Kinoform design with an optimal-rotation-angle method.

Science.gov (United States)

Bengtsson, J

1994-10-10

Kinoforms (i.e., computer-generated phase holograms) are designed with a new algorithm, the optimalrotation- angle method, in the paraxial domain. This is a direct Fourier method (i.e., no inverse transform is performed) in which the height of the kinoform relief in each discrete point is chosen so that the diffraction efficiency is increased. The optimal-rotation-angle algorithm has a straightforward geometrical interpretation. It yields excellent results close to, or better than, those obtained with other state-of-the-art methods. The optimal-rotation-angle algorithm can easily be modified to take different restraints into account; as an example, phase-swing-restricted kinoforms, which distribute the light into a number of equally bright spots (so called fan-outs), were designed. The phase-swing restriction lowers the efficiency, but the uniformity can still be made almost perfect.

A method of network topology optimization design considering application process characteristic

Science.gov (United States)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

Structural Optimization Design of Horizontal-Axis Wind Turbine Blades Using a Particle Swarm Optimization Algorithm and Finite Element Method

Directory of Open Access Journals (Sweden)

Pan Pan

2012-11-01

Full Text Available This paper presents an optimization method for the structural design of horizontal-axis wind turbine (HAWT blades based on the particle swarm optimization algorithm (PSO combined with the finite element method (FEM. The main goal is to create an optimization tool and to demonstrate the potential improvements that could be brought to the structural design of HAWT blades. A multi-criteria constrained optimization design model pursued with respect to minimum mass of the blade is developed. The number and the location of layers in the spar cap and the positions of the shear webs are employed as the design variables, while the strain limit, blade/tower clearance limit and vibration limit are taken into account as the constraint conditions. The optimization of the design of a commercial 1.5 MW HAWT blade is carried out by combining the above method and design model under ultimate (extreme flap-wise load conditions. The optimization results are described and compared with the original design. It shows that the method used in this study is efficient and produces improved designs.

Advanced Topology Optimization Methods for Conceptual Architectural Design

DEFF Research Database (Denmark)

Aage, Niels; Amir, Oded; Clausen, Anders

2015-01-01

This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities...

Advanced Topology Optimization Methods for Conceptual Architectural Design

DEFF Research Database (Denmark)

Aage, Niels; Amir, Oded; Clausen, Anders

2014-01-01

This paper presents a series of new, advanced topology optimization methods, developed specifically for conceptual architectural design of structures. The proposed computational procedures are implemented as components in the framework of a Grasshopper plugin, providing novel capacities...

Reliability-based design optimization using a generalized subset simulation method and posterior approximation

Science.gov (United States)

Ma, Yuan-Zhuo; Li, Hong-Shuang; Yao, Wei-Xing

2018-05-01

The evaluation of the probabilistic constraints in reliability-based design optimization (RBDO) problems has always been significant and challenging work, which strongly affects the performance of RBDO methods. This article deals with RBDO problems using a recently developed generalized subset simulation (GSS) method and a posterior approximation approach. The posterior approximation approach is used to transform all the probabilistic constraints into ordinary constraints as in deterministic optimization. The assessment of multiple failure probabilities required by the posterior approximation approach is achieved by GSS in a single run at all supporting points, which are selected by a proper experimental design scheme combining Sobol' sequences and Bucher's design. Sequentially, the transformed deterministic design optimization problem can be solved by optimization algorithms, for example, the sequential quadratic programming method. Three optimization problems are used to demonstrate the efficiency and accuracy of the proposed method.

A multilevel, level-set method for optimizing eigenvalues in shape design problems

International Nuclear Information System (INIS)

Haber, E.

2004-01-01

In this paper, we consider optimal design problems that involve shape optimization. The goal is to determine the shape of a certain structure such that it is either as rigid or as soft as possible. To achieve this goal we combine two new ideas for an efficient solution of the problem. First, we replace the eigenvalue problem with an approximation by using inverse iteration. Second, we use a level set method but rather than propagating the front we use constrained optimization methods combined with multilevel continuation techniques. Combining these two ideas we obtain a robust and rapid method for the solution of the optimal design problem

A novel optimized LCL-filter designing method for grid connected converter

DEFF Research Database (Denmark)

Guohong, Zeng; Rasmussen, Tonny Wederberg; Teodorescu, Remus

2010-01-01

This paper presents a new LCL-filters optimized designing method for grid connected voltage source converter. This method is based on the analysis of converter output voltage components and inherent relations among LCL-filter parameters. By introducing an optimizing index of equivalent total capa...

