analysis, and a vaporization model for the fuel droplet was adopted to calculate residence time. Finally, a genetic algorithm was adopted to optimize the designs. The combustor and gas generator were optimally designed for 30-tonf, 75-tonf, and 150-tonf engines. The optimized combustors demonstrated superior design characteristics when compared with previous non-optimized results. Wall temperatures at the nozzle throat were optimized to satisfy the requirement of 800 K, and specific impulses were maximized. In addition, the target turbine power and a burned-gas temperature of 1000 K were obtained from the optimized gas-generator design.
Self-repair networks a mechanism design
Ishida, Yoshiteru
2015-01-01
This book describes the struggle to introduce a mechanism that enables next-generation information systems to maintain themselves. Our generation observed the birth and growth of information systems, and the Internet in particular. Surprisingly information systems are quite different from conventional (energy, material-intensive) artificial systems, and rather resemble biological systems (information-intensive systems). Many artificial systems are designed based on (Newtonian) physics assuming that every element obeys simple and static rules; however, the experience of the Internet suggests a different way of designing where growth cannot be controlled but self-organized with autonomous and selfish agents. This book suggests using game theory, a mechanism design in particular, for designing next-generation information systems which will be self-organized by collective acts with autonomous components. The challenge of mapping a probability to time appears repeatedly in many forms throughout this book. The book...
Design of planar articulated mechanisms using branch and bound
DEFF Research Database (Denmark)
Stolpe, Mathias; Kawamoto, Atsushi
2005-01-01
This paper considers an optimization model and a solution method for the design of two-dimensional mechanical mechanisms. The mechanism design problem is modeled as a nonconvex mixed integer program which allows the optimal topology and geometry of the mechanism to be determined simultaneously...
Aniba, Ghassane
2011-04-01
This paper presents an optimal adaptive modulation (AM) algorithm designed using a cross-layer approach which combines truncated automatic repeat request (ARQ) protocol and packet combining. Transmissions are performed over multiple-input multiple-output (MIMO) Nakagami fading channels, and retransmitted packets are not necessarily modulated using the same modulation format as in the initial transmission. Compared to traditional approach, cross-layer design based on the coupling across the physical and link layers, has proven to yield better performance in wireless communications. However, there is a lack for the performance analysis and evaluation of such design when the ARQ protocol is used in conjunction with packet combining. Indeed, previous works addressed the link layer performance of AM with truncated ARQ but without packet combining. In addition, previously proposed AM algorithms are not optimal and can provide poor performance when packet combining is implemented. Herein, we first show that the packet loss rate (PLR) resulting from the combining of packets modulated with different constellations can be well approximated by an exponential function. This model is then used in the design of an optimal AM algorithm for systems employing packet combining, truncated ARQ and MIMO antenna configurations, considering transmission over Nakagami fading channels. Numerical results are provided for operation with or without packet combining, and show the enhanced performance and efficiency of the proposed algorithm in comparison with existing ones. © 2011 IEEE.
Tel, G.
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of
Directory of Open Access Journals (Sweden)
Rachmad Vidya Wicaksana Putra
2013-09-01
Full Text Available In the literature, several approaches of designing a DCT/IDCT-based image compression system have been proposed. In this paper, we present a new RTL design approach with as main focus developing a DCT/IDCT-based image compression architecture using a self-created algorithm. This algorithm can efficiently minimize the amount of shifter -adders to substitute multiplier s. We call this new algorithm the multiplication from Common Binary Expression (mCBE Algorithm. Besides this algorithm, we propose alternative quantization numbers, which can be implemented simply as shifters in digital hardware. Mostly, these numbers can retain a good compressed-image quality compared to JPEG recommendations. These ideas lead to our design being small in circuit area, multiplierless, and low in complexity. The proposed 8-point 1D-DCT design has only six stages, while the 8-point 1D-IDCT design has only seven stages (one stage being defined as equal to the delay of one shifter or 2-input adder. By using the pipelining method, we can achieve a high-speed architecture with latency as a trade-off consideration. The design has been synthesized and can reach a speed of up to 1.41ns critical path delay (709.22MHz.
Latief, Y.; Berawi, M. A.; Koesalamwardi, A. B.; Supriadi, L. S. R.
2018-03-01
Near Zero Energy House (NZEH) is a housing building that provides energy efficiency by using renewable energy technologies and passive house design. Currently, the costs for NZEH are quite expensive due to the high costs of the equipment and materials for solar panel, insulation, fenestration and other renewable energy technology. Therefore, a study to obtain the optimum design of a NZEH is necessary. The aim of the optimum design is achieving an economical life cycle cost performance of the NZEH. One of the optimization methods that could be utilized is Genetic Algorithm. It provides the method to obtain the optimum design based on the combinations of NZEH variable designs. This paper discusses the study to identify the optimum design of a NZEH that provides an optimum life cycle cost performance using Genetic Algorithm. In this study, an experiment through extensive design simulations of a one-level house model was conducted. As a result, the study provide the optimum design from combinations of NZEH variable designs, which are building orientation, window to wall ratio, and glazing types that would maximize the energy generated by photovoltaic panel. Hence, the design would support an optimum life cycle cost performance of the house.
An Improved Task Scheduling Algorithm for Intelligent Control in Tiny Mechanical System
Directory of Open Access Journals (Sweden)
Jialiang Wang
2014-01-01
Full Text Available Wireless sensor network (WSN has been already widely used in many fields in terms of industry, agriculture, and military, and so forth. The basic composition is WSN nodes that are capable of performing processing, gathering information, and communicating with other connected nodes in the network. The main components of a WSN node are microcontroller, transceiver, and some sensors. Undoubtedly, it also can be added with some actuators to form a tiny mechanical system. Under this case, the existence of task preemption while executing operating system will not only cost more energy for WSN nodes themselves, but also bring unacceptable system states caused by vibrations. However for these nodes, task I/O delays are inevitable due to the existence of task preemption, which will bring extra overhead for the whole system, and even bring unacceptable system states caused by vibrations. This paper mainly considers the earliest deadline first (EDF task preemption algorithm executed in WSN OS and proposes an improved task preemption algorithm so as to lower the preemption overhead and I/O delay and then improve the system performance. The experimental results show that the improved task preemption algorithm can reduce the I/O delay effectively, so the real-time processing ability of the system is enhanced.
Mechanical Drawing and Design.
Mikulsky, Marilyn; McEnaney, Walter K.
A syllabus is provided for a comprehensive foundation course in mechanical drawing and design for grades 9, 10, 11, or 12 that is prerequisite to advanced elective courses. Introductory materials include course objectives, an overview of basic concepts, and guidelines for implementation. Brief discussions of and suggestions for the areas of design…
DEFF Research Database (Denmark)
Wang, Yong; Cai, Zixing; Zhou, Yuren
2009-01-01
A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...
Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm
International Nuclear Information System (INIS)
Duan, Chen; Wang, Xinggang; Shu, Shuiming; Jing, Changwei; Chang, Huawei
2014-01-01
Highlights: • An improved thermodynamic model taking into account irreversibility parameter was developed. • A multi-objective optimization method for designing Stirling engine was investigated. • Multi-objective particle swarm optimization algorithm was adopted in the area of Stirling engine for the first time. - Abstract: In the recent years, the interest in Stirling engine has remarkably increased due to its ability to use any heat source from outside including solar energy, fossil fuels and biomass. A large number of studies have been done on Stirling cycle analysis. In the present study, a mathematical model based on thermodynamic analysis of Stirling engine considering regenerative losses and internal irreversibilities has been developed. Power output, thermal efficiency and the cycle irreversibility parameter of Stirling engine are optimized simultaneously using Particle Swarm Optimization (PSO) algorithm, which is more effective than traditional genetic algorithms. In this optimization problem, some important parameters of Stirling engine are considered as decision variables, such as temperatures of the working fluid both in the high temperature isothermal process and in the low temperature isothermal process, dead volume ratios of each heat exchanger, volumes of each working spaces, effectiveness of the regenerator, and the system charge pressure. The Pareto optimal frontier is obtained and the final design solution has been selected by Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP). Results show that the proposed multi-objective optimization approach can significantly outperform traditional single objective approaches
Low-cost satellite mechanical design and construction
Boisjolie-Gair, Nathaniel; Straub, Jeremy
2017-05-01
This paper presents a discussion of techniques for low-cost design and construction of a CubeSat mechanical structure that can serve as a basis for academic programs and a starting point for government, military and commercial large-scale sensing networks, where the cost of each node must be minimized to facilitate system affordability and lower the cost and associated risk of losing any node. Spacecraft Design plays a large role in manufacturability. An intentionally simplified mechanical design is presented which reduces machining costs, as compared to more intricate designs that were considered. Several fabrication approaches are evaluated relative to the low-cost goal.
International Nuclear Information System (INIS)
Martin-del-Campo, Cecilia; Francois, Juan Luis; Avendano, Linda; Gonzalez, Mario
2004-01-01
An optimization system based on Genetic Algorithms (GAs), in combination with expert knowledge coded in heuristics rules, was developed for the design of optimized boiling water reactor (BWR) fuel loading patterns. The system was coded in a computer program named Loading Pattern Optimization System based on Genetic Algorithms, in which the optimization code uses GAs to select candidate solutions, and the core simulator code CM-PRESTO to evaluate them. A multi-objective function was built to maximize the cycle energy length while satisfying power and reactivity constraints used as BWR design parameters. Heuristic rules were applied to satisfy standard fuel management recommendations as the Control Cell Core and Low Leakage loading strategies, and octant symmetry. To test the system performance, an optimized cycle was designed and compared against an actual operating cycle of Laguna Verde Nuclear Power Plant, Unit I
Directory of Open Access Journals (Sweden)
Long-Hua Ma
2011-08-01
Full Text Available A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform.
Xiao, Li; Cai, Qin; Li, Zhilin; Zhao, Hongkai; Luo, Ray
2014-11-25
A multi-scale framework is proposed for more realistic molecular dynamics simulations in continuum solvent models by coupling a molecular mechanics treatment of solute with a fluid mechanics treatment of solvent. This article reports our initial efforts to formulate the physical concepts necessary for coupling the two mechanics and develop a 3D numerical algorithm to simulate the solvent fluid via the Navier-Stokes equation. The numerical algorithm was validated with multiple test cases. The validation shows that the algorithm is effective and stable, with observed accuracy consistent with our design.
Design definition of a mechanical capacitor
Michaelis, T. D.; Schlieban, E. W.; Scott, R. D.
1977-01-01
A design study and analyses of a 10 kW-hr, 15 kW mechanical capacitor system was studied. It was determined that magnetically supported wheels constructed of advanced composites have the potential for high energy density and high power density. Structural concepts are analyzed that yield the highest energy density of any structural design yet reported. Particular attention was paid to the problem of 'friction' caused by magnetic and I to the second power R losses in the suspension and motor-generator subsystems, and low design friction levels have been achieved. The potentially long shelf life of this system, and the absence of wearing parts, provide superior performance over conventional flywheels supported with mechanical bearings. Costs and economies of energy storage wheels were reviewed briefly.
Directory of Open Access Journals (Sweden)
Oguz Emrah Turgut
2014-12-01
Full Text Available This study explores the thermal design of shell and tube heat exchangers by using Improved Intelligent Tuned Harmony Search (I-ITHS algorithm. Intelligent Tuned Harmony Search (ITHS is an upgraded version of harmony search algorithm which has an advantage of deciding intensification and diversification processes by applying proper pitch adjusting strategy. In this study, we aim to improve the search capacity of ITHS algorithm by utilizing chaotic sequences instead of uniformly distributed random numbers and applying alternative search strategies inspired by Artificial Bee Colony algorithm and Opposition Based Learning on promising areas (best solutions. Design variables including baffle spacing, shell diameter, tube outer diameter and number of tube passes are used to minimize total cost of heat exchanger that incorporates capital investment and the sum of discounted annual energy expenditures related to pumping and heat exchanger area. Results show that I-ITHS can be utilized in optimizing shell and tube heat exchangers.
Computational Design of Animated Mechanical Characters
Coros, Stelian; Thomaszewski, Bernhard; DRZ Team Team
2014-03-01
A factor key to the appeal of modern CG movies and video-games is that the virtual worlds they portray place no bounds on what can be imagined. Rapid manufacturing devices hold the promise of bringing this type of freedom to our own world, by enabling the fabrication of physical objects whose appearance, deformation behaviors and motions can be precisely specified. In order to unleash the full potential of this technology however, computational design methods that create digital content suitable for fabrication need to be developed. In recent work, we presented a computational design system that allows casual users to create animated mechanical characters. Given an articulated character as input, the user designs the animated character by sketching motion curves indicating how they should move. For each motion curve, our framework creates an optimized mechanism that reproduces it as closely as possible. The resulting mechanisms are attached to the character and then connected to each other using gear trains, which are created in a semi-automated fashion. The mechanical assemblies generated with our system can be driven with a single input driver, such as a hand-operated crank or an electric motor, and they can be fabricated using rapid prototyping devices.
Urselmann, Maren; Emmerich, Michael T. M.; Till, Jochen; Sand, Guido; Engell, Sebastian
2007-07-01
Engineering optimization often deals with large, mixed-integer search spaces with a rigid structure due to the presence of a large number of constraints. Metaheuristics, such as evolutionary algorithms (EAs), are frequently suggested as solution algorithms in such cases. In order to exploit the full potential of these algorithms, it is important to choose an adequate representation of the search space and to integrate expert-knowledge into the stochastic search operators, without adding unnecessary bias to the search. Moreover, hybridisation with mathematical programming techniques such as mixed-integer programming (MIP) based on a problem decomposition can be considered for improving algorithmic performance. In order to design problem-specific EAs it is desirable to have a set of design guidelines that specify properties of search operators and representations. Recently, a set of guidelines has been proposed that gives rise to so-called Metric-based EAs (MBEAs). Extended by the minimal moves mutation they allow for a generalization of EA with self-adaptive mutation strength in discrete search spaces. In this article, a problem-specific EA for process engineering task is designed, following the MBEA guidelines and minimal moves mutation. On the background of the application, the usefulness of the design framework is discussed, and further extensions and corrections proposed. As a case-study, a two-stage stochastic programming problem in chemical batch process scheduling is considered. The algorithm design problem can be viewed as the choice of a hierarchical decision structure, where on different layers of the decision process symmetries and similarities can be exploited for the design of minimal moves. After a discussion of the design approach and its instantiation for the case-study, the resulting problem-specific EA/MIP is compared to a straightforward application of a canonical EA/MIP and to a monolithic mathematical programming algorithm. In view of the
Python algorithms mastering basic algorithms in the Python language
Hetland, Magnus Lie
2014-01-01
Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data struc
The design of 3D scaffold for tissue engineering using automated scaffold design algorithm.
Mahmoud, Shahenda; Eldeib, Ayman; Samy, Sherif
2015-06-01
Several progresses have been introduced in the field of bone regenerative medicine. A new term tissue engineering (TE) was created. In TE, a highly porous artificial extracellular matrix or scaffold is required to accommodate cells and guide their growth in three dimensions. The design of scaffolds with desirable internal and external structure represents a challenge for TE. In this paper, we introduce a new method known as automated scaffold design (ASD) for designing a 3D scaffold with a minimum mismatches for its geometrical parameters. The method makes use of k-means clustering algorithm to separate the different tissues and hence decodes the defected bone portions. The segmented portions of different slices are registered to construct the 3D volume for the data. It also uses an isosurface rendering technique for 3D visualization of the scaffold and bones. It provides the ability to visualize the transplanted as well as the normal bone portions. The proposed system proves good performance in both the segmentation results and visualizations aspects.
International Nuclear Information System (INIS)
Tadaki, Kohtaro
2010-01-01
The statistical mechanical interpretation of algorithmic information theory (AIT, for short) was introduced and developed by our former works [K. Tadaki, Local Proceedings of CiE 2008, pp. 425-434, 2008] and [K. Tadaki, Proceedings of LFCS'09, Springer's LNCS, vol. 5407, pp. 422-440, 2009], where we introduced the notion of thermodynamic quantities, such as partition function Z(T), free energy F(T), energy E(T), statistical mechanical entropy S(T), and specific heat C(T), into AIT. We then discovered that, in the interpretation, the temperature T equals to the partial randomness of the values of all these thermodynamic quantities, where the notion of partial randomness is a stronger representation of the compression rate by means of program-size complexity. Furthermore, we showed that this situation holds for the temperature T itself, which is one of the most typical thermodynamic quantities. Namely, we showed that, for each of the thermodynamic quantities Z(T), F(T), E(T), and S(T) above, the computability of its value at temperature T gives a sufficient condition for T is an element of (0,1) to satisfy the condition that the partial randomness of T equals to T. In this paper, based on a physical argument on the same level of mathematical strictness as normal statistical mechanics in physics, we develop a total statistical mechanical interpretation of AIT which actualizes a perfect correspondence to normal statistical mechanics. We do this by identifying a microcanonical ensemble in the framework of AIT. As a result, we clarify the statistical mechanical meaning of the thermodynamic quantities of AIT.
Robust state feedback controller design of STATCOM using chaotic optimization algorithm
Directory of Open Access Journals (Sweden)
Safari Amin
2010-01-01
Full Text Available In this paper, a new design technique for the design of robust state feedback controller for static synchronous compensator (STATCOM using Chaotic Optimization Algorithm (COA is presented. The design is formulated as an optimization problem which is solved by the COA. Since chaotic planning enjoys reliability, ergodicity and stochastic feature, the proposed technique presents chaos mapping using Lozi map chaotic sequences which increases its convergence rate. To ensure the robustness of the proposed damping controller, the design process takes into account a wide range of operating conditions and system configurations. The simulation results reveal that the proposed controller has an excellent capability in damping power system low frequency oscillations and enhances greatly the dynamic stability of the power systems. Moreover, the system performance analysis under different operating conditions shows that the phase based controller is superior compare to the magnitude based controller.
Hamdy, M.; Nguyen, A.T. (Anh Tuan); Hensen, J.L.M.
2016-01-01
Integrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently. Many multi-objective optimization algorithms have been developed; however few of them are tested in solving building design
Design and analysis of shutdown mechanisms of PFBR
International Nuclear Information System (INIS)
Vijayashree, R.; Rajan Babu, V.; Puthiyavinayagam, P.; Chellapandi, P.; Chetal, S.C.
2009-01-01
Prototype Fast Breeder Reactor (PFBR) is equipped with two independent, fast acting and diverse shutdown systems. The absorber rod of the first system is called Control and Safety Rod (CSR) and that of the second system is called Diverse Safety Rod (DSR). The respective drive mechanisms are called Control and Safety Rod Drive Mechanism (CSRDM) and Diverse Safety Rod Drive Mechanism (DSRDM). The conceptual features of the Absorber Rods (ARs) and Absorber Rod Drive Mechanisms (ARDMs) are given in the figures. The functions and design specifications of the ARDMs are listed. The theoretical results of the performance of the shutdown systems during scram are presented. The design was always backed up with testing and design validation. The individual subassemblies testing and the design have proceeded side by side, the efforts finally culminated into the manufacturing of 1:1 scale prototype ARDMs and ARs. The prototypes were extensively tested in air, water and sodium to qualify them for reactor application. A companion paper in this conference gives the details of design validation by testing. This paper gives a brief account of the design of ARDMs and ARs. (author)
International Nuclear Information System (INIS)
Chen, Lei; Yan, Changqi; Liao, Yi; Song, Feifei; Jia, Zhen
2017-01-01
Highlights: • The optimization ability of NSGA-II is improved. • The design targets can be obvious optimized through optimization methodology. • Multi-objective optimization is implanted into the design of nuclear power plant. - Abstract: The design of nuclear component can be optimized by seeking out the best combination of article operational and structural parameters. Through multi-objective optimization, the optimized scheme can not only meets the design requirements, but also satisfies the safety regulations. In this work, a hybrid non-dominated sorting genetic algorithm is proposed, and its performance is verified by comparing it with its prototype and immune memory clone constraint multi-objective algorithm through four test-functions; the designs of the steam generator and the primary loop of Qinshan I nuclear power plant are optimized by the proposed algorithm. The results show that the algorithm outperforms the other two through overall evaluation; the reactor inlet temperature is an important parameter which influences the distribution of the Pareto optimal front; through optimization, the weight of the steam generator can be reduced by 16.5%, and the primary flow-rate can be reduced by 17.0%, the weight of the primary loop can be reduced by 11.4%, and the volume can be reduced by 9.8%.
Design Procedure for High-Speed PM Motors Aided by Optimization Algorithms
Directory of Open Access Journals (Sweden)
Francesco Cupertino
2018-02-01
Full Text Available This paper considers the electromagnetic and structural co-design of superficial permanent magnet synchronous machines for high-speed applications, with the aid of a Pareto optimization procedure. The aim of this work is to present a design procedure for the afore-mentioned machines that relies on the combined used of optimization algorithms and finite element analysis. The proposed approach allows easy analysis of the results and a lowering of the computational burden. The proposed design method is presented through a practical example starting from the specifications of an aeronautical actuator. The design procedure is based on static finite element simulations for electromagnetic analysis and on analytical formulas for structural design. The final results are validated through detailed transient finite element analysis to verify both electromagnetic and structural performance. The step-by-step presentation of the proposed design methodology allows the reader to easily adapt it to different specifications. Finally, a comparison between a distributed-winding (24 slots and a concentrated-winding (6 slots machine is presented demonstrating the advantages of the former winding arrangement for high-speed applications.
Directory of Open Access Journals (Sweden)
Zhang Ziran
2018-01-01
Full Text Available In the study, context-creativity of Teresa M. Amabile was used as The foundation to apply it in the bags & luggage design course. Moreover, the sectional creative training education mode of prior heuristic task and postpositional algorithmic task was proposed. 26 junior students in product design were used as the trial objects. The Consensual Technique for Creativity (CAT was considered as the scoring standard of creative performance. In the end, the sectional theoretical framework of effective creative training in product design was finally proposed.
Design and Implementation of DC-DC Converter with Inc-Cond Algorithm
Mustafa Engin Basoğlu; Bekir Çakır
2015-01-01
The most important component affecting the efficiency of photovoltaic power systems are solar panels. In other words, efficiency of these systems are significantly affected due to the being low efficiency of solar panel. Thus, solar panels should be operated under maximum power point conditions through a power converter. In this study, design of boost converter has been carried out with maximum power point tracking (MPPT) algorithm which is incremental conductance (Inc-Co...
On the design of compliant mechanisms using topology optimization
DEFF Research Database (Denmark)
Sigmund, Ole
1997-01-01
This paper presents a method for optimal design of compliant mechanism topologies. The method is based on continuum-type topology optimization techniques and finds the optimal compliant mechanism topology within a given design domain and a given position and direction of input and output forces....... By constraining the allowed displacement at the input port, it is possible to control the maximum stress level in the compliant mechanism. The ability of the design method to find a mechanism with complex output behavior is demonstrated by several examples. Some of the optimal mechanism topologies have been...... manufactured, both in macroscale (hand-size) made in Nylon, and in microscale (
Group leaders optimization algorithm
Daskin, Anmer; Kais, Sabre
2011-03-01
We present a new global optimization algorithm in which the influence of the leaders in social groups is used as an inspiration for the evolutionary technique which is designed into a group architecture. To demonstrate the efficiency of the method, a standard suite of single and multi-dimensional optimization functions along with the energies and the geometric structures of Lennard-Jones clusters are given as well as the application of the algorithm on quantum circuit design problems. We show that as an improvement over previous methods, the algorithm scales as N 2.5 for the Lennard-Jones clusters of N-particles. In addition, an efficient circuit design is shown for a two-qubit Grover search algorithm which is a quantum algorithm providing quadratic speedup over the classical counterpart.
International Nuclear Information System (INIS)
Chen, Wang Chih; Chen Jahau Lewis
2014-01-01
The work proposes a new design tool that integrates design-around concepts with the algorithm for inventive problem solving (Russian acronym: ARIZ). ARIZ includes a complete procedure for analyzing problems and related resource, resolving conflicts and generating solutions. The combination of ARIZ and design-around concepts and understanding identified principles that govern patent infringements can prevent patent infringements whenever designers innovate, greatly reducing the cost and time associated with the product design stage. The presented tool is developed from an engineering perspective rather than a legal perspective, and so can help designers easily to prevent patent infringements and succeed in innovating by designing around. An example is used to demonstrate the proposed method.
Robust design of large-displacement compliant mechanisms
DEFF Research Database (Denmark)
Lazarov, Boyan Stefanov; Schevenels, M.; Sigmund, Ole
2011-01-01
The aim of this article is to introduce a new topology optimisation formulation for optimal robust design of Micro Electro Mechanical Systems. Mesh independence in topology optimisation is most often ensured by using filtering techniques, which result in transition grey regions difficult to inter...... in nearly black and white mechanism designs, robust with respect to uncertainties in the production process, i.e. without any hinges or small details which can create manufacturing difficulties....
Ferentinos, Konstantinos P
2005-09-01
Two neural network (NN) applications in the field of biological engineering are developed, designed and parameterized by an evolutionary method based on the evolutionary process of genetic algorithms. The developed systems are a fault detection NN model and a predictive modeling NN system. An indirect or 'weak specification' representation was used for the encoding of NN topologies and training parameters into genes of the genetic algorithm (GA). Some a priori knowledge of the demands in network topology for specific application cases is required by this approach, so that the infinite search space of the problem is limited to some reasonable degree. Both one-hidden-layer and two-hidden-layer network architectures were explored by the GA. Except for the network architecture, each gene of the GA also encoded the type of activation functions in both hidden and output nodes of the NN and the type of minimization algorithm that was used by the backpropagation algorithm for the training of the NN. Both models achieved satisfactory performance, while the GA system proved to be a powerful tool that can successfully replace the problematic trial-and-error approach that is usually used for these tasks.
3rd IFToMM Symposium on Mechanism Design for Robotics
Ceccarelli, Marco
2015-01-01
This volume contains the Proceedings of the 3rd IFToMM Symposium on Mechanism Design for Robotics, held in Aalborg, Denmark, 2-4 June, 2015. The book contains papers on recent advances in the design of mechanisms and their robotic applications. It treats the following topics: mechanism design, mechanics of robots, parallel manipulators, actuators and their control, linkage and industrial manipulators, innovative mechanisms/robots and their applications, among others. The book can be used by researchers and engineers in the relevant areas of mechanisms, machines and robotics.
Sathiya, P.; Panneerselvam, K.; Soundararajan, R.
2012-09-01
Laser welding input parameters play a very significant role in determining the quality of a weld joint. The joint quality can be defined in terms of properties such as weld bead geometry, mechanical properties and distortion. Therefore, mechanical properties should be controlled to obtain good welded joints. In this study, the weld bead geometry such as depth of penetration (DP), bead width (BW) and tensile strength (TS) of the laser welded butt joints made of AISI 904L super austenitic stainless steel were investigated. Full factorial design was used to carry out the experimental design. Artificial Neural networks (ANN) program was developed in MatLab software to establish the relationships between the laser welding input parameters like beam power, travel speed and focal position and the three responses DP, BW and TS in three different shielding gases (Argon, Helium and Nitrogen). The established models were used for optimizing the process parameters using Genetic Algorithm (GA). Optimum solutions for the three different gases and their respective responses were obtained. Confirmation experiment has also been conducted to validate the optimized parameters obtained from GA.
Mechanical design of a magnetic fusion production reactor
International Nuclear Information System (INIS)
Neef, W.S.; Jassby, D.L.
1986-01-01
The mechanical aspects of a tandem mirror and tokamak concepts for the tritium production mission are compared, and a proposed breeding blanket configuration for each type of reactor is presented in detail, along with a design outline of the complete fusion reaction system. In both cases, the reactor design is developed sufficiently to permit preliminary cost estimates of all components. A qualitative comparison is drawn between both concepts from the view of mechanical design and serviceability, and suggestions are made for technology proof tests on unique mechanical features. Detailed cost breakdowns indicate less than 10% difference in the overall costs of the two reactors
An Algorithm for the Design of an Axial Flow Compressor of a Power ...
African Journals Online (AJOL)
This paper focuses on the development of an algorithm for designing an axial flow compressor for a power generation gas turbine and attempts to bring to the public domain some parameters regarded as propriety data by plant manufacturers. The theory used in this work is based on simple thermodynamics and ...
International Nuclear Information System (INIS)
2010-01-01
The particle beam of the SXR (soft x-ray) beam line in the LCLS (Linac Coherent Light Source) has a high intensity in order to penetrate through samples at the atomic level. However, the intensity is so high that many experiments fail because of severe damage. To correct this issue, attenuators are put into the beam line to reduce this intensity to a level suitable for experimentation. Attenuation is defined as 'the gradual loss in intensity of any flux through a medium' by (1). It is found that Beryllium and Boron Carbide can survive the intensity of the beam. At very thin films, both of these materials work very well as filters for reducing the beam intensity. Using a total of 12 filters, the first 9 being made of Beryllium and the rest made of Boron Carbide, the beam's energy range of photons can be attenuated between 800 eV and 9000 eV. The design of the filters allows attenuation for different beam intensities so that experiments can obtain different intensities from the beam if desired. The step of attenuation varies, but is relative to the thickness of the filter as a power function of 2. A relationship for this is f(n) = x 0 2 n where n is the step of attenuation desired and x 0 is the initial thickness of the material. To allow for this desired variation, a mechanism must be designed within the test chamber. This is visualized using a 3D computer aided design modeling tool known as Solid Edge.
Hou, Zhenlong; Huang, Danian
2017-09-01
In this paper, we make a study on the inversion of probability tomography (IPT) with gravity gradiometry data at first. The space resolution of the results is improved by multi-tensor joint inversion, depth weighting matrix and the other methods. Aiming at solving the problems brought by the big data in the exploration, we present the parallel algorithm and the performance analysis combining Compute Unified Device Architecture (CUDA) with Open Multi-Processing (OpenMP) based on Graphics Processing Unit (GPU) accelerating. In the test of the synthetic model and real data from Vinton Dome, we get the improved results. It is also proved that the improved inversion algorithm is effective and feasible. The performance of parallel algorithm we designed is better than the other ones with CUDA. The maximum speedup could be more than 200. In the performance analysis, multi-GPU speedup and multi-GPU efficiency are applied to analyze the scalability of the multi-GPU programs. The designed parallel algorithm is demonstrated to be able to process larger scale of data and the new analysis method is practical.
International Nuclear Information System (INIS)
Neshat, Elaheh; Saray, Rahim Khoshbakhti
2015-01-01
Highlights: • A new chemical kinetic mechanism for PRFs HCCI combustion is developed. • New mechanism optimization is performed using genetic algorithm and multi-zone model. • Engine-related combustion and performance parameters are predicted accurately. • Engine unburned HC and CO emissions are predicted by the model properly. - Abstract: Development of comprehensive chemical kinetic mechanisms is required for HCCI combustion and emissions prediction to be used in engine development. The main purpose of this study is development of a new chemical kinetic mechanism for primary reference fuels (PRFs) HCCI combustion, which can be applied to combustion models to predict in-cylinder pressure and exhaust CO and UHC emissions, accurately. Hence, a multi-zone model is developed for HCCI engine simulation. Two semi-detailed chemical kinetic mechanisms those are suitable for premixed combustion are used for n-heptane and iso-octane HCCI combustion simulation. The iso-octane mechanism contains 84 species and 484 reactions and the n-heptane mechanism contains 57 species and 296 reactions. A simple interaction between iso-octane and n-heptane is considered in new mechanism. The multi-zone model is validated using experimental data for pure n-heptane and iso-octane. A new mechanism is prepared by combination of these two mechanisms for n-heptane and iso-octane blended fuel, which includes 101 species and 594 reactions. New mechanism optimization is performed using genetic algorithm and multi-zone model. Mechanism contains low temperature heat release region, which decreases with increasing octane number. The results showed that the optimized chemical kinetic mechanism is capable of predicting engine-related combustion and performance parameters. Also after implementing the optimized mechanism, engine unburned HC and CO emissions predicted by the model are in good agreement with the corresponding experimental data
A possibilistic approach to rotorcraft design through a multi-objective evolutionary algorithm
Chae, Han Gil
Most of the engineering design processes in use today in the field may be considered as a series of successive decision making steps. The decision maker uses information at hand, determines the direction of the procedure, and generates information for the next step and/or other decision makers. However, the information is often incomplete, especially in the early stages of the design process of a complex system. As the complexity of the system increases, uncertainties eventually become unmanageable using traditional tools. In such a case, the tools and analysis values need to be "softened" to account for the designer's intuition. One of the methods that deals with issues of intuition and incompleteness is possibility theory. Through the use of possibility theory coupled with fuzzy inference, the uncertainties estimated by the intuition of the designer are quantified for design problems. By involving quantified uncertainties in the tools, the solutions can represent a possible set, instead of a crisp spot, for predefined levels of certainty. From a different point of view, it is a well known fact that engineering design is a multi-objective problem or a set of such problems. The decision maker aims to find satisfactory solutions, sometimes compromising the objectives that conflict with each other. Once the candidates of possible solutions are generated, a satisfactory solution can be found by various decision-making techniques. A number of multi-objective evolutionary algorithms (MOEAs) have been developed, and can be found in the literature, which are capable of generating alternative solutions and evaluating multiple sets of solutions in one single execution of an algorithm. One of the MOEA techniques that has been proven to be very successful for this class of problems is the strength Pareto evolutionary algorithm (SPEA) which falls under the dominance-based category of methods. The Pareto dominance that is used in SPEA, however, is not enough to account for the
Energy Technology Data Exchange (ETDEWEB)
Fluhr, Christian Yves Andre
1977-06-15
This research thesis concerns the field of artificial intelligence. It addresses learning algorithms applied to automatic processing of languages. The author first briefly describes some mechanisms of human intelligence in order to describe how these mechanisms are simulated on a computer. He outlines the specific role of learning in various manifestations of intelligence. Then, based on the Markov's algorithm theory, the author discusses the notion of learning algorithm. Two main types of learning algorithms are then addressed: firstly, an 'algorithm-teacher dialogue' type sanction-based algorithm which aims at learning how to solve grammatical ambiguities in submitted texts; secondly, an algorithm related to a document system which structures semantic data automatically obtained from a set of texts in order to be able to understand by references to any question on the content of these texts.