Design optimization of hydraulic turbine draft tube based on CFD and DOE method

Science.gov (United States)

Nam, Mun chol; Dechun, Ba; Xiangji, Yue; Mingri, Jin

2018-03-01

In order to improve performance of the hydraulic turbine draft tube in its design process, the optimization for draft tube is performed based on multi-disciplinary collaborative design optimization platform by combining the computation fluid dynamic (CFD) and the design of experiment (DOE) in this paper. The geometrical design variables are considered as the median section in the draft tube and the cross section in its exit diffuser and objective function is to maximize the pressure recovery factor (Cp). Sample matrixes required for the shape optimization of the draft tube are generated by optimal Latin hypercube (OLH) method of the DOE technique and their performances are evaluated through computational fluid dynamic (CFD) numerical simulation. Subsequently the main effect analysis and the sensitivity analysis of the geometrical parameters of the draft tube are accomplished. Then, the design optimization of the geometrical design variables is determined using the response surface method. The optimization result of the draft tube shows a marked performance improvement over the original.

Distributed optimization for systems design : an augmented Lagrangian coordination method

NARCIS (Netherlands)

Tosserams, S.

2008-01-01

This thesis presents a coordination method for the distributed design optimization of engineering systems. The design of advanced engineering systems such as aircrafts, automated distribution centers, and microelectromechanical systems (MEMS) involves multiple components that together realize the

A hybrid optimization method for biplanar transverse gradient coil design

International Nuclear Information System (INIS)

Qi Feng; Tang Xin; Jin Zhe; Jiang Zhongde; Shen Yifei; Meng Bin; Zu Donglin; Wang Weimin

2007-01-01

The optimization of transverse gradient coils is one of the fundamental problems in designing magnetic resonance imaging gradient systems. A new approach is presented in this paper to optimize the transverse gradient coils' performance. First, in the traditional spherical harmonic target field method, high order coefficients, which are commonly ignored, are used in the first stage of the optimization process to give better homogeneity. Then, some cosine terms are introduced into the series expansion of stream function. These new terms provide simulated annealing optimization with new freedoms. Comparison between the traditional method and the optimized method shows that the inhomogeneity in the region of interest can be reduced from 5.03% to 1.39%, the coil efficiency increased from 3.83 to 6.31 mT m -1 A -1 and the minimum distance of these discrete coils raised from 1.54 to 3.16 mm

Global optimization methods for engineering design

Science.gov (United States)

Arora, Jasbir S.

1990-01-01

The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated.

Optimal correction and design parameter search by modern methods of rigorous global optimization

International Nuclear Information System (INIS)

Makino, K.; Berz, M.

2011-01-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle

Design of materials with extreme thermal expansion using a three-phase topology optimization method

DEFF Research Database (Denmark)

Sigmund, Ole; Torquato, S.

1997-01-01

We show how composites with extremal or unusual thermal expansion coefficients can be designed using a numerical topology optimization method. The composites are composed of two different material phases and void. The optimization method is illustrated by designing materials having maximum therma...

Search method optimization technique for thermal design of high power RFQ structure

International Nuclear Information System (INIS)

Sharma, N.K.; Joshi, S.C.

2009-01-01

RRCAT has taken up the development of 3 MeV RFQ structure for the low energy part of 100 MeV H - ion injector linac. RFQ is a precision machined resonating structure designed for high rf duty factor. RFQ structural stability during high rf power operation is an important design issue. The thermal analysis of RFQ has been performed using ANSYS finite element analysis software and optimization of various parameters is attempted using Search Method optimization technique. It is an effective optimization technique for the systems governed by a large number of independent variables. The method involves examining a number of combinations of values of independent variables and drawing conclusions from the magnitude of the objective function at these combinations. In these methods there is a continuous improvement in the objective function throughout the course of the search and hence these methods are very efficient. The method has been employed in optimization of various parameters (called independent variables) of RFQ like cooling water flow rate, cooling water inlet temperatures, cavity thickness etc. involved in RFQ thermal design. The temperature rise within RFQ structure is the objective function during the thermal design. Using ANSYS Programming Development Language (APDL), various multiple iterative programmes are written and the analysis are performed to minimize the objective function. The dependency of the objective function on various independent variables is established and the optimum values of the parameters are evaluated. The results of the analysis are presented in the paper. (author)