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
Chemical optimization algorithm for fuzzy controller design
Astudillo, Leslie; Castillo, Oscar
2014-01-01
In this book, a novel optimization method inspired by a paradigm from nature is introduced. The chemical reactions are used as a paradigm to propose an optimization method that simulates these natural processes. The proposed algorithm is described in detail and then a set of typical complex benchmark functions is used to evaluate the performance of the algorithm. Simulation results show that the proposed optimization algorithm can outperform other methods in a set of benchmark functions. This chemical reaction optimization paradigm is also applied to solve the tracking problem for the dynamic model of a unicycle mobile robot by integrating a kinematic and a torque controller based on fuzzy logic theory. Computer simulations are presented confirming that this optimization paradigm is able to outperform other optimization techniques applied to this particular robot application
Wu, Yue; Li, Q.; Hu, Qingjie; Borgart, A.
2017-01-01
Firefly Algorithm (FA, for short) is inspired by the social behavior of fireflies and their phenomenon of bioluminescent communication. Based on the fundamentals of FA, two improved strategies are proposed to conduct size and topology optimization for trusses with discrete design variables. Firstly,
ALE-PSO: An Adaptive Swarm Algorithm to Solve Design Problems of Laminates
Directory of Open Access Journals (Sweden)
Paolo Vannucci
2009-04-01
Full Text Available This paper presents an adaptive PSO algorithm whose numerical parameters can be updated following a scheduled protocol respecting some known criteria of convergence in order to enhance the chances to reach the global optimum of a hard combinatorial optimization problem, such those encountered in global optimization problems of composite laminates. Some examples concerning hard design problems are provided, showing the effectiveness of the approach.
Mechanical Design of Carbon Ion Optics
Haag, Thomas
2005-01-01
Carbon Ion Optics are expected to provide much longer thruster life due to their resistance to sputter erosion. There are a number of different forms of carbon that have been used for fabricating ion thruster optics. The mechanical behavior of carbon is much different than that of most metals, and poses unique design challenges. In order to minimize mission risk, the behavior of carbon must be well understood, and components designed within material limitations. Thermal expansion of the thruster structure must be compatible with thermal expansion of the carbon ion optics. Specially designed interfaces may be needed so that grid gap and aperture alignment are not adversely affected by dissimilar material properties within the thruster. The assembled thruster must be robust and tolerant of launch vibration. The following paper lists some of the characteristics of various carbon materials. Several past ion optics designs are discussed, identifying strengths and weaknesses. Electrostatics and material science are not emphasized so much as the mechanical behavior and integration of grid electrodes into an ion thruster.
SHARPEN-Systematic Hierarchical Algorithms for Rotamers and Proteins on an Extended Network
Loksha, Ilya V.
2009-04-30
Algorithms for discrete optimization of proteins play a central role in recent advances in protein structure prediction and design. We wish to improve the resources available for computational biologists to rapidly prototype such algorithms and to easily scale these algorithms to many processors. To that end, we describe the implementation and use of two new open source resources, citing potential benefits over existing software. We discuss CHOMP, a new object-oriented library for macromolecular optimization, and SHARPEN, a framework for scaling CHOMP scripts to many computers. These tools allow users to develop new algorithms for a variety of applications including protein repacking, protein-protein docking, loop rebuilding, or homology model remediation. Particular care was taken to allow modular energy function design; protein conformations may currently be scored using either the OPLSaa molecular mechanical energy function or an all-atom semiempirical energy function employed by Rosetta. © 2009 Wiley Periodicals, Inc.
Parameterized Algorithms for Survivable Network Design with Uniform Demands
DEFF Research Database (Denmark)
Bang-Jensen, Jørgen; Klinkby Knudsen, Kristine Vitting; Saurabh, Saket
2018-01-01
problem in combinatorial optimization that captures numerous well-studied problems in graph theory and graph algorithms. Consequently, there is a long line of research into exact-polynomial time algorithms as well as approximation algorithms for various restrictions of this problem. An important...... that SNDP is W[1]-hard for both arc and vertex connectivity versions on digraphs. The core of our algorithms is composed of new combinatorial results on connectivity in digraphs and undirected graphs....
A Novel Classification Algorithm Based on Incremental Semi-Supervised Support Vector Machine.
Directory of Open Access Journals (Sweden)
Fei Gao
Full Text Available For current computational intelligence techniques, a major challenge is how to learn new concepts in changing environment. Traditional learning schemes could not adequately address this problem due to a lack of dynamic data selection mechanism. In this paper, inspired by human learning process, a novel classification algorithm based on incremental semi-supervised support vector machine (SVM is proposed. Through the analysis of prediction confidence of samples and data distribution in a changing environment, a "soft-start" approach, a data selection mechanism and a data cleaning mechanism are designed, which complete the construction of our incremental semi-supervised learning system. Noticeably, with the ingenious design procedure of our proposed algorithm, the computation complexity is reduced effectively. In addition, for the possible appearance of some new labeled samples in the learning process, a detailed analysis is also carried out. The results show that our algorithm does not rely on the model of sample distribution, has an extremely low rate of introducing wrong semi-labeled samples and can effectively make use of the unlabeled samples to enrich the knowledge system of classifier and improve the accuracy rate. Moreover, our method also has outstanding generalization performance and the ability to overcome the concept drift in a changing environment.
Multiobjective optimization of building design using genetic algorithm and artificial neural network
Energy Technology Data Exchange (ETDEWEB)
Magnier, L.; Zhou, L.; Haghighat, F. [Concordia Univ., Centre for Building Studies, Montreal, PQ (Canada). Dept. of Building, Civil and Environmental Engineering
2008-07-01
This paper addressed the challenge of designing modern buildings that are energy efficient, affordable, environmentally sound and comfortable for occupants. Building optimization is a time consuming process when so many objectives must be met. In particular, the use of genetic algorithm (GA) for building design has limitations due to the high number of simulations required. This paper presented an efficient approach to overcome the limitations of GA for building design. The approach expanded the GA methodology to multiobjective optimization. The GA integrating neural network (GAINN) approach first uses a simulation-based artificial neural network (ANN) to characterize building behaviour, and then combines it with a GA for optimization. The process was shown to provide fast and reliable optimization. GAINN was further improved by integrating multiobjective evolutionary algorithms (MOEAs). Two new MOEAs named NSGAINN and PLAGUE were designed for the proposed methodology. The purpose of creating a new MOEA was to take advantage of GAINN fast evaluations. This paper presented bench test results and compared them with with NSGA-2. A previous case study using GAINN methodology was re-optimized with the newly developed MOEA. The design to be optimized was a ventilation system of a standard office room in the summer, with 2 occupants and 4 underfloor air distribution diffusers. The objectives included thermal comfort, indoor air quality, and energy conservation for cooling. The control variables were temperature of the air supply, speed of air supply, distance from the diffuser to the occupant, and the distance from the return grill to the contaminant source. The results showed that the newly presented GAINN methodology was better in both convergence and range of choices compared to a weighted sum GA. 13 refs., 2 tabs., 9 figs.
Mechanical design of a power-adjustable spectacle lens frame.
Zapata, Asuncion; Barbero, Sergio
2011-05-01
Power-adjustable spectacle lenses, based on the Alvarez-Lohmann principle, can be used to provide affordable spectacles for subjective refractive errors measurement and its correction. A new mechanical frame has been designed to maximize the advantages of this technology. The design includes a mechanism to match the interpupillary distance with that of the optical centers of the lenses. The frame can be manufactured using low cost plastic injection molding techniques. A prototype has been built to test the functioning of this mechanical design.
Directory of Open Access Journals (Sweden)
Faryal Shamsi
2017-12-01
Full Text Available This Analysis and Design of Algorithm is considered as a compulsory course in the field of Computer Science. It increases the logical and problem solving skills of the students and make their solutions efficient in terms of time and space. These objectives can only be achieved if a student practically implements what he or she has studied throughout the course. But if the contents of this course are merely studied and rarely practiced then the actual goals of the course is not fulfilled. This article will explore the extent of practical implementation of the course of analysis and design of algorithm. Problems faced by the computer science community and major barriers in the field are also enumerated. Finally, some recommendations are made to overcome the obstacles in the practical implementation of analysis and design of algorithms.
Scalable Atomistic Simulation Algorithms for Materials Research
Directory of Open Access Journals (Sweden)
Aiichiro Nakano
2002-01-01
Full Text Available A suite of scalable atomistic simulation programs has been developed for materials research based on space-time multiresolution algorithms. Design and analysis of parallel algorithms are presented for molecular dynamics (MD simulations and quantum-mechanical (QM calculations based on the density functional theory. Performance tests have been carried out on 1,088-processor Cray T3E and 1,280-processor IBM SP3 computers. The linear-scaling algorithms have enabled 6.44-billion-atom MD and 111,000-atom QM calculations on 1,024 SP3 processors with parallel efficiency well over 90%. production-quality programs also feature wavelet-based computational-space decomposition for adaptive load balancing, spacefilling-curve-based adaptive data compression with user-defined error bound for scalable I/O, and octree-based fast visibility culling for immersive and interactive visualization of massive simulation data.
Canadell, Marta; Haro, Àlex
2017-12-01
We present several algorithms for computing normally hyperbolic invariant tori carrying quasi-periodic motion of a fixed frequency in families of dynamical systems. The algorithms are based on a KAM scheme presented in Canadell and Haro (J Nonlinear Sci, 2016. doi: 10.1007/s00332-017-9389-y), to find the parameterization of the torus with prescribed dynamics by detuning parameters of the model. The algorithms use different hyperbolicity and reducibility properties and, in particular, compute also the invariant bundles and Floquet transformations. We implement these methods in several 2-parameter families of dynamical systems, to compute quasi-periodic arcs, that is, the parameters for which 1D normally hyperbolic invariant tori with a given fixed frequency do exist. The implementation lets us to perform the continuations up to the tip of the quasi-periodic arcs, for which the invariant curves break down. Three different mechanisms of breakdown are analyzed, using several observables, leading to several conjectures.
Task-Based Method for Designing Underactuated Mechanisms
Directory of Open Access Journals (Sweden)
Shoichiro Kamada
2012-03-01
Full Text Available In this paper we introduce a task-based method for designing underactuated multi-joint prosthetic hands for specific grasping tasks. The designed robotic hands or prosthetic hands contain fewer independent actuators than joints. We chose a few specific grasping tasks that are frequently repeated in everyday life and analysed joint motions of the hand during the completion of each task and the level of participation of each joint. The information was used for the synthesis of dedicated underactuated mechanisms that can operate in a low dimensional task coordinate space. We propose two methods for reducing the actuators' number. The kinematic parameters of the synthesized mechanism are determined by using a numerical approach. In this study the joint angles of the synthesized hand are considered as linearly dependent on the displacements of the actuators. We introduced a special error index that allowed us to compare the original trajectory and the trajectory performed by the synthesized mechanism, and to select the kinematic parameters of the new kinematic structure as a way to reduce the error. The approach allows the design of simple gripper mechanisms with good accuracy for the preliminary defined tasks.
Directory of Open Access Journals (Sweden)
Jingmin Wang
2016-01-01
Full Text Available Electricity consumption forecast is perceived to be a growing hot topic in such a situation that China’s economy has entered a period of new normal and the demand of electric power has slowed down. Therefore, exploring Chinese electricity consumption influence mechanism and forecasting electricity consumption are crucial to formulate electrical energy plan scientifically and guarantee the sustainable economic and social development. Research has identified medium and long term electricity consumption forecast as a difficult study influenced by various factors. This paper proposed an improved Artificial Bee Colony (ABC algorithm which combined with multivariate linear regression (MLR for exploring the influencing mechanism of various factors on Chinese electricity consumption and forecasting electricity consumption in the future. The results indicated that the improved ABC algorithm in view of the various factors is superior to traditional models just considering unilateralism in accuracy and persuasion. The overall findings cast light on this model which provides a new scientific and effective way to forecast the medium and long term electricity consumption.
Mechanical Designs for Inorganic Stretchable Circuits in Soft Electronics.
Wang, Shuodao; Huang, Yonggang; Rogers, John A
2015-09-01
Mechanical concepts and designs in inorganic circuits for different levels of stretchability are reviewed in this paper, through discussions of the underlying mechanics and material theories, fabrication procedures for the constituent microscale/nanoscale devices, and experimental characterization. All of the designs reported here adopt heterogeneous structures of rigid and brittle inorganic materials on soft and elastic elastomeric substrates, with mechanical design layouts that isolate large deformations to the elastomer, thereby avoiding potentially destructive plastic strains in the brittle materials. The overall stiffnesses of the electronics, their stretchability, and curvilinear shapes can be designed to match the mechanical properties of biological tissues. The result is a class of soft stretchable electronic systems that are compatible with traditional high-performance inorganic semiconductor technologies. These systems afford promising options for applications in portable biomedical and health-monitoring devices. Mechanics theories and modeling play a key role in understanding the underlining physics and optimization of these systems.
An Adaptive Power Efficient Packet Scheduling Algorithm for Wimax Networks
R Murali Prasad; P. Satish Kumar
2010-01-01
Admission control schemes and scheduling algorithms are designed to offer QoS services in 802.16/802.16e networks and a number of studies have investigated these issues. But the channel condition and priority of traffic classes are very rarely considered in the existing scheduling algorithms. Although a number of energy saving mechanisms have been proposed for the IEEE 802.16e, to minimize the power consumption of IEEE 802.16e mobile stations with multiple real-time connections has not yet be...
Directory of Open Access Journals (Sweden)
S. Alireza Mohades Kasaei
2010-04-01
Full Text Available Robocup is an international competition for multi agent research and related subject like: Artificial intelligence, Image processing, machine learning, robot path planning, control, and
obstacle avoidance. In a soccer robot game, the environment is highly competitive and dynamic. In order to work in the dynamically changing environment, the decision-making system of a soccer robot system should have the features of flexibility and real-time adaptation. In this paper we will
focus on the Middle Size Soccer Robot league (MSL and new hierarchical hybrid fuzzy methods for decision making and action selection of a robot in Middle Size Soccer Robot league (MSL are presented. First, the behaviors of an agent are introduced, implemented and classified in two layers,
the Low_Level_Behaviors and the High_Level_Behaviors. In the second layer, a two phase mechanism for decision making is introduced. In phase one, some useful methods are implemented which check the robot’s situation for performing required behaviors. In the next phase, the team strategy, team formation, robot’s role and the robot’s positioning system are introduced. A fuzzy logical approach is employed to recognize the team strategy and further more to tell the player the
best position to move. We believe that a Dynamic role engine is necessary for a successful team. Dynamic role engine and formation control during offensive or defensive play, help us to prevent collision avoidance among own players when attacking the ball and obstacle avoidance of the opponents. At last, we comprised our implemented algorithm in the Robocup 2007 and 2008 and results showed the efficiency of the introduced methodology. The results are satisfactory which has already been successfully implemented in ADRO RoboCup team. This project is still in progress and some new interesting methods are described in the current report.
Energy Technology Data Exchange (ETDEWEB)
Shook, Richard; /Marquette U. /SLAC
2010-08-25
The particle beam of the SXR (soft x-ray) beam line in the LCLS (Linac Coherent Light Source) has a high intensity in order to penetrate through samples at the atomic level. However, the intensity is so high that many experiments fail because of severe damage. To correct this issue, attenuators are put into the beam line to reduce this intensity to a level suitable for experimentation. Attenuation is defined as 'the gradual loss in intensity of any flux through a medium' by [1]. It is found that Beryllium and Boron Carbide can survive the intensity of the beam. At very thin films, both of these materials work very well as filters for reducing the beam intensity. Using a total of 12 filters, the first 9 being made of Beryllium and the rest made of Boron Carbide, the beam's energy range of photons can be attenuated between 800 eV and 9000 eV. The design of the filters allows attenuation for different beam intensities so that experiments can obtain different intensities from the beam if desired. The step of attenuation varies, but is relative to the thickness of the filter as a power function of 2. A relationship for this is f(n) = x{sub 0}2{sup n} where n is the step of attenuation desired and x{sub 0} is the initial thickness of the material. To allow for this desired variation, a mechanism must be designed within the test chamber. This is visualized using a 3D computer aided design modeling tool known as Solid Edge.