OPTIMIZATION OF I-SECTION PROFILE DESIGN BY THE FINITE ELEMENT METHOD

Directory of Open Access Journals (Sweden)

Patryk Różyło

2016-03-01

Full Text Available This paper discusses the problem of design optimization for an I-section profile. The optimization process was performed using the Abaqus program. The numerical analysis of a strictly static problem was based on the finite element method. The scope of the analysis involved both determination of stresses and displacements in the profile and structure topology optimization. The main focus of the numerical analysis was put on reducing profile volume while maintaining the same load and similar stresses prior to and after optimization. The solution of the optimization problem is just an example of the potential of using this method in combination with the finite element method in the Abaqus environment. Nowadays numerical analysis is the most effective cost-reducing alternative to experimental tests and it enables structure examination by means of a computer.

Optimal design of an IPM motor using Taguchi and Rosenbrock's methods

International Nuclear Information System (INIS)

Hwang, C C; Li, P L; Chang, C M; Liu, C T

2011-01-01

Techniques for the design optimization for cogging torque minimization and average torque maximization of a high-speed 2-pole interior permanent magnet (IPM) synchronous motor are presented. It is shown by the finite element method (FEM) and measurement, that combined the Taguchi and Rosenbrock's methods is a very efficient and effective approach in robust design a high performance motor.

Fast optimization method of designing a wideband metasurface without using the Pancharatnam-Berry phase.

Science.gov (United States)

Sui, Sai; Ma, Hua; Lv, Yueguang; Wang, Jiafu; Li, Zhiqiang; Zhang, Jieqiu; Xu, Zhuo; Qu, Shaobo

2018-01-22

Arbitrary control of electromagnetic waves remains a significant challenge although it promises many important applications. Here, we proposed a fast optimization method of designing a wideband metasurface without using the Pancharatnam-Berry (PB) phase, of which the elements are non-absorptive and capable of predicting the wideband and smooth phase-shift. In our design method, the metasurface is composed of low-Q-factor resonant elements without using the PB phase, and is optimized by the genetic algorithm and nonlinear fitting method, having the advantages that the far field scattering patterns can be quickly synthesized by the hybrid array patterns. To validate the design method, a wideband low radar cross section metasurface is demonstrated, showing good feasibility and performance of wideband RCS reduction. This work reveals an opportunity arising from a metasurface in effective manipulation of microwave and flexible fast optimal design method.

OpenMDAO: Framework for Flexible Multidisciplinary Design, Analysis and Optimization Methods

Science.gov (United States)

Heath, Christopher M.; Gray, Justin S.

2012-01-01

The OpenMDAO project is underway at NASA to develop a framework which simplifies the implementation of state-of-the-art tools and methods for multidisciplinary design, analysis and optimization. Foremost, OpenMDAO has been designed to handle variable problem formulations, encourage reconfigurability, and promote model reuse. This work demonstrates the concept of iteration hierarchies in OpenMDAO to achieve a flexible environment for supporting advanced optimization methods which include adaptive sampling and surrogate modeling techniques. In this effort, two efficient global optimization methods were applied to solve a constrained, single-objective and constrained, multiobjective version of a joint aircraft/engine sizing problem. The aircraft model, NASA's nextgeneration advanced single-aisle civil transport, is being studied as part of the Subsonic Fixed Wing project to help meet simultaneous program goals for reduced fuel burn, emissions, and noise. This analysis serves as a realistic test problem to demonstrate the flexibility and reconfigurability offered by OpenMDAO.

Methods for the design and optimization of shaped tokamaks

International Nuclear Information System (INIS)

Haney, S.W.