New design for a space cryo-mechanism
Durand, Gilles; Amiaux, Jérôme; Augueres, Jean-Louis; Carty, Michael; Barrière, Jean Christophe; Bouzat, Marylène; Duboué, Bruno; Lagage, Pierre Olivier; Lebeuf, Didier; Lepage, Erwan; Lemer, Isabelle; Marlaguey, Nathalie Peydrol; Poupar, Sébastien
2008-07-01
Based on its experience of space application instrument and its development of cryomechanism for astronomical ground based instrument VLT / VISIR, CEA Saclay is proposing a new concept of Space Cryomechanism. This design is based on VLT/VISIR cryo-mechanism design adapted to space requirements taking into account all the specification of space environment (vibrations at launch, cryogenic vacuum, materials, radiations, ...). The original concept of the design is based on the association of the key elements: a dog-clutch with Hirth teeth jaws coupled to a step-by-step space qualified cryo-motor, a bellows that allows for separation of indexing and rotating functions, and enlarged bearings design in "O" arrangement that increase robustness to vibration. The actuator has 360 steady positions that can be reached within les than a second with repeatability of 5 arcsec peak to peak. After a presentation of the details of the concept and of its benefits to robustness to space environment, the paper describes the thoroughly qualification program of the cryo-mechanism with respect to space requirements (cryo-cycling, indexing accuracy, power consumption, heat dissipation, motorisation margins, vibrations). This cryo-mechanism may be built in 3 different sizes for wheels up to 10 kg.
Application of green concept in mechanical design and manufacture
Liu, Xing ping
2017-11-01
With the development of productive forces, the relationship between human and nature is becoming tight increasingly, especially environmental pollution and resource consumption that comes from equipment manufacturing industry mainly. Green development concept is a new concept which can solve the current ecological environment. The philosophical foundation and theoretical basis of green idea are expounded through the study of scientific development and green concept. The difference between the traditional design and the green design is analyzed; the meaning and content of the mechanical design for green concept are discussed. And the evaluation method of green design is discussed too. The significance of green development concept in the mechanical design and manufacturing science is pinpointed clearly. The results show that the implementation of green design under the mechanical design, from the source of pollution control to achieve green manufacturing, is the only way to achieve sustainable development.
A diffusion tensor imaging tractography algorithm based on Navier-Stokes fluid mechanics.
Hageman, Nathan S; Toga, Arthur W; Narr, Katherine L; Shattuck, David W
2009-03-01
We introduce a fluid mechanics based tractography method for estimating the most likely connection paths between points in diffusion tensor imaging (DTI) volumes. We customize the Navier-Stokes equations to include information from the diffusion tensor and simulate an artificial fluid flow through the DTI image volume. We then estimate the most likely connection paths between points in the DTI volume using a metric derived from the fluid velocity vector field. We validate our algorithm using digital DTI phantoms based on a helical shape. Our method segmented the structure of the phantom with less distortion than was produced using implementations of heat-based partial differential equation (PDE) and streamline based methods. In addition, our method was able to successfully segment divergent and crossing fiber geometries, closely following the ideal path through a digital helical phantom in the presence of multiple crossing tracts. To assess the performance of our algorithm on anatomical data, we applied our method to DTI volumes from normal human subjects. Our method produced paths that were consistent with both known anatomy and directionally encoded color images of the DTI dataset.
Optimal Design of Wind-PV-Diesel-Battery System using Genetic Algorithm
Suryoatmojo, Heri; Hiyama, Takashi; Elbaset, Adel A.; Ashari, Mochamad
Application of diesel generators to supply the load demand on isolated islands in Indonesia has widely spread. With increases in oil price and the concerns about global warming, the integration of diesel generators with renewable energy systems have become an attractive energy sources for supplying the load demand. This paper performs an optimal design of integrated system involving Wind-PV-Diesel-Battery system for isolated island with CO2 emission evaluation by using genetic algorithm. The proposed system has been designed for the hybrid power generation in East Nusa Tenggara, Indonesia-latitude 09.30S, longitude 122.0E. From simulation results, the proposed system is able to minimize the total annual cost of the system under study and reduce CO2 emission generated by diesel generators.
HYLIFE-II reactor chamber mechanical design: Update
International Nuclear Information System (INIS)
House, P.A.
1992-01-01
Mechanical design features of the reactor chamber for the HYLIFE-II inertial confinement fusion power plant are presented. A combination of oscillating and steady, molten salt streams (Li 2 BeF 4 ) are used for shielding and blast protection of the chamber walls. The system is designed for a 6 Hz repetition rate. Beam path clearing, between shots, is accomplished with the oscillating flow. The mechanism for generating the oscillating streams is described. A design configuration of the vessel wall allows adequate cooling and provides extra shielding to reduce thermal stresses to tolerable levels. The bottom portion of the reactor chamber is designed to minimize splash back of the high velocity (17 m/s) salt streams and also recover up to half of the dynamic head. Cost estimates for a 1 GW e and 2 GW e reactor chamber are presented
Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design
Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.
2014-01-01
In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057
Stress-constrained topology optimization for compliant mechanism design
DEFF Research Database (Denmark)
de Leon, Daniel M.; Alexandersen, Joe; Jun, Jun S.
2015-01-01
This article presents an application of stress-constrained topology optimization to compliant mechanism design. An output displacement maximization formulation is used, together with the SIMP approach and a projection method to ensure convergence to nearly discrete designs. The maximum stress...... is approximated using a normalized version of the commonly-used p-norm of the effective von Mises stresses. The usual problems associated with topology optimization for compliant mechanism design: one-node and/or intermediate density hinges are alleviated by the stress constraint. However, it is also shown...
Evaluation of Topology-Aware Broadcast Algorithms for Dragonfly Networks
Energy Technology Data Exchange (ETDEWEB)
Dorier, Matthieu; Mubarak, Misbah; Ross, Rob; Li, Jianping Kelvin; Carothers, Christopher D.; Ma, Kwan-Liu
2016-09-12
Two-tiered direct network topologies such as Dragonflies have been proposed for future post-petascale and exascale machines, since they provide a high-radix, low-diameter, fast interconnection network. Such topologies call for redesigning MPI collective communication algorithms in order to attain the best performance. Yet as increasingly more applications share a machine, it is not clear how these topology-aware algorithms will react to interference with concurrent jobs accessing the same network. In this paper, we study three topology-aware broadcast algorithms, including one designed by ourselves. We evaluate their performance through event-driven simulation for small- and large-sized broadcasts (in terms of both data size and number of processes). We study the effect of different routing mechanisms on the topology-aware collective algorithms, as well as their sensitivity to network contention with other jobs. Our results show that while topology-aware algorithms dramatically reduce link utilization, their advantage in terms of latency is more limited.
A Generalized Ant Colony Algorithm for Job一shop Scheduling Problem
Directory of Open Access Journals (Sweden)
ZHANG Hong-Guo
2017-02-01
Full Text Available Aiming at the problem of ant colony algorithm for solving Job一shop scheduling problem. Considering the complexity of the algorithm that uses disjunctive graph to describe the relationship between workpiece processing. To solve the problem of optimal solution，a generalized ant colony algorithm is proposed. Under the premise of considering constrained relationship between equipment and process，the pheromone update mechanism is applied to solve Job-shop scheduling problem，so as to improve the quality of the solution. In order to improve the search efficiency，according to the state transition rules of ant colony algorithm，this paper makes a detailed study on the selection and improvement of the parameters in the algorithm，and designs the pheromone update strategy. Experimental results show that a generalized ant colony algorithm is more feasible and more effective. Compared with other algorithms in the literature，the results prove that the algorithm improves in computing the optimal solution and convergence speed.
Computer-based mechanical design of overhead lines
Rusinaru, D.; Bratu, C.; Dinu, R. C.; Manescu, L. G.
2016-02-01
Beside the performance, the safety level according to the actual standards is a compulsory condition for distribution grids’ operation. Some of the measures leading to improvement of the overhead lines reliability ask for installations’ modernization. The constraints imposed to the new lines components refer to the technical aspects as thermal stress or voltage drop, and look for economic efficiency, too. The mechanical sizing of the overhead lines is after all an optimization problem. More precisely, the task in designing of the overhead line profile is to size poles, cross-arms and stays and locate poles along a line route so that the total costs of the line's structure to be minimized and the technical and safety constraints to be fulfilled.The authors present in this paper an application for the Computer-Based Mechanical Design of the Overhead Lines and the features of the corresponding Visual Basic program, adjusted to the distribution lines. The constraints of the optimization problem are adjusted to the existing weather and loading conditions of Romania. The outputs of the software application for mechanical design of overhead lines are: the list of components chosen for the line: poles, cross-arms, stays; the list of conductor tension and forces for each pole, cross-arm and stay for different weather conditions; the line profile drawings.The main features of the mechanical overhead lines design software are interactivity, local optimization function and high-level user-interface
Haffner, D. P.; McPeters, R. D.; Bhartia, P. K.; Labow, G. J.
2015-12-01
The TOMS V9 total ozone algorithm will be applied to the OMPS Nadir Mapper instrument to supersede the exisiting V8.6 data product in operational processing and re-processing for public release. Becuase the quality of the V8.6 data is already quite high, enchancements in V9 are mainly with information provided by the retrieval and simplifcations to the algorithm. The design of the V9 algorithm has been influenced by improvements both in our knowledge of atmospheric effects, such as those of clouds made possible by studies with OMI, and also limitations in the V8 algorithms applied to both OMI and OMPS. But the namesake instruments of the TOMS algorithm are substantially more limited in their spectral and noise characterisitics, and a requirement of our algorithm is to also apply the algorithm to these discrete band spectrometers which date back to 1978. To achieve continuity for all these instruments, the TOMS V9 algorithm continues to use radiances in discrete bands, but now uses Rodgers optimal estimation to retrieve a coarse profile and provide uncertainties for each retrieval. The algorithm remains capable of achieving high accuracy results with a small number of discrete wavelengths, and in extreme cases, such as unusual profile shapes and high solar zenith angles, the quality of the retrievals is improved. Despite the intended design to use limited wavlenegths, the algorithm can also utilitze additional wavelengths from hyperspectral sensors like OMPS to augment the retreival's error detection and information content; for example SO2 detection and correction of Ring effect on atmospheric radiances. We discuss these and other aspects of the V9 algorithm as it will be applied to OMPS, and will mention potential improvements which aim to take advantage of a synergy with OMPS Limb Profiler and Nadir Mapper to further improve the quality of total ozone from the OMPS instrument.
Directory of Open Access Journals (Sweden)
Yu Wang
2015-01-01
Full Text Available This paper presents a multiobjective mathematical programming model to optimize airline fleet size and structure with consideration of several critical factors severely affecting the fleet planning process. The main purpose of this paper is to reveal how multiairline competitive behaviors impact airline fleet size and structure by enhancing the existing route-based fleet planning model with consideration of the interaction between market share and flight frequency and also by applying the concept of equilibrium optimum to design heuristic algorithm for solving the model. Through case study and comparison, the heuristic algorithm is proved to be effective. By using the algorithm presented in this paper, the fleet operational profit is significantly increased compared with the use of the existing route-based model. Sensitivity analysis suggests that the fleet size and structure are more sensitive to the increase of fare price than to the increase of passenger demand.
International Nuclear Information System (INIS)
Chandrasekharan, Shailesh
2000-01-01
Cluster algorithms have been recently used to eliminate sign problems that plague Monte-Carlo methods in a variety of systems. In particular such algorithms can also be used to solve sign problems associated with the permutation of fermion world lines. This solution leads to the possibility of designing fermion cluster algorithms in certain cases. Using the example of free non-relativistic fermions we discuss the ideas underlying the algorithm
The Optimal Hydraulic Design of Centrifugal Impeller Using Genetic Algorithm with BVF
Directory of Open Access Journals (Sweden)
Xin Zhou
2014-01-01
Full Text Available Derived from idea of combining the advantages of two-dimensional hydraulic design theory, genetic algorithm, and boundary vorticity flux diagnosis, an optimal hydraulic design method of centrifugal pump impeller was developed. Given design parameters, the desired optimal centrifugal impeller can be obtained after several iterations by this method. Another 5 impellers with the same parameters were also designed by using single arc, double arcs, triple arcs, logarithmic spiral, and linear-variable angle spiral as blade profiles to make comparisons. Using Reynolds averaged N-S equations with a RNG k-ε two-equation turbulence model and log-law wall function to solve 3D turbulent flow field in the flow channel between blades of 6 designed impellers by CFD code FLUENT, the investigation on velocity distributions, pressure distributions, boundary vorticity flux distributions on blade surfaces, and hydraulic performance of impellers was presented and the comparisons of impellers by different design methods were demonstrated. The results showed that the hydraulic performance of impeller designed by this method is much better than the other 5 impellers under design operation condition with almost the same head, higher efficiency, and lower rotating torque, which implied less hydraulic loss and energy consumption.
Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che
2014-01-16
To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high
Design principles for precision mechanisms
Soemers, Herman
2011-01-01
The successful design of mechanisms for products, tools and equipment relies on excellent concepts and properly designed details. Both are covered in this book. Many of the examples presented have been realised in practice and properly evaluated, giving the reader/designer a high level of confidence. Every example comes with the considerations underlying the application and the limitations of the particular idea. This book is based on the work started in the 1960s by W. van der Hoek at Philips in Eindhoven, the Netherlands, and subsequently continued by M.P. Koster, culminating in the Dutch-language book “Constructieprincipes” [Design principles for accurate movement and positioning]. The core of their design approach has been preserved, while theory and examples were updated and the English language was adopted to reach a broad audience within the Netherlands as well as abroad. Herman (H.M.J.R.) Soemers is associated with the University of Twente, Enschede, the Netherlands. He also works as a technolog...
International Nuclear Information System (INIS)
Rong Bao; Rui Xiaoting; Tao Ling
2012-01-01
In this paper, a dynamic modeling method and an active vibration control scheme for a smart flexible four-bar linkage mechanism featuring piezoelectric actuators and strain gauge sensors are presented. The dynamics of this smart mechanism is described by the Discrete Time Transfer Matrix Method of Multibody System (MS-DTTMM). Then a nonlinear fuzzy neural network control is employed to suppress the vibration of this smart mechanism. For improving the dynamic performance of the fuzzy neural network, a genetic algorithm based on the MS-DTTMM is designed offline to tune the initial parameters of the fuzzy neural network. The MS-DTTMM avoids the global dynamics equations of the system, which results in the matrices involved are always very small, so the computational efficiency of the dynamic analysis and control system optimization can be greatly improved. Formulations of the method as well as a numerical simulation are given to demonstrate the proposed dynamic method and control scheme.
Effects of visualization on algorithm comprehension
Mulvey, Matthew
Computer science students are expected to learn and apply a variety of core algorithms which are an essential part of the field. Any one of these algorithms by itself is not necessarily extremely complex, but remembering the large variety of algorithms and the differences between them is challenging. To address this challenge, we present a novel algorithm visualization tool designed to enhance students understanding of Dijkstra's algorithm by allowing them to discover the rules of the algorithm for themselves. It is hoped that a deeper understanding of the algorithm will help students correctly select, adapt and apply the appropriate algorithm when presented with a problem to solve, and that what is learned here will be applicable to the design of other visualization tools designed to teach different algorithms. Our visualization tool is currently in the prototype stage, and this thesis will discuss the pedagogical approach that informs its design, as well as the results of some initial usability testing. Finally, to clarify the direction for further development of the tool, four different variations of the prototype were implemented, and the instructional effectiveness of each was assessed by having a small sample participants use the different versions of the prototype and then take a quiz to assess their comprehension of the algorithm.
Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures
Directory of Open Access Journals (Sweden)
Ayang Xiao
2014-01-01
Full Text Available Due to the fact that vastly different variables and constraints are simultaneously considered, truss layout optimization is a typical difficult constrained mixed-integer nonlinear program. Moreover, the computational cost of truss analysis is often quite expensive. In this paper, a novel fitness estimation based particle swarm optimization algorithm with an adaptive penalty function approach (FEPSO-AP is proposed to handle this problem. FEPSO-AP adopts a special fitness estimate strategy to evaluate the similar particles in the current population, with the purpose to reduce the computational cost. Further more, a laconic adaptive penalty function is employed by FEPSO-AP, which can handle multiple constraints effectively by making good use of historical iteration information. Four benchmark examples with fixed topologies and up to 44 design dimensions were studied to verify the generality and efficiency of the proposed algorithm. Numerical results of the present work compared with results of other state-of-the-art hybrid algorithms shown in the literature demonstrate that the convergence rate and the solution quality of FEPSO-AP are essentially competitive.
Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N
2015-08-01
A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed
DESIGN AND OPTIMIZATION OF VALVELESS MICROPUMPS BY USING GENETIC ALGORITHMS APPROACH
Directory of Open Access Journals (Sweden)
AIDA F. M. SHUKUR
2015-10-01
Full Text Available This paper presents a design optimization of valveless micropump using Genetic Algorithms (GA. The micropump is designed with a diaphragm, pumping chamber and diffuser/nozzle element functions as inlet and outlet of micropump with outer dimension of (5×1.75×5 mm3. The main objectives of this research are to determine the optimum pressure to be applied at micropump’s diaphragm and to find the optimum coupling parameters of the micropump to achieve high flow rate with low power consumption. In order to determine the micropump design performance, the total deformation, strain energy density, equivalent stress for diaphragm, velocity and net flow rate of micropump are investigated. An optimal resonant frequency range for the diaphragm of valveless micropump is obtained through the result assessment. With the development of GA-ANSYS model, a maximum total displacement of diaphragm, 5.3635 µm, with 12 kPa actuation pressure and optimum net flowrate of 7.467 mL/min are achieved.
International Nuclear Information System (INIS)
Kobayashi, Yoko; Aiyoshi, Eitaro
2005-01-01
Multistate searching methods are a subfield of distributed artificial intelligence that aims to provide both principles for construction of complex systems involving multiple states and mechanisms for coordination of independent agents' actions. This paper proposes a multistate searching algorithm with reinforcement learning for the automatic core design of a boiling water reactor. The characteristics of this algorithm are that the coupling structure and the coupling operation suitable for the assigned problem are assumed and an optimal solution is obtained by mutual interference in multistate transitions using multiagents. Calculations in an actual plant confirmed that the proposed algorithm increased the convergence ability of the optimization process
Sheng, Lizeng
The dissertation focuses on one of the major research needs in the area of adaptive/intelligent/smart structures, the development and application of finite element analysis and genetic algorithms for optimal design of large-scale adaptive structures. We first review some basic concepts in finite element method and genetic algorithms, along with the research on smart structures. Then we propose a solution methodology for solving a critical problem in the design of a next generation of large-scale adaptive structures---optimal placements of a large number of actuators to control thermal deformations. After briefly reviewing the three most frequently used general approaches to derive a finite element formulation, the dissertation presents techniques associated with general shell finite element analysis using flat triangular laminated composite elements. The element used here has three nodes and eighteen degrees of freedom and is obtained by combining a triangular membrane element and a triangular plate bending element. The element includes the coupling effect between membrane deformation and bending deformation. The membrane element is derived from the linear strain triangular element using Cook's transformation. The discrete Kirchhoff triangular (DKT) element is used as the plate bending element. For completeness, a complete derivation of the DKT is presented. Geometrically nonlinear finite element formulation is derived for the analysis of adaptive structures under the combined thermal and electrical loads. Next, we solve the optimization problems of placing a large number of piezoelectric actuators to control thermal distortions in a large mirror in the presence of four different thermal loads. We then extend this to a multi-objective optimization problem of determining only one set of piezoelectric actuator locations that can be used to control the deformation in the same mirror under the action of any one of the four thermal loads. A series of genetic algorithms
Control Algorithms Along Relative Equilibria of Underactuated Lagrangian Systems on Lie Groups
DEFF Research Database (Denmark)
Nordkvist, Nikolaj; Bullo, F.
2008-01-01
We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...
Control algorithms along relative equilibria of underactuated Lagrangian systems on Lie groups
DEFF Research Database (Denmark)
Nordkvist, Nikolaj; Bullo, Francesco
2007-01-01
We present novel algorithms to control underactuated mechanical systems. For a class of invariant systems on Lie groups, we design iterative small-amplitude control forces to accelerate along, decelerate along, and stabilize relative equilibria. The technical approach is based upon a perturbation...
Hardware-Efficient Design of Real-Time Profile Shape Matching Stereo Vision Algorithm on FPGA
Directory of Open Access Journals (Sweden)
Beau Tippetts
2014-01-01
Full Text Available A variety of platforms, such as micro-unmanned vehicles, are limited in the amount of computational hardware they can support due to weight and power constraints. An efficient stereo vision algorithm implemented on an FPGA would be able to minimize payload and power consumption in microunmanned vehicles, while providing 3D information and still leaving computational resources available for other processing tasks. This work presents a hardware design of the efficient profile shape matching stereo vision algorithm. Hardware resource usage is presented for the targeted micro-UV platform, Helio-copter, that uses the Xilinx Virtex 4 FX60 FPGA. Less than a fifth of the resources on this FGPA were used to produce dense disparity maps for image sizes up to 450 × 375, with the ability to scale up easily by increasing BRAM usage. A comparison is given of accuracy, speed performance, and resource usage of a census transform-based stereo vision FPGA implementation by Jin et al. Results show that the profile shape matching algorithm is an efficient real-time stereo vision algorithm for hardware implementation for resource limited systems such as microunmanned vehicles.
Directory of Open Access Journals (Sweden)
Chengfen Zhang
2015-01-01
Full Text Available Dry-type air-core reactor is now widely applied in electrical power distribution systems, for which the optimization design is a crucial issue. In the optimization design problem of dry-type air-core reactor, the objectives of minimizing the production cost and minimizing the operation cost are both important. In this paper, a multiobjective optimal model is established considering simultaneously the two objectives of minimizing the production cost and minimizing the operation cost. To solve the multi-objective optimization problem, a memetic evolutionary algorithm is proposed, which combines elitist nondominated sorting genetic algorithm version II (NSGA-II with a local search strategy based on the covariance matrix adaptation evolution strategy (CMA-ES. NSGA-II can provide decision maker with flexible choices among the different trade-off solutions, while the local-search strategy, which is applied to nondominated individuals randomly selected from the current population in a given generation and quantity, can accelerate the convergence speed. Furthermore, another modification is that an external archive is set in the proposed algorithm for increasing the evolutionary efficiency. The proposed algorithm is tested on a dry-type air-core reactor made of rectangular cross-section litz-wire. Simulation results show that the proposed algorithm has high efficiency and it converges to a better Pareto front.
Space mapping optimization algorithms for engineering design
DEFF Research Database (Denmark)
Koziel, Slawomir; Bandler, John W.; Madsen, Kaj
2006-01-01
A simple, efficient optimization algorithm based on space mapping (SM) is presented. It utilizes input SM to reduce the misalignment between the coarse and fine models of the optimized object over a region of interest, and output space mapping (OSM) to ensure matching of response and first...... to a benchmark problem. In comparison with SMIS, the models presented are simple and have a small number of parameters that need to be extracted. The new algorithm is applied to the optimization of coupled-line band-pass filter....
Adaptive symbiotic organisms search (SOS algorithm for structural design optimization
Directory of Open Access Journals (Sweden)
Ghanshyam G. Tejani
2016-07-01
Full Text Available The symbiotic organisms search (SOS algorithm is an effective metaheuristic developed in 2014, which mimics the symbiotic relationship among the living beings, such as mutualism, commensalism, and parasitism, to survive in the ecosystem. In this study, three modified versions of the SOS algorithm are proposed by introducing adaptive benefit factors in the basic SOS algorithm to improve its efficiency. The basic SOS algorithm only considers benefit factors, whereas the proposed variants of the SOS algorithm, consider effective combinations of adaptive benefit factors and benefit factors to study their competence to lay down a good balance between exploration and exploitation of the search space. The proposed algorithms are tested to suit its applications to the engineering structures subjected to dynamic excitation, which may lead to undesirable vibrations. Structure optimization problems become more challenging if the shape and size variables are taken into account along with the frequency. To check the feasibility and effectiveness of the proposed algorithms, six different planar and space trusses are subjected to experimental analysis. The results obtained using the proposed methods are compared with those obtained using other optimization methods well established in the literature. The results reveal that the adaptive SOS algorithm is more reliable and efficient than the basic SOS algorithm and other state-of-the-art algorithms.
A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems
Directory of Open Access Journals (Sweden)
Leilei Cao
2016-01-01
Full Text Available A Guiding Evolutionary Algorithm (GEA with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best one instead of a randomly selected individual. The current best individual served as a guide to attract offspring to its region of genotype space. Mutation was added to offspring according to a dynamic mutation probability. To increase the capability of exploitation, a local search mechanism was applied to new individuals according to a dynamic probability of local search. Experimental results show that GEA outperformed the other three typical global optimization algorithms with which it was compared.
Mechanical design of translocating motor proteins.
Hwang, Wonmuk; Lang, Matthew J
2009-01-01
Translocating motors generate force and move along a biofilament track to achieve diverse functions including gene transcription, translation, intracellular cargo transport, protein degradation, and muscle contraction. Advances in single molecule manipulation experiments, structural biology, and computational analysis are making it possible to consider common mechanical design principles of these diverse families of motors. Here, we propose a mechanical parts list that include track, energy conversion machinery, and moving parts. Energy is supplied not just by burning of a fuel molecule, but there are other sources or sinks of free energy, by binding and release of a fuel or products, or similarly between the motor and the track. Dynamic conformational changes of the motor domain can be regarded as controlling the flow of free energy to and from the surrounding heat reservoir. Multiple motor domains are organized in distinct ways to achieve motility under imposed physical constraints. Transcending amino acid sequence and structure, physically and functionally similar mechanical parts may have evolved as nature's design strategy for these molecular engines.
Model-Based Fault Diagnosis Techniques Design Schemes, Algorithms and Tools
Ding, Steven X
2013-01-01
Guaranteeing a high system performance over a wide operating range is an important issue surrounding the design of automatic control systems with successively increasing complexity. As a key technology in the search for a solution, advanced fault detection and identification (FDI) is receiving considerable attention. This book introduces basic model-based FDI schemes, advanced analysis and design algorithms, and mathematical and control-theoretic tools. This second edition of Model-Based Fault Diagnosis Techniques contains: · new material on fault isolation and identification, and fault detection in feedback control loops; · extended and revised treatment of systematic threshold determination for systems with both deterministic unknown inputs and stochastic noises; addition of the continuously-stirred tank heater as a representative process-industrial benchmark; and · enhanced discussion of residual evaluation in stochastic processes. Model-based Fault Diagno...
Li, Dongni; Guo, Rongtao; Zhan, Rongxin; Yin, Yong
2018-06-01
In this article, an innovative artificial bee colony (IABC) algorithm is proposed, which incorporates two mechanisms. On the one hand, to provide the evolutionary process with a higher starting level, genetic programming (GP) is used to generate heuristic rules by exploiting the elements that constitute the problem. On the other hand, to achieve a better balance between exploration and exploitation, a leading mechanism is proposed to attract individuals towards a promising region. To evaluate the performance of IABC in solving practical and complex problems, it is applied to the intercell scheduling problem with limited transportation capacity. It is observed that the GP-generated rules incorporate the elements of the most competing human-designed rules, and they are more effective than the human-designed ones. Regarding the leading mechanism, the strategies of the ageing leader and multiple challengers make the algorithm less likely to be trapped in local optima.
Mechanical design of the Mars Pathfinder mission
Eisen, Howard Jay; Buck, Carl W.; Gillis-Smith, Greg R.; Umland, Jeffrey W.
1997-01-01
The Mars Pathfinder mission and the Sojourner rover is reported on, with emphasis on the various mission steps and the performance of the technologies involved. The mechanical design of mission hardware was critical to the success of the entry sequence and the landing operations. The various mechanisms employed are considered.
Thermostructural and mechanical aspects of the TFTR plasma limiter design
International Nuclear Information System (INIS)
Condolff, R.; Fixler, S.
1977-01-01
This paper presents the preliminary mechanical and thermostructural aspects of the TFTR (TOKAMAK Fusion Test Reactor) plasma limiter design. The evolution of the limiter design is traced through the various stages from conceptual design to the present state. Results of parametric limiter blade studies are presented. Design criteria, requirements, design loads (mechanical and thermal), material considerations, and remote handling problems are described. The design approach used to achieve a satisfactory plasma limiter and blade is discussed
Thermostructural and mechanical aspects of the TFTR plasma limiter design
International Nuclear Information System (INIS)
Condolff, R.; Fixler, S.
1978-01-01
This paper presents the preliminary mechanical and thermostructural aspects of the TFTR (TOKAMAK Fusion Test Reactor) plasma limiter design. The evolution of the limiter design is traced through the various stages from conceptual design to the present state. Results of parametric limiter blade studies are presented. Design criteria, requirements, design loads (mechanical and thermal), material considerations, and remote handling problems are described. The design approach used to achieve a satisfactory plasma limiter and blade is discussed
DESIGNING ALGORITHMS FOR SOLVING PHYSICS PROBLEMS ON THE BASIS OF MIVAR APPROACH
Directory of Open Access Journals (Sweden)
Dmitry Alekseevich Chuvikov
2017-05-01
Full Text Available The paper considers the process of designing algorithms for solving physics problems on the basis of mivar approach. The work also describes general principles of mivar theory. The concepts of parameter, relation and class in mivar space are considered. There are descriptions of properties which every object in Wi!Mi model should have. An experiment in testing capabilities of the Wi!Mi software has been carried out, thus the model has been designed which solves physics problems from year 8 school course in Russia. To conduct the experiment a new version of Wi!Mi 2.1 software has been used. The physics model deals with the following areas: thermal phenomena, electric and electromagnetic phenomena, optical phenomena.
Directory of Open Access Journals (Sweden)
Cheng-Hong Yang
Full Text Available BACKGROUND: Complete mitochondrial (mt genome sequencing is becoming increasingly common for phylogenetic reconstruction and as a model for genome evolution. For long template sequencing, i.e., like the entire mtDNA, it is essential to design primers for Polymerase Chain Reaction (PCR amplicons which are partly overlapping each other. The presented chromosome walking strategy provides the overlapping design to solve the problem for unreliable sequencing data at the 5' end and provides the effective sequencing. However, current algorithms and tools are mostly focused on the primer design for a local region in the genomic sequence. Accordingly, it is still challenging to provide the primer sets for the entire mtDNA. METHODOLOGY/PRINCIPAL FINDINGS: The purpose of this study is to develop an integrated primer design algorithm for entire mt genome in general, and for the common primer sets for closely-related species in particular. We introduce ClustalW to generate the multiple sequence alignment needed to find the conserved sequences in closely-related species. These conserved sequences are suitable for designing the common primers for the entire mtDNA. Using a heuristic algorithm particle swarm optimization (PSO, all the designed primers were computationally validated to fit the common primer design constraints, such as the melting temperature, primer length and GC content, PCR product length, secondary structure, specificity, and terminal limitation. The overlap requirement for PCR amplicons in the entire mtDNA is satisfied by defining the overlapping region with the sliding window technology. Finally, primer sets were designed within the overlapping region. The primer sets for the entire mtDNA sequences were successfully demonstrated in the example of two closely-related fish species. The pseudo code for the primer design algorithm is provided. CONCLUSIONS/SIGNIFICANCE: In conclusion, it can be said that our proposed sliding window-based PSO
Optimal IIR filter design using Gravitational Search Algorithm with Wavelet Mutation
Directory of Open Access Journals (Sweden)
S.K. Saha
2015-01-01
Full Text Available This paper presents a global heuristic search optimization technique, which is a hybridized version of the Gravitational Search Algorithm (GSA and Wavelet Mutation (WM strategy. Thus, the Gravitational Search Algorithm with Wavelet Mutation (GSAWM was adopted for the design of an 8th-order infinite impulse response (IIR filter. GSA is based on the interaction of masses situated in a small isolated world guided by the approximation of Newtonian’s laws of gravity and motion. Each mass is represented by four parameters, namely, position, active, passive and inertia mass. The position of the heaviest mass gives the near optimal solution. For better exploitation in multidimensional search spaces, the WM strategy is applied to randomly selected particles that enhance the capability of GSA for finding better near optimal solutions. An extensive simulation study of low-pass (LP, high-pass (HP, band-pass (BP and band-stop (BS IIR filters unleashes the potential of GSAWM in achieving better cut-off frequency sharpness, smaller pass band and stop band ripples, smaller transition width and higher stop band attenuation with assured stability.
A high precision position sensor design and its signal processing algorithm for a maglev train.
Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen
2012-01-01
High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.
A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train
Directory of Open Access Journals (Sweden)
Wensen Chang
2012-04-01
Full Text Available High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.
Identification and sensitivity analysis of a correlated ground rule system (design arc)
Eastman, Eric; Chidambarrao, Dureseti; Rausch, Werner; Topaloglu, Rasit O.; Shao, Dongbing; Ramachandran, Ravikumar; Angyal, Matthew
2017-04-01
We demonstrate a tool which can function as an interface between VLSI designers and process-technology engineers throughout the Design-Technology Co-optimization (DTCO) process. This tool uses a Monte Carlo algorithm on the output of lithography simulations to model the frequency of fail mechanisms on wafer. Fail mechanisms are defined according to process integration flow: by Boolean operations and measurements between original and derived shapes. Another feature of this design rule optimization methodology is the use of a Markov-Chain-based algorithm to perform a sensitivity analysis, the output of which may be used by process engineers to target key process-induced variabilities for improvement. This tool is used to analyze multiple Middle-Of-Line fail mechanisms in a 10nm inverter design and identify key process assumptions that will most strongly affect the yield of the structures. This tool and the underlying algorithm are also shown to be scalable to arbitrarily complex geometries in three dimensions. Such a characteristic which is becoming more important with the introduction of novel patterning technologies and more complex 3-D on-wafer structures.