1988-05-01

Two major questions associated with the design and optimization of shaped tokamaks are considered. How do physics and engineering constraints affect the design of shaped tokamaks? How can the process of designing shaped tokamaks be improved? The first question is addressed with the aid of a completely analytical procedure for optimizing the design of a resistive-magnet tokamak reactor. It is shown that physics constraints---particularly the MHD beta limits and the Murakami density limit---have an enormous, and sometimes, unexpected effect on the final design. The second question is addressed through the development of a series of computer models for calculating plasma equilibria, estimating poloidal field coil currents, and analyzing axisymmetric MHD stability in the presence of resistive conductors and feedback. The models offer potential advantages over conventional methods since they are characterized by extremely fast computer execution times, simplicity, and robustness. Furthermore, evidence is presented that suggests that very little loss of accuracy is required to achieve these desirable features. 94 refs., 66 figs., 14 tabs

Simulated annealing method for electronic circuits design: adaptation and comparison with other optimization methods

International Nuclear Information System (INIS)

Berthiau, G.

1995-10-01

The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistors geometries ...) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient times ...). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyper-rectangular domain ; equality constraints can be eventually specified. A similar problem consists in fitting component models. In this way, the optimization variables are the model parameters and one aims at minimizing a cost function built on the error between the model response and the data measured on the component. The chosen optimization method for this kind of problem is the simulated annealing method. This method, provided by the combinatorial optimization domain, has been adapted and compared with other global optimization methods for the continuous variables problems. An efficient strategy of variables discretization and a set of complementary stopping criteria have been proposed. The different parameters of the method have been adjusted with analytical functions of which minima are known, classically used in the literature. Our simulated annealing algorithm has been coupled with an open electrical simulator SPICE-PAC of which the modular structure allows the chaining of simulations required by the circuit optimization process. We proposed, for high-dimensional problems, a partitioning technique which ensures proportionality between CPU-time and variables number. To compare our method with others, we have adapted three other methods coming from combinatorial optimization domain - the threshold method, a genetic algorithm and the Tabu search method - The tests have been performed on the same set of test functions and the results allow a first comparison between these methods applied to continuous optimization variables. Finally, our simulated annealing program

Detailed design of a lattice composite fuselage structure by a mixed optimization method

Science.gov (United States)

Liu, D.; Lohse-Busch, H.; Toropov, V.; Hühne, C.; Armani, U.

2016-10-01

In this article, a procedure for designing a lattice fuselage barrel is developed. It comprises three stages: first, topology optimization of an aircraft fuselage barrel is performed with respect to weight and structural performance to obtain the conceptual design. The interpretation of the optimal result is given to demonstrate the development of this new lattice airframe concept for the fuselage barrel. Subsequently, parametric optimization of the lattice aircraft fuselage barrel is carried out using genetic algorithms on metamodels generated with genetic programming from a 101-point optimal Latin hypercube design of experiments. The optimal design is achieved in terms of weight savings subject to stability, global stiffness and strain requirements, and then verified by the fine mesh finite element simulation of the lattice fuselage barrel. Finally, a practical design of the composite skin complying with the aircraft industry lay-up rules is presented. It is concluded that the mixed optimization method, combining topology optimization with the global metamodel-based approach, allows the problem to be solved with sufficient accuracy and provides the designers with a wealth of information on the structural behaviour of the novel anisogrid composite fuselage design.

Design of a rotary dielectric elastomer actuator using a topology optimization method based on pairs of curves

Science.gov (United States)

Wang, Nianfeng; Guo, Hao; Chen, Bicheng; Cui, Chaoyu; Zhang, Xianmin

2018-05-01

Dielectric elastomers (DE), known as electromechanical transducers, have been widely used in the field of sensors, generators, actuators and energy harvesting for decades. A large number of DE actuators including bending actuators, linear actuators and rotational actuators have been designed utilizing an experience design method. This paper proposes a new method for the design of DE actuators by using a topology optimization method based on pairs of curves. First, theoretical modeling and optimization design are discussed, after which a rotary dielectric elastomer actuator has been designed using this optimization method. Finally, experiments and comparisons between several DE actuators have been made to verify the optimized result.

Sequential ensemble-based optimal design for parameter estimation: SEQUENTIAL ENSEMBLE-BASED OPTIMAL DESIGN

Energy Technology Data Exchange (ETDEWEB)

Man, Jun [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Zhang, Jiangjiang [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Li, Weixuan [Pacific Northwest National Laboratory, Richland Washington USA; Zeng, Lingzao [Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Institute of Soil and Water Resources and Environmental Science, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou China; Wu, Laosheng [Department of Environmental Sciences, University of California, Riverside California USA

2016-10-01

The ensemble Kalman filter (EnKF) has been widely used in parameter estimation for hydrological models. The focus of most previous studies was to develop more efficient analysis (estimation) algorithms. On the other hand, it is intuitively understandable that a well-designed sampling (data-collection) strategy should provide more informative measurements and subsequently improve the parameter estimation. In this work, a Sequential Ensemble-based Optimal Design (SEOD) method, coupled with EnKF, information theory and sequential optimal design, is proposed to improve the performance of parameter estimation. Based on the first-order and second-order statistics, different information metrics including the Shannon entropy difference (SD), degrees of freedom for signal (DFS) and relative entropy (RE) are used to design the optimal sampling strategy, respectively. The effectiveness of the proposed method is illustrated by synthetic one-dimensional and two-dimensional unsaturated flow case studies. It is shown that the designed sampling strategies can provide more accurate parameter estimation and state prediction compared with conventional sampling strategies. Optimal sampling designs based on various information metrics perform similarly in our cases. The effect of ensemble size on the optimal design is also investigated. Overall, larger ensemble size improves the parameter estimation and convergence of optimal sampling strategy. Although the proposed method is applied to unsaturated flow problems in this study, it can be equally applied in any other hydrological problems.

Advanced methods for the analysis, design, and optimization of SMA-based aerostructures

International Nuclear Information System (INIS)

Hartl, D J; Lagoudas, D C; Calkins, F T

2011-01-01

Engineers continue to apply shape memory alloys to aerospace actuation applications due to their high energy density, robust solid-state actuation, and silent and shock-free operation. Past design and development of such actuators relied on experimental trial and error and empirically derived graphical methods. Over the last two decades, however, it has been repeatedly demonstrated that existing SMA constitutive models can capture stabilized SMA transformation behaviors with sufficient accuracy. This work builds upon past successes and suggests a general framework by which predictive tools can be used to assess the responses of many possible design configurations in an automated fashion. By applying methods of design optimization, it is shown that the integrated implementation of appropriate analysis tools can guide engineers and designers to the best design configurations. A general design optimization framework is proposed for the consideration of any SMA component or assembly of such components that applies when the set of design variables includes many members. This is accomplished by relying on commercially available software and utilizing tools already well established in the design optimization community. Such tools are combined with finite element analysis (FEA) packages that consider a multitude of structural effects. The foundation of this work is a three-dimensional thermomechanical constitutive model for SMAs applicable for arbitrarily shaped bodies. A reduced-order implementation also allows computationally efficient analysis of structural components such as wires, rods, beams and shells. The use of multiple optimization schemes, the consideration of assembled components, and the accuracy of the implemented constitutive model in full and reduced-order forms are all demonstrated

A hybrid method for in-core optimization of pressurized water reactor reload core design

International Nuclear Information System (INIS)

Stevens, J.G.

1995-05-01

The objective of this research is the development of an accurate, practical, and robust method for optimization of the design of loading patterns for pressurized water reactors, a nonlinear, non-convex, integer optimization problem. The many logical constraints which may be applied during the design process are modeled herein by a network construction upon which performance objectives and safety constraints from reactor physics calculations are optimized. This thesis presents the synthesis of the strengths of previous algorithms developed for reload design optimization and extension of robustness through development of a hybrid liberated search algorithm. Development of three independent methods for reload design optimization is presented: random direct search for local improvement, liberated search by simulated annealing, and deterministic search for local improvement via successive linear assignment by branch and bound. Comparative application of the methods to a variety of problems is discussed, including an exhaustive enumeration benchmark created to allow comparison of search results to a known global optimum for a large scale problem. While direct search and determinism are shown to be capable of finding improvement, only the liberation of simulated annealing is found to perform robustly in the non-convex design spaces. The hybrid method SHAMAN is presented. The algorithm applies: determinism to shuffle an initial solution for satisfaction of heuristics and symmetry; liberated search through simulated annealing with a bounds cooling constraint treatment; and search bias through relational heuristics for the application of engineering judgment. The accuracy, practicality, and robustness of the SHAMAN algorithm is demonstrated through application to a variety of reload loading pattern optimization problems