Small Sized Drone Fall Recover Mechanism Design
LIU, Tzu-Heng; CHAO, Fang-Lin; LIOU, Jhen-Yuan
2017-12-01
Drones uses four motors to rotate clockwise, counter-clockwise, or change in rotational speed to change its status of motion. The problem of Unmanned Aerial Vehicle turnover causes personal loses and harm local environment. Designs of devices that can let falling drones recover are discussed. The models attempt to change the orientation, so that the drone may be able to improve to the point where it can take off again. The design flow included looking for functional elements, using simplify model to estimate primary functional characteristics, and find the appropriate design parameters. For reducing the complexity, we adopted the simple rotate mechanism with rotating arms to change the fuselage angle and reduce the dependence on the extra-components. A rough model was built to verify structure, and then the concept drawing and prototype were constructed. We made the prototype through the integration of mechanical part and the electronic control circuit. The electronic control module that selected is Arduino-mini pro. Through the Bluetooth modules, user can start the rebound mechanism by the motor control signal. Protections frames are added around each propeller to improve the body rotate problem. Limited by current size of Arduino module, motor and rebound mechanism make the main chassis more massive than the commercial product. However, built-in sensor and circuit miniaturization will improve it in future.
DESIGN QUALITY IN MECHANICAL ENGINEERING APPLICATION
Directory of Open Access Journals (Sweden)
Ayşegül Akdogan Eker
2010-09-01
Full Text Available There is a close relationship between material chose and quality in mechanical engineering application like there is in all the other engineering applications. If this relation is balanced then engineering success increases. Material chose comes to fore in the design process most of the time. The two most important responsibilities of the design engineer in here is to chose suitable material and to know the production processes about design. The chose of material of a design that will fulfill the needs all through its life has great importance. It is needed to limit the material applicants by choosing the most suitable ones among variable material. Choosing materials that were examined before and whose behavior is well known provides the designer to feel confident. However since using highly successful materials would increase the competitive power of the designs; designers should follow the developments in materials and know the features of new materials. The description of these features can be interpreted within quality. Quality from the point of engineer is the total fulfillment of expectations.Engineer today are faced with very important problems such as fast technological innovations, a dynamic socio-economical environment, global rivalry. One of the life buoys they stick while trying to solve these problems is total method of quality control. Total Quality model which can provide higher competitive power compared to classical management model brings success only when applied with its whole components. "Approach toward prevention" and "measurement and statistics" have an important place among these elements. The first step of the approach toward prevention composes of design quality and Quality Function Deployment (QFD, or in other words The House of Quality method that will provide this. In this paper; considering the quality function deployment, how the chose of material are done in mechanical engineering applications will be explained.
Mechanical flexible joint design document
Daily, Vic
1993-01-01
The purpose of this report is to document the status of the Mechanical Flexible Joint (MFJ) Design Subtask with the intent of halting work on the design. Recommendations for future work is included in the case that the task is to be resumed. The MFJ is designed to eliminate two failure points from the current flex joint configuration, the inner 'tripod configuration' and the outer containment jacket. The MFJ will also be designed to flex 13.5 degrees and have three degrees of freedom. By having three degrees of freedom, the MFJ will allow the Low Pressure Fuel Duct to twist and remove the necessity to angulate the full 11 degrees currently required. The current flex joints are very labor intensive and very costly and a simple alternative is being sought. The MFJ is designed with a greater angular displacement, with three degrees of freedom, to reside in the same overall envelope, to meet weight constraints of the current bellows, to be compatible with cryogenic fuel and oxidizers, and also to be man-rated.
Pole placement algorithm for control of civil structures subjected to earthquake excitation
Directory of Open Access Journals (Sweden)
Nikos Pnevmatikos
2017-04-01
Full Text Available In this paper the control algorithm for controlled civil structures subjected to earthquake excitation is thoroughly investigated. The objective of this work is the control of structures by means of the pole placement algorithm, in order to improve their response against earthquake actions. Successful application of the algorithm requires judicious placement of the closed-loop eigenvalues from the part of the designer. The pole placement algorithm was widely applied to control mechanical systems. In this paper, a modification in the mathematical background of the algorithm in order to be suitable for civil fixed structures is primarily presented. The proposed approach is demonstrated by numerical simulations for the control of both single and multi-degree of freedom systems subjected to seismic actions. Numerical results have shown that the control algorithm is efficient in reducing the response of building structures, with small amount of required control forces.
Asaithambi, Sasikumar; Rajappa, Muthaiah
2018-05-01
In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.
MEMS resonant load cells for micro-mechanical test frames: feasibility study and optimal design
Torrents, A.; Azgin, K.; Godfrey, S. W.; Topalli, E. S.; Akin, T.; Valdevit, L.
2010-12-01
This paper presents the design, optimization and manufacturing of a novel micro-fabricated load cell based on a double-ended tuning fork. The device geometry and operating voltages are optimized for maximum force resolution and range, subject to a number of manufacturing and electromechanical constraints. All optimizations are enabled by analytical modeling (verified by selected finite elements analyses) coupled with an efficient C++ code based on the particle swarm optimization algorithm. This assessment indicates that force resolutions of ~0.5-10 nN are feasible in vacuum (~1-50 mTorr), with force ranges as large as 1 N. Importantly, the optimal design for vacuum operation is independent of the desired range, ensuring versatility. Experimental verifications on a sub-optimal device fabricated using silicon-on-glass technology demonstrate a resolution of ~23 nN at a vacuum level of ~50 mTorr. The device demonstrated in this article will be integrated in a hybrid micro-mechanical test frame for unprecedented combinations of force resolution and range, displacement resolution and range, optical (or SEM) access to the sample, versatility and cost.
Directory of Open Access Journals (Sweden)
Taek Seo Jung
2006-03-01
Full Text Available This paper presents an Image Motion Compensation (IMC algorithm for the Korea's Communication, Ocean, and Meteorological Satellite (COMS-1. An IMC algorithm is a priority component of image registration in Image Navigation and Registration (INR system to locate and register radiometric image data. Due to various perturbations, a satellite has orbit and attitude errors with respect to a reference motion. These errors cause depointing of the imager aiming direction, and in consequence cause image distortions. To correct the depointing of the imager aiming direction, a compensation algorithm is designed by adapting different equations from those used for the GOES satellites. The capability of the algorithm is compared with that of existing algorithm applied to the GOES's INR system. The algorithm developed in this paper improves pointing accuracy by 40%, and efficiently compensates the depointings of the imager aiming direction.
Conceptual design based on scale laws and algorithms for sub-critical transmutation reactors
Energy Technology Data Exchange (ETDEWEB)
Lee, Kwang Gu; Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)
1998-12-31
In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making for both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors. 6 refs., 5 figs., 1 tab. (Author)
Conceptual design based on scale laws and algorithms for sub-critical transmutation reactors
Energy Technology Data Exchange (ETDEWEB)
Lee, Kwang Gu; Chang, Soon Heung [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)
1997-12-31
In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making for both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors. 6 refs., 5 figs., 1 tab. (Author)
Mechanical and thermal design of hybrid blankets
International Nuclear Information System (INIS)
Schultz, K.R.
1978-01-01
The thermal and mechanical aspects of hybrid reactor blanket design considerations are discussed. This paper is intended as a companion to that of J. D. Lee of Lawrence Livermore Laboratory on the nuclear aspects of hybrid reactor blanket design. The major design characteristics of hybrid reactor blankets are discussed with emphasis on the areas of difference between hybrid reactors and standard fusion or fission reactors. Specific examples are used to illustrate the design tradeoffs and choices that must be made in hybrid reactor design. These examples are drawn from the work on the Mirror Hybrid Reactor
Directory of Open Access Journals (Sweden)
J. M. Jeevani W. Jayasinghe
2015-01-01
Full Text Available Genetic algorithm (GA has been a popular optimization technique used for performance improvement of microstrip patch antennas (MPAs. When using GA, the patch geometry is optimized by dividing the patch area into small rectangular cells. This has an inherent problem of adjacent cells being connected to each other with infinitesimal connections, which may not be achievable in practice due to fabrication tolerances in chemical etching. As a solution, this paper presents a novel method of dividing the patch area into cells with nonuniform overlaps. The optimized design, which is obtained by using fixed overlap sizes, shows a quad-band performance covering GSM1800, GSM1900, LTE2300, and Bluetooth bands. In contrast, use of nonuniform overlap sizes leads to obtaining a pentaband design covering GSM1800, GSM1900, UMTS, LTE2300, and Bluetooth bandswith fractional bands with of 38% due to the extra design flexibility.
AHTR Mechanical, Structural, And Neutronic Preconceptual Design
Energy Technology Data Exchange (ETDEWEB)
Varma, Venugopal Koikal [ORNL; Holcomb, David Eugene [ORNL; Peretz, Fred J [ORNL; Bradley, Eric Craig [ORNL; Ilas, Dan [ORNL; Qualls, A L [ORNL; Zaharia, Nathaniel M [ORNL
2012-10-01
This report provides an overview of the mechanical, structural, and neutronic aspects of the Advanced High Temperature Reactor (AHTR) design concept. The AHTR is a design concept for a large output Fluoride salt cooled High-temperature Reactor (FHR) that is being developed to enable evaluation of the technology hurdles remaining to be overcome prior to FHRs becoming a commercial reactor class. This report documents the incremental AHTR design maturation performed over the past year and is focused on advancing the design concept to a level of a functional, self-consistent system. The AHTR employs plate type coated particle fuel assemblies with rapid, off-line refueling. Neutronic analysis of the core has confirmed the viability of a 6-month 2-batch cycle with 9 weight-percent enriched uranium fuel. Refueling is intended to be performed automatically under visual guidance using dedicated robotic manipulators. The present design intent is for used fuel to be stored inside of containment for at least 6 months and then transferred to local dry wells for intermediate term, on-site storage. The mechanical and structural concept development effort has included an emphasis on transportation and constructability to minimize construction costs and schedule. The design intent is that all components be factory fabricated into rail transportable modules that are assembled into subsystems at an on-site workshop prior to being lifted into position using a heavy-lift crane in an open-top style construction. While detailed accident identification and response sequence analysis has yet to be performed, the design concept incorporates multiple levels of radioactive material containment including fully passive responses to all identified design basis or non-very-low frequency beyond design basis accidents. Key building design elements include: 1) below grade siting to minimize vulnerability to aircraft impact, 2) multiple natural circulation decay heat rejection chimneys, 3) seismic
Bone biopsy needles. Mechanical properties, needle design and specimen quality
International Nuclear Information System (INIS)
Keulers, Annika; Penzkofer, T.; Cunha-Cruz, V.C.; Bruners, P.; Helmholtz Inst. fuer biomedizinische Technik, Aachen; Braunschweig, T.; Schmitz-Rode, T.; Mahnken, A.; Helmholtz Inst. fuer biomedizinische Technik, Aachen
2011-01-01
To quantitatively analyze differences in mechanical properties, needle design including signs of wear, subjective handling and specimen quality of bone biopsy needles. Materials and Methods: In this study 19 different bone biopsy systems (total 38; 2 /type) were examined. With each biopsy needle five consecutive samples were obtained from vertebral bodies of swine. During puncture a force-torques sensor measured the mechanical properties and subjective handling was assessed. Before and after each biopsy the needles were investigated using a profile projector and signs of wear were recorded. Afterwards, a pathologist semi-quantitatively examined the specimen regarding sample quality. The overall evaluation considered mechanical properties, needle wear, subjective handling and sample quality. Differences were assessed for statistical significance using ANOVA and t-test. Results: Needle diameter (p = 0.003) as well as needle design (p = 0.008) affect the mechanical properties significantly. Franseen design is significantly superior to other needle designs. Besides, length reduction recorded by the profile projector, as a quality criterion showed notable distinctions in between the needle designs. Conclusion: Bone biopsy needles vary significantly in performance. Needle design has an important influence on mechanical properties, handling and specimen quality. Detailed knowledge of those parameters would improve selecting the appropriate bone biopsy needle. (orig.)
Variable threshold algorithm for division of labor analyzed as a dynamical system.
Castillo-Cagigal, Manuel; Matallanas, Eduardo; Navarro, Iñaki; Caamaño-Martín, Estefanía; Monasterio-Huelin, Félix; Gutiérrez, Álvaro
2014-12-01
Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.
Optimization Design by Genetic Algorithm Controller for Trajectory Control of a 3-RRR Parallel Robot
Directory of Open Access Journals (Sweden)
Lianchao Sheng
2018-01-01
Full Text Available In order to improve the control precision and robustness of the existing proportion integration differentiation (PID controller of a 3-Revolute–Revolute–Revolute (3-RRR parallel robot, a variable PID parameter controller optimized by a genetic algorithm controller is proposed in this paper. Firstly, the inverse kinematics model of the 3-RRR parallel robot was established according to the vector method, and the motor conversion matrix was deduced. Then, the error square integral was chosen as the fitness function, and the genetic algorithm controller was designed. Finally, the control precision of the new controller was verified through the simulation model of the 3-RRR planar parallel robot—built in SimMechanics—and the robustness of the new controller was verified by adding interference. The results show that compared with the traditional PID controller, the new controller designed in this paper has better control precision and robustness, which provides the basis for practical application.
Light water reactors fuel assembly mechanical design and evaluation
International Nuclear Information System (INIS)
Anon.
1981-01-01
This standard establishes a procedure for performing an evaluation of the mechanical design of fuel assemblies for light water-cooled commercial power reactors. It does not address the various aspects of neutronic or thermalhydraulic performance except where these factors impose loads or constraints on the mechanical design of the fuel assemblies. This standard also includes a set of specific requirements for design, various potential performance problems and criteria aimed specifically at averting them. This standard replaces ANSI/ANS-57.5-1978
Designing machines for lattice physics and algorithm investigation
International Nuclear Information System (INIS)
Fischler, M.; Atac, R.; Cook, A.
1989-10-01
Special-purpose computers are appropriate tools for the study of lattice gauge theory. While these machines deliver considerable processing power, it is also important to be able to program complex physics ideas and investigate algorithms on them. We examine features that facilitate coding of physics problems, and flexibility in algorithms. Appropriate balances among power, memory, communications and I/O capabilities are presented. 10 refs
Blahut-Arimoto algorithm and code design for action-dependent source coding problems
DEFF Research Database (Denmark)
Trillingsgaard, Kasper Fløe; Simeone, Osvaldo; Popovski, Petar
2013-01-01
The source coding problem with action-dependent side information at the decoder has recently been introduced to model data acquisition in resource-constrained systems. In this paper, an efficient Blahut-Arimoto-type algorithm for the numerical computation of the rate-distortion-cost function...... for this problem is proposed. Moreover, a simplified two-stage code structure based on multiplexing is put forth, whereby the first stage encodes the actions and the second stage is composed of an array of classical Wyner-Ziv codes, one for each action. Leveraging this structure, specific coding/decoding...... strategies are designed based on LDGM codes and message passing. Through numerical examples, the proposed code design is shown to achieve performance close to the rate-distortion-cost function....
Energy Technology Data Exchange (ETDEWEB)
Blodgett, Douglas [DNV KEMA Renewables, Inc., San Ramon, CA (United States); Behnke, Michael [DNV KEMA Renewables, Inc., San Ramon, CA (United States); Erdman, William [DNV KEMA Renewables, Inc., San Ramon, CA (United States)
2016-08-01
The National Renewable Energy Laboratory (NREL) and NREL Next-Generation Drivetrain Partners are developing a next-generation drivetrain (NGD) design as part of a Funding Opportunity Announcement award from the U.S. Department of Energy. The proposed NGD includes comprehensive innovations to the gearbox, generator, and power converter that increase the gearbox reliability and drivetrain capacity, while lowering deployment and operation and maintenance costs. A key task within this development effort is the power converter fault control algorithm design and associated computer simulations using an integrated electromechanical model of the drivetrain. The results of this task will be used in generating the embedded control software to be utilized in the power converter during testing of the NGD in the National Wind Technology Center 2.5-MW dynamometer. A list of issues to be addressed with these algorithms was developed by review of the grid interconnection requirements of various North American transmission system operators, and those requirements that presented the greatest impact to the wind turbine drivetrain design were then selected for mitigation via power converter control algorithms.
Design methodology for wing trailing edge device mechanisms
Martins Pires, Rui Miguel
2007-01-01
Over the last few decades the design of high lift devices has become a very important part of the total aircraft design process. Reviews of the design process are performed on a regular basis, with the intent to improve and optimize the design process. This thesis describes a new and innovative methodology for the design and evaluation of mechanisms for Trailing Edge High-Lift devices. The initial research reviewed existing High-Lift device design methodologies and current f...
International Nuclear Information System (INIS)
Sacco, Wagner F.; Oliveira, Cassiano R.E. de
2005-01-01
A new metaheuristic called 'Gravitational Attraction Algorithm' (GAA) is introduced in this article. It is an analogy with the gravitational force field, where a body attracts another proportionally to both masses and inversely to their distances. The GAA is a populational algorithm where, first of all, the solutions are clustered using the Fuzzy Clustering Means (FCM) algorithm. Following that, the gravitational forces of the individuals in relation to each cluster are evaluated and this individual or solution is displaced to the cluster with the greatest attractive force. Once it is inside this cluster, the solution receives small stochastic variations, performing a local exploration. Then the solutions are crossed over and the process starts all over again. The parameters required by the GAA are the 'diversity factor', which is used to create a random diversity in a fashion similar to genetic algorithm's mutation, and the number of clusters for the FCM. GAA is applied to the reactor core design optimization problem which consists in adjusting several reactor cell parameters in order to minimize the average peak-factor in a 3-enrichment-zone reactor, considering operational restrictions. This problem was previously attacked using the canonical genetic algorithm (GA) and a Niching Genetic Algorithm (NGA). The new metaheuristic is then compared to those two algorithms. The three algorithms are submitted to the same computational effort and GAA reaches the best results, showing its potential for other applications in the nuclear engineering field as, for instance, the nuclear core reload optimization problem. (author)
Direct design of an energy landscape with bistable DNA origami mechanisms.
Zhou, Lifeng; Marras, Alexander E; Su, Hai-Jun; Castro, Carlos E
2015-03-11
Structural DNA nanotechnology provides a feasible technique for the design and fabrication of complex geometries even exhibiting controllable dynamic behavior. Recently we have demonstrated the possibility of implementing macroscopic engineering design approaches to construct DNA origami mechanisms (DOM) with programmable motion and tunable flexibility. Here, we implement the design of compliant DNA origami mechanisms to extend from prescribing motion to prescribing an energy landscape. Compliant mechanisms facilitate motion via deformation of components with tunable stiffness resulting in well-defined mechanical energy stored in the structure. We design, fabricate, and characterize a DNA origami nanostructure with an energy landscape defined by two stable states (local energy minima) separated by a designed energy barrier. This nanostructure is a four-bar bistable mechanism with two undeformed states. Traversing between those states requires deformation, and hence mechanical energy storage, in a compliant arm of the linkage. The energy barrier for switching between two states was obtained from the conformational distribution based on a Boltzmann probability function and closely follows a predictive mechanical model. Furthermore, we demonstrated the ability to actuate the mechanism into one stable state via additional DNA inputs and then release the actuation via DNA strand displacement. This controllable multistate system establishes a foundation for direct design of energy landscapes that regulate conformational dynamics similar to biomolecular complexes.
Modification of Brueschweiler quantum searching algorithm and realization by NMR experiment
International Nuclear Information System (INIS)
Yang Xiaodong; Wei Daxiu; Luo Jun; Miao Xijia
2002-01-01
In recent years, quantum computing research has made big progress, which exploit quantum mechanical laws, such as interference, superposition and parallelism, to perform computing tasks. The most inducing thing is that the quantum computing can provide large rise to the speedup in quantum algorithm. Quantum computing can solve some problems, which are impossible or difficult for the classical computing. The problem of searching for a specific item in an unsorted database can be solved with certain quantum algorithm, for example, Grover quantum algorithm and Brueschweiler quantum algorithm. The former gives a quadratic speedup, and the latter gives an exponential speedup comparing with the corresponding classical algorithm. In Brueschweiler quantum searching algorithm, the data qubit and the read-out qubit (the ancilla qubit) are different qubits. The authors have studied Brueschweiler algorithm and proposed a modified version, in which no ancilla qubit is needed to reach exponential speedup in the searching, the data and the read-out qubit are the same qubits. The modified Brueschweiler algorithm can be easier to design and realize. The authors also demonstrate the modified Brueschweiler algorithm in a 3-qubit molecular system by Nuclear Magnetic Resonance (NMR) experiment
The Bilevel Design Problem for Communication Networks on Trains: Model, Algorithm, and Verification
Directory of Open Access Journals (Sweden)
Yin Tian
2014-01-01
Full Text Available This paper proposes a novel method to solve the problem of train communication network design. Firstly, we put forward a general description of such problem. Then, taking advantage of the bilevel programming theory, we created the cost-reliability-delay model (CRD model that consisted of two parts: the physical topology part aimed at obtaining the networks with the maximum reliability under constrained cost, while the logical topology part focused on the communication paths yielding minimum delay based on the physical topology delivered from upper level. We also suggested a method to solve the CRD model, which combined the genetic algorithm and the Floyd-Warshall algorithm. Finally, we used a practical example to verify the accuracy and the effectiveness of the CRD model and further applied the novel method on a train with six carriages.
The design of disengaging mechanism of radix pseudostellariae and soil
Xiao, Shungen; Song, Mengmeng; Chen, Chanwei
2017-12-01
With the continuous development of the scale of the cultivation of the radix pseudostellariae, the traditional separation mode cannot adapt to the mass production of the crown prince, and the existing manual separation mode is of great labor intensity and low degree of mechanization. Therefore, it is necessary to design a disengaging mechanism of radix pseudostellariae and soil on the basis of the design principle of modern agricultural machinery. According to the physical characteristics and growing environment of radix pseudostellariae, a drum-type separating component is presented, and the drum screen separating mechanism and vibration mechanism of the disengaging mechanism are designed. In this paper, the movement rule and time of the mixture of radix pseudostellariae and soil are determined in the drum screen. Rotation speed of the drum screen is calculated, and the operation rules of the eccentric wheel in the vibration mechanism are summarized.
Variants of Evolutionary Algorithms for Real-World Applications
Weise, Thomas; Michalewicz, Zbigniew
2012-01-01
Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book “Variants of Evolutionary Algorithms for Real-World Applications” aims to promote the practitioner’s view on EAs by providing a comprehensive discussion of how EAs can be adapted to the requirements of various applications in the real-world domains. It comprises 14 chapters, including an introductory chapter re-visiting the fundamental question of what an EA is and other chapters addressing a range of real-world problems such as production process planning, inventory system and supply chain network optimisation, task-based jobs assignment, planning for CNC-based work piece construction, mechanical/ship design tasks that involve runtime-intense simulations, data mining for the predictio...
Design considerations for mechanical face seals
Ludwig, L. P.; Greiner, H. F.
1980-01-01
Two companion reports deal with design considerations for improving performance of mechanical face seals, one of family of devices used in general area of fluid sealing of rotating shafts. One report deals with basic seal configuration and other with lubrication of seal.
Energy Technology Data Exchange (ETDEWEB)
Beghi, Alessandro [Dipartimento di Ingegneria dell' Informazione, Universita di Padova, via Gradenigo 6/B, I-35131 Padova (Italy); Cecchinato, Luca [Dipartimento di Fisica Tecnica, Universita di Padova, via Venezia 1, I-35131 Padova (Italy)
2009-11-15
In this paper some results of a research project aimed at deriving high-performance, adaptive control algorithms for electronic expansion valves (EEVs) to be used in finned-coiled, dry-expansion evaporators for refrigeration systems are reported. With the aim of developing a software environment that can be used for controller design, rapid prototyping, optimization of data collection and test design, virtual prototyping approach to design was adopted. The development of a distributed dynamic simulation model of the evaporator coupled with an electronic expansion valve, and its use for deriving autotuning PID control algorithms is described. Experimental results confirm the effectiveness of this kind of approach. (author)
Denni Algorithm An Enhanced Of SMS (Scan, Move and Sort) Algorithm
Aprilsyah Lubis, Denni; Salim Sitompul, Opim; Marwan; Tulus; Andri Budiman, M.
2017-12-01
Sorting has been a profound area for the algorithmic researchers, and many resources are invested to suggest a more working sorting algorithm. For this purpose many existing sorting algorithms were observed in terms of the efficiency of the algorithmic complexity. Efficient sorting is important to optimize the use of other algorithms that require sorted lists to work correctly. Sorting has been considered as a fundamental problem in the study of algorithms that due to many reasons namely, the necessary to sort information is inherent in many applications, algorithms often use sorting as a key subroutine, in algorithm design there are many essential techniques represented in the body of sorting algorithms, and many engineering issues come to the fore when implementing sorting algorithms., Many algorithms are very well known for sorting the unordered lists, and one of the well-known algorithms that make the process of sorting to be more economical and efficient is SMS (Scan, Move and Sort) algorithm, an enhancement of Quicksort invented Rami Mansi in 2010. This paper presents a new sorting algorithm called Denni-algorithm. The Denni algorithm is considered as an enhancement on the SMS algorithm in average, and worst cases. The Denni algorithm is compared with the SMS algorithm and the results were promising.
Algorithmic Principles of Mathematical Programming
Faigle, Ulrich; Kern, Walter; Still, Georg
2002-01-01
Algorithmic Principles of Mathematical Programming investigates the mathematical structures and principles underlying the design of efficient algorithms for optimization problems. Recent advances in algorithmic theory have shown that the traditionally separate areas of discrete optimization, linear
PinaColada: peptide-inhibitor ant colony ad-hoc design algorithm.
Zaidman, Daniel; Wolfson, Haim J
2016-08-01
Design of protein-protein interaction (PPI) inhibitors is a major challenge in Structural Bioinformatics. Peptides, especially short ones (5-15 amino acid long), are natural candidates for inhibition of protein-protein complexes due to several attractive features such as high structural compatibility with the protein binding site (mimicking the surface of one of the proteins), small size and the ability to form strong hotspot binding connections with the protein surface. Efficient rational peptide design is still a major challenge in computer aided drug design, due to the huge space of possible sequences, which is exponential in the length of the peptide, and the high flexibility of peptide conformations. In this article we present PinaColada, a novel computational method for the design of peptide inhibitors for protein-protein interactions. We employ a version of the ant colony optimization heuristic, which is used to explore the exponential space ([Formula: see text]) of length n peptide sequences, in combination with our fast robotics motivated PepCrawler algorithm, which explores the conformational space for each candidate sequence. PinaColada is being run in parallel, on a DELL PowerEdge 2.8 GHZ computer with 20 cores and 256 GB memory, and takes up to 24 h to design a peptide of 5-15 amino acids length. An online server available at: http://bioinfo3d.cs.tau.ac.il/PinaColada/. danielza@post.tau.ac.il; wolfson@tau.ac.il. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Jacomy, Mathieu; Venturini, Tommaso; Heymann, Sebastien; Bastian, Mathieu
2014-01-01
Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics...). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users' typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.
International Nuclear Information System (INIS)
Piepel, Gregory F.; Cooley, Scott K.; Jones, Bradley
2005-01-01
This paper describes the solution to a unique and challenging mixture experiment design problem involving: (1) 19 and 21 components for two different parts of the design, (2) many single-component and multi-component constraints, (3) augmentation of existing data, (4) a layered design developed in stages, and (5) a no-candidate-point optimal design approach. The problem involved studying the liquidus temperature of spinel crystals as a function of nuclear waste glass composition. The statistical objective was to develop an experimental design by augmenting existing glasses with new nonradioactive and radioactive glasses chosen to cover the designated nonradioactive and radioactive experimental regions. The existing 144 glasses were expressed as 19-component nonradioactive compositions and then augmented with 40 new nonradioactive glasses. These included 8 glasses on the outer layer of the region, 27 glasses on an inner layer, 2 replicate glasses at the centroid, and one replicate each of three existing glasses. Then, the 144 + 40 = 184 glasses were expressed as 21-component radioactive compositions, and augmented with 5 radioactive glasses. A D-optimal design algorithm was used to select the new outer layer, inner layer, and radioactive glasses. Several statistical software packages can generate D-optimal experimental designs, but nearly all of them require a set of candidate points (e.g., vertices) from which to select design points. The large number of components (19 or 21) and many constraints made it impossible to generate the huge number of vertices and other typical candidate points. JMP was used to select design points without candidate points. JMP uses a coordinate-exchange algorithm modified for mixture experiments, which is discussed and illustrated in the paper
An improved genetic algorithm for designing optimal temporal patterns of neural stimulation
Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.
2017-12-01
Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.
A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules.
Nguyen, Su; Mei, Yi; Xue, Bing; Zhang, Mengjie
2018-06-04
Designing effective dispatching rules for production systems is a difficult and timeconsuming task if it is done manually. In the last decade, the growth of computing power, advanced machine learning, and optimisation techniques has made the automated design of dispatching rules possible and automatically discovered rules are competitive or outperform existing rules developed by researchers. Genetic programming is one of the most popular approaches to discovering dispatching rules in the literature, especially for complex production systems. However, the large heuristic search space may restrict genetic programming from finding near optimal dispatching rules. This paper develops a new hybrid genetic programming algorithm for dynamic job shop scheduling based on a new representation, a new local search heuristic, and efficient fitness evaluators. Experiments show that the new method is effective regarding the quality of evolved rules. Moreover, evolved rules are also significantly smaller and contain more relevant attributes.
Mechanism Design for Incentivizing Social Media Contributions
Singh, Vivek K.; Jain, Ramesh; Kankanhalli, Mohan
Despite recent advancements in user-driven social media platforms, tools for studying user behavior patterns and motivations remain primitive. We highlight the voluntary nature of user contributions and that users can choose when (and when not) to contribute to the common media pool. A Game theoretic framework is proposed to study the dynamics of social media networks where contribution costs are individual but gains are common. We model users as rational selfish agents, and consider domain attributes like voluntary participation, virtual reward structure, network effect, and public-sharing to model the dynamics of this interaction. The created model describes the most appropriate contribution strategy from each user's perspective and also highlights issues like 'free-rider' problem and individual rationality leading to irrational (i.e. sub-optimal) group behavior. We also consider the perspective of the system designer who is interested in finding the best incentive mechanisms to influence the selfish end-users so that the overall system utility is maximized. We propose and compare multiple mechanisms (based on optimal bonus payment, social incentive leveraging, and second price auction) to study how a system designer can exploit the selfishness of its users, to design incentive mechanisms which improve the overall task-completion probability and system performance, while possibly still benefiting the individual users.
Multiaxial pedicle screw designs: static and dynamic mechanical testing.
Stanford, Ralph Edward; Loefler, Andreas Herman; Stanford, Philip Mark; Walsh, William R
2004-02-15
Randomized investigation of multiaxial pedicle screw mechanical properties. Measure static yield and ultimate strengths, yield stiffness, and fatigue resistance according to an established model. Compare these measured properties with expected loads in vivo. Multiaxial pedicle screws provide surgical versatility, but the complexity of their design may reduce their strength and fatigue resistance. There is no published data on the mechanical properties of such screws. Screws were assembled according to a vertebrectomy model for destructive mechanical testing. Groups of five assemblies were tested in static tension and compression and subject to three cyclical loads. Modes of failure, yield, and ultimate strength, yield stiffness, and cycles to failure were determined for six designs of screw. Static compression yield loads ranged from 217.1 to 388.0 N and yield stiffness from 23.7 to 38.0 N/mm. Cycles to failure ranged from 42 x 10(3) to 4,719 x 10(3) at 75% of static ultimate load. There were significant differences between designs in all modes of testing. Failure occurred at the multiaxial link in static and cyclical compression. Bending yield strengths just exceeded loads expected in vivo. Multiaxial designs had lower static bending yield strength than fixed screw designs. Five out of six multiaxial screw designs achieved one million cycles at 200 N in compression bending. "Ball-in-cup" multiaxial locking mechanisms were vulnerable to fatigue failure. Smooth surfaces and thicker material appeared to be protective against fatigue failure.
Game Theoretic Problems in Network Economics and Mechanism Design Solutions
Narahari, Y; Narayanam, Ramasuri; Prakash, Hastagiri
2009-01-01
Explores game theoretic modeling and mechanism design for problem solving in Internet and network economics. This monograph contains an exposition of representative game theoretic problems in three different network economics situations and a systematic exploration of mechanism design solutions to these problems.
Learning algorithms and automatic processing of languages
International Nuclear Information System (INIS)
Fluhr, Christian Yves Andre
1977-01-01
This research thesis concerns the field of artificial intelligence. It addresses learning algorithms applied to automatic processing of languages. The author first briefly describes some mechanisms of human intelligence in order to describe how these mechanisms are simulated on a computer. He outlines the specific role of learning in various manifestations of intelligence. Then, based on the Markov's algorithm theory, the author discusses the notion of learning algorithm. Two main types of learning algorithms are then addressed: firstly, an 'algorithm-teacher dialogue' type sanction-based algorithm which aims at learning how to solve grammatical ambiguities in submitted texts; secondly, an algorithm related to a document system which structures semantic data automatically obtained from a set of texts in order to be able to understand by references to any question on the content of these texts
Design and simulation of airport congestion control algorithms
Simaiakis, Ioannis; Balakrishnan, Hamsa
2014-01-01
This paper proposes a stochastic model of runway departures and a dynamic programming algorithm for their control at congested airports. Using a multi-variable state description that includes the capacity forecast, the runway system is modeled as a semi-Markov process. The paper then introduces a queuing system for modeling the controlled departure process that enables the efficient calculation of optimal pushback policies using decomposition techniques. The developed algorithm is simulated a...
Mechanical design of a high field common coil magnet
Caspi, S; Dietderich, D R; Gourlay, S A; Gupta, R; McInturff, A; Millos, G; Scanlan, R M
1999-01-01
A common coil design for high field 2-in-1 accelerator magnets has been previously presented as a "conductor-friendly" option for high field magnets applicable for a Very Large Hadron Collider. This paper presents the mechanical design for a 14 tesla 2-in-1 dipole based on the common coil design approach. The magnet will use a high current density Nb/sub 3/Sn conductor. The design addresses mechanical issues particular to the common coil geometry: horizontal support against coil edges, vertical preload on coil faces, end loading and support, and coil stresses and strains. The magnet is the second in a series of racetrack coil magnets that will provide experimental verification of the common coil design approach. (9 refs).
International Nuclear Information System (INIS)
Schwall, R.E.; Gray, W.H.; Long, C.J.
1977-01-01
ORPUS-3 is the third in a series of pulsed superconducting solenoids built to test construction techniques applicable to tokamak poloidal field coils. The present coil is designed to be charged to a maximum field of 7 T in 1 sec. Stored energy is approximately 300 kJ. The conductor is a high copper-superconductor ratio mixed matrix material developed for this application. In this paper we present a mechanical design which uses distributed reinforcement to support a self-ventilating braid conductor. Using this design, it has been possible to obtain a high overall current density and a low heat flux in a fully normal zone. In order for the stress to be kept within acceptable limits in the reinforcing material, a programmed winding tension schedule has been calculated. The deflection, stress, and strain of the windings are predicted using the STANSOL-II computer code
Optimal Design of Gravity Pipeline Systems Using Genetic Algorithm and Mathematical Optimization
Directory of Open Access Journals (Sweden)
maryam rohani
2015-03-01
Full Text Available In recent years, the optimal design of pipeline systems has become increasingly important in the water industry. In this study, the two methods of genetic algorithm and mathematical optimization were employed for the optimal design of pipeline systems with the objective of avoiding the water hammer effect caused by valve closure. The problem of optimal design of a pipeline system is a constrained one which should be converted to an unconstrained optimization problem using an external penalty function approach in the mathematical programming method. The quality of the optimal solution greatly depends on the value of the penalty factor that is calculated by the iterative method during the optimization procedure such that the computational effort is simultaneously minimized. The results obtained were used to compare the GA and mathematical optimization methods employed to determine their efficiency and capabilities for the problem under consideration. It was found that the mathematical optimization method exhibited a slightly better performance compared to the GA method.
Mechanical Design of Metal Dome for Industrial Application
Jin-Chee Liu, Thomas; Chen, Li-Wei; Lin, Nai-Pin
2018-02-01
In this paper, the mechanical design of metal domes is studied using finite element analysis. The snap-through behavior of a practical button design that uses a metal dome is found. In addition, the individual click ratio and maximum force for a variety of metal domes are determined. This paper provides guidance on button design for industrial engineers.
Software design to calculate and simulate the mechanical response of electromechanical lifts
Herrera, I.; Romero, E.
2016-05-01
Lift engineers and lift companies which are involved in the design process of new products or in the research and development of improved components demand a predictive tool of the lift slender system response before testing expensive prototypes. A method for solving the movement of any specified lift system by means of a computer program is presented. The mechanical response of the lift operating in a user defined installation and configuration, for a given excitation and other configuration parameters of real electric motors and its control system, is derived. A mechanical model with 6 degrees of freedom is used. The governing equations are integrated step by step through the Meden-Kutta algorithm in the MATLAB platform. Input data consists on the set point speed for a standard trip and the control parameters of a number of controllers and lift drive machines. The computer program computes and plots very accurately the vertical displacement, velocity, instantaneous acceleration and jerk time histories of the car, counterweight, frame, passengers/loads and lift drive in a standard trip between any two floors of the desired installation. The resulting torque, rope tension and deviation of the velocity plot with respect to the setpoint speed are shown. The software design is implemented in a demo release of the computer program called ElevaCAD. Further on, the program offers the possibility to select the configuration of the lift system and the performance parameters of each component. In addition to the overall system response, detailed information of transients, vibrations of the lift components, ride quality levels, modal analysis and frequency spectrum (FFT) are plotted.
Directory of Open Access Journals (Sweden)
Chunhua Ju
2012-01-01
Full Text Available Managing multiple project is a complex task involving the unrelenting pressures of time and cost. Many studies have proposed various tools and techniques for single-project scheduling; however, the literature further considering multimode or multiproject issues occurring in the real world is rather scarce. In this paper, design structure matrix (DSM and an improved artificial immune network algorithm (aiNet are developed to solve a multi-mode resource-constrained scheduling problem. Firstly, the DSM is used to simplify the mathematic model of multi-project scheduling problem. Subsequently, aiNet algorithm comprised of clonal selection, negative selection, and network suppression is adopted to realize the local searching and global searching, which will assure that it has a powerful searching ability and also avoids the possible combinatorial explosion. Finally, the approach is tested on a set of randomly cases generated from ProGen. The computational results validate the effectiveness of the proposed algorithm comparing with other famous metaheuristic algorithms such as genetic algorithm (GA, simulated annealing algorithm (SA, and ant colony optimization (ACO.
Process Improvement Through Tool Integration in Aero-Mechanical Design
Briggs, Clark
2010-01-01
Emerging capabilities in commercial design tools promise to significantly improve the multi-disciplinary and inter-disciplinary design and analysis coverage for aerospace mechanical engineers. This paper explores the analysis process for two example problems of a wing and flap mechanical drive system and an aircraft landing gear door panel. The examples begin with the design solid models and include various analysis disciplines such as structural stress and aerodynamic loads. Analytical methods include CFD, multi-body dynamics with flexible bodies and structural analysis. Elements of analysis data management, data visualization and collaboration are also included.
SSC collider dipole magnet end mechanical design
International Nuclear Information System (INIS)
Delchamps, S.W.; Bossert, R.C.; Carson, J.; Ewald, K.; Fulton, H.; Kerby, J.; Koska, W.; Strait, J.; Wake, M.; Leung, K.K.
1991-01-01
This paper describes the mechanical design of the ends of Superconducting Super Collider dipole magnets to be constructed and tested at Fermilab. Coil end clamps, end yoke configuration, and end plate design are discussed. Loading of the end plate by axial Lorentz forces is discussed. Relevant data from 40 mm and 50 mm aperture model dipole magnets built and tested at Fermilab are presented. In particular, the apparent influence of end clamp design on the quench behavior of model SSC dipoles is described
Texas Medication Algorithm Project, phase 3 (TMAP-3): rationale and study design.
Rush, A John; Crismon, M Lynn; Kashner, T Michael; Toprac, Marcia G; Carmody, Thomas J; Trivedi, Madhukar H; Suppes, Trisha; Miller, Alexander L; Biggs, Melanie M; Shores-Wilson, Kathy; Witte, Bradley P; Shon, Steven P; Rago, William V; Altshuler, Kenneth Z
2003-04-01
Medication treatment algorithms may improve clinical outcomes, uniformity of treatment, quality of care, and efficiency. However, such benefits have never been evaluated for patients with severe, persistent mental illnesses. This study compared clinical and economic outcomes of an algorithm-driven disease management program (ALGO) with treatment-as-usual (TAU) for adults with DSM-IV schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) treated in public mental health outpatient clinics in Texas. The disorder-specific intervention ALGO included a consensually derived and feasibility-tested medication algorithm, a patient/family educational program, ongoing physician training and consultation, a uniform medical documentation system with routine assessment of symptoms and side effects at each clinic visit to guide ALGO implementation, and prompting by on-site clinical coordinators. A total of 19 clinics from 7 local authorities were matched by authority and urban status, such that 4 clinics each offered ALGO for only 1 disorder (SCZ, BD, or MDD). The remaining 7 TAU clinics offered no ALGO and thus served as controls (TAUnonALGO). To determine if ALGO for one disorder impacted care for another disorder within the same clinic ("culture effect"), additional TAU subjects were selected from 4 of the ALGO clinics offering ALGO for another disorder (TAUinALGO). Patient entry occurred over 13 months, beginning March 1998 and concluding with the final active patient visit in April 2000. Research outcomes assessed at baseline and periodically for at least 1 year included (1) symptoms, (2) functioning, (3) cognitive functioning (for SCZ), (4) medication side effects, (5) patient satisfaction, (6) physician satisfaction, (7) quality of life, (8) frequency of contacts with criminal justice and state welfare system, (9) mental health and medical service utilization and cost, and (10) alcohol and substance abuse and supplemental substance use information
Design and implementation of robust controllers for a gait trainer.
Wang, F C; Yu, C H; Chou, T Y
2009-08-01
This paper applies robust algorithms to control an active gait trainer for children with walking disabilities. Compared with traditional rehabilitation procedures, in which two or three trainers are required to assist the patient, a motor-driven mechanism was constructed to improve the efficiency of the procedures. First, a six-bar mechanism was designed and constructed to mimic the trajectory of children's ankles in walking. Second, system identification techniques were applied to obtain system transfer functions at different operating points by experiments. Third, robust control algorithms were used to design Hinfinity robust controllers for the system. Finally, the designed controllers were implemented to verify experimentally the system performance. From the results, the proposed robust control strategies are shown to be effective.
Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms
Directory of Open Access Journals (Sweden)
Qingjian Ni
2014-01-01
Full Text Available In evolutionary algorithm, population diversity is an important factor for solving performance. In this paper, combined with some population diversity analysis methods in other evolutionary algorithms, three indicators are introduced to be measures of population diversity in PSO algorithms, which are standard deviation of population fitness values, population entropy, and Manhattan norm of standard deviation in population positions. The three measures are used to analyze the population diversity in a relatively new PSO variant—Dynamic Probabilistic Particle Swarm Optimization (DPPSO. The results show that the three measure methods can fully reflect the evolution of population diversity in DPPSO algorithms from different angles, and we also discuss the impact of population diversity on the DPPSO variants. The relevant conclusions of the population diversity on DPPSO can be used to analyze, design, and improve the DPPSO algorithms, thus improving optimization performance, which could also be beneficial to understand the working mechanism of DPPSO theoretically.
Mechanical system design in the engineering design of digital x-ray
International Nuclear Information System (INIS)
Muhammad Awwaluddin; I Putu Susila; Edy Purwanta; Abdul Jalil; Ahmad H
2014-01-01
Has been designed a mechanical system design to hold and moving the x-ray tube, detector films, and a place the holder control box. The design was conducted on the frame foundation, frame columns and frame arms in order to operate the device as well SS304 hollow measuring 40 x 60 x mm with thickness of 2 mm long 4.1 m, size 100 x 100 mm and 2 mm thick along the 2 m, and the size of 40 x 80 mm thickness 2 mm long 1.8 m is needed to reactive the design the linear guide way models HGW20HB 3 m. With the proposed design, the operation of the digital x-rays can be completed as well. (author)
Generation and application of tri-dimensional animation in mechanical design
International Nuclear Information System (INIS)
Liu Li
2003-01-01
The mechanical design can be understood vividly and accurately and can be improved in time when there is any mistake if it is made in tri-dimensional animation. The author introduces the generation process and methods for animation in mechanical design with an example
Opposite Degree Algorithm and Its Applications
Directory of Open Access Journals (Sweden)
Xiao-Guang Yue
2015-12-01
Full Text Available The opposite (Opposite Degree, referred to as OD algorithm is an intelligent algorithm proposed by Yue Xiaoguang et al. Opposite degree algorithm is mainly based on the concept of opposite degree, combined with the idea of design of neural network and genetic algorithm and clustering analysis algorithm. The OD algorithm is divided into two sub algorithms, namely: opposite degree - numerical computation (OD-NC algorithm and opposite degree - Classification computation (OD-CC algorithm.
International Nuclear Information System (INIS)
Coban, Ramazan
2011-01-01
Research highlights: → A closed-loop fuzzy logic controller based on the particle swarm optimization algorithm was proposed for controlling the power level of nuclear research reactors. → The proposed control system was tested for various initial and desired power levels, and it could control the reactor successfully for most situations. → The proposed controller is robust against the disturbances. - Abstract: In this paper, a closed-loop fuzzy logic controller based on the particle swarm optimization algorithm is proposed for controlling the power level of nuclear research reactors. The principle of the fuzzy logic controller is based on the rules constructed from numerical experiments made by means of a computer code for the core dynamics calculation and from human operator's experience and knowledge. In addition to these intuitive and experimental design efforts, consequent parts of the fuzzy rules are optimally (or near optimally) determined using the particle swarm optimization algorithm. The contribution of the proposed algorithm to a reactor control system is investigated in details. The performance of the controller is also tested with numerical simulations in numerous operating conditions from various initial power levels to desired power levels, as well as under disturbance. It is shown that the proposed control system performs satisfactorily under almost all operating conditions, even in the case of very small initial power levels.
Mechanical Cushion Design Influence on Cylinder Dynamics
DEFF Research Database (Denmark)
Borghi, Massimo; Milani, Massimo; Conrad, Finn
2005-01-01
. experimental comparison, involving the piston velocity and the cylinder chambers pressure. After, with the aim of highlighting the effect of mechanical cushions design on a two effect linear actuator dynamic performances, the characteristics modulation of four alternative cushioning systems are determined......The paper deals with the simulation and the experimental verification of the dynamic behaviour of a linear actuator equipped with different configurations of mechanical cushion. A numerical model, developed and tailored to describe the influence of different modulation of the discharged flow......-rate (and of the correspondent discharging orifice design) on the cushioning characteristics variation is firstly introduced. Then, with respect to the case of the cylindrical cushioning engagement, both the reliability and the limits of the numerical approach are highlighted through a numerical vs...
Sisko, Zachary W; Teeter, Matthew G; Lanting, Brent A; Howard, James L; McCalden, Richard W; Naudie, Douglas D; MacDonald, Steven J; Vasarhelyi, Edward M
2017-12-01
Tibial baseplate roughness and polyethylene-insert micromotion resulting from locking-mechanism loosening can lead to polyethylene backside wear in TKAs. However, many retrieval studies examining these variables have evaluated only older TKA implant designs. We used implant-retrieval analysis to examine if there were differences in: (1) backside damage scores, (2) backside damage modes, and (3) backside linear wear rates in five TKA implant designs owing to differing baseplate surface roughness and locking mechanisms. Additionally, we examined if (4) patient demographics influence backside damage and wear. Five TKA implant models (four modern and one historical design) were selected with different tibial baseplate and/or locking mechanism designs. Six tibial inserts retrieved at the time of revision from each TKA model were matched for time in vivo, age of the patient at TKA revision, BMI, sex, revision number, and revision reason. Each insert backside was analyzed for: (1) visual total damage score and (2) individual visual damage modes, both by two observers and with an intraclass correlation coefficient of 0.66 (95% CI, 0.39-0.92), and (3) linear wear rate measured by micro-CT. Median primary outcomes were compared among the five designs. For our given sample size among five groups we could detect with 80% power a 10-point difference in damage score and an 0.11-mm per year difference in wear rate. The polished tibial design with a partial peripheral capture locking mechanism and anterior constraint showed a lower total damage score compared with the nonpolished tibial design with only a complete peripheral-rim locking mechanism (median, 12.5; range, 9.5-18.0; 95% CI, 9.58-16.42 versus median, 22.3; range, 15.5-27.0; 95% CI, 17.5-26.5; p = 0.019). The polished baseplate with a tongue-in-groove locking mechanism showed more abrasions than the nonpolished baseplate with a peripheral-rim capture and antirotational island (median, 7.25; range, 0.5-8.0; 95% CI, 2
SSC collider dipole magnet end mechanical design
International Nuclear Information System (INIS)
Delchamps, S.W.; Bossert, R.C.; Carson, J.; Ewald, K.; Fulton, H.; Kerby, J.; Koska, W.; Strait, J.; Wake, S.M.; Leung, K.K.
1991-05-01
This paper describes the mechanical design of the ends of Superconducting Super Collider dipole magnets to be constructed and tested at Fermilab. Coil end clamps, end yoke configuration, and end plate design are discussed. Loading of the end plate by axial Lorentz forces is discussed. Relevant data from 40 mm and 50 mm aperture model dipole magnets built and tested at Fermilab are presented. In particular, the apparent influence of end clamp design on the quench behavior of model SSC dipoles is described. 8 refs., 3 figs
PDX, mechanical design update and assembly
International Nuclear Information System (INIS)
Knutson, D.; Cavalluzzo, S.; Davenport, J.; Kaminsky, E.; Perry, E.; Willard, J.
1977-01-01
Mechanical design changes and refinements have occurred since the Sixth Symposium on Engineering Problems of Fusion Research. Particular attention is focused on the area of the toroidal field coil lap joint. Preassembly of major components and final assembly and alignment of the toroidal and poloidal field coils is discussed
Ushijima, T.; Yeh, W.
2013-12-01
An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.