Review of Reliability-Based Design Optimization Approach and Its Integration with Bayesian Method

Science.gov (United States)

Zhang, Xiangnan

2018-03-01

A lot of uncertain factors lie in practical engineering, such as external load environment, material property, geometrical shape, initial condition, boundary condition, etc. Reliability method measures the structural safety condition and determine the optimal design parameter combination based on the probabilistic theory. Reliability-based design optimization (RBDO) is the most commonly used approach to minimize the structural cost or other performance under uncertainty variables which combines the reliability theory and optimization. However, it cannot handle the various incomplete information. The Bayesian approach is utilized to incorporate this kind of incomplete information in its uncertainty quantification. In this paper, the RBDO approach and its integration with Bayesian method are introduced.

A novel design procedure for tractor clutch fingers by using optimization and response surface methods

Energy Technology Data Exchange (ETDEWEB)

Dogan, Oguz; Karpat, Fatih; Yuce, Celalettin; Kaya, Necmettin; Yavuz, Nurettin [Uludag University, Gorukle (Turkmenistan); Sen, Hasan [Valeo A. S., Bursa (Turkmenistan)

2016-06-15

This paper presents a methodology for re-designing a failed tractor transmission component subjected to cyclic loading. Unlike other vehicles, tractors cope with tough working conditions. Thus, it is necessary to re-design components by using modern optimization techniques. To extend their service life, we present a design methodology for a failed tractor clutch power take-off finger. The finger was completely re-designed using topology and shape optimization approach. Stress-life based fatigue analyses were performed. Shape optimization and response surface methodology were conducted to obtain optimum dimensions of the finger. Two design parameters were selected for the design of experiment method and 15 cases were analyzed. By using design of the experiment method, three responses were obtained: Maximum stresses, mass, and displacement depending on the selected the design parameters. After solving the optimization problem, we achieved a maximum stress and mass reduction of 14% and 6%, respectively. The stiffness was improved up to 31.6% compared to the initial design.

Mechanical Design Optimization Using Advanced Optimization Techniques

CERN Document Server

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 ...

A thermal design method for the performance optimization of multi-stream plate-fin heat exchangers

Energy Technology Data Exchange (ETDEWEB)

Wang, Zhe; Li, Yanzhong [Xi’an Jiaotong University, Xi’an (China); Sunden, Bengt [Lund University, Lund (Sweden); Han, Fenghui [Dalian Maritime University, Dalian (China)

2017-06-15

An optimization design method based on field synergy principle is developed for Multi-stream plate-fin heat exchangers (MPHEs) with a segmented differential model. The heat exchanger is divided into a number of sub-exchangers along the main stream, and each sub-exchanger consists of N passages along the height of the exchanger. Compared with the traditional heat exchanger design, this method allows temperature and pressure fields to be obtained via coupling calculation with consideration of variable physical properties and the axial heat loss of the heat exchanger. Finally, the heat exchanger is optimally designed using a temperature-difference uniformity optimization factor based on field synergy principle. This design model can provide an accurate temperature field and pressure field, because the stream properties are determined by the mean temperature and pressure of each local sub-exchanger. Optimum results indicate that the temperature distribution on the cross section of the heat exchanger is relatively uniform and that the temperature difference of heat transfer for each stream is always a small value. These characteristics prove the feasibility and effectiveness of this design model. In this paper, a case of five stream plate-fin heat exchangers for an ethylene plant is designed under a practical cold box operating condition with the proposed model, the structure and heat transfer of which are optimally determined. The design model and optimization method proposed in this work can provide theoretical and technical support to the optimization design of MPHEs.

Optimization of Automotive Suspension System by Design of Experiments: A Nonderivative Method

Directory of Open Access Journals (Sweden)

Anirban C. Mitra

2016-01-01

Full Text Available A lot of health issues like low back pain, digestive disorders, and musculoskeletal disorders are caused as a result of the whole body vibrations induced by automobiles. This paper is concerned with the enhancement and optimization of suspension performance by using factorial methods of Design of Experiments, a nonderivative method. It focuses on the optimization of ride comfort and determining the parameters which affect the suspension behavior significantly as per the guidelines stated in ISO 2631-1:1997 standards. A quarter car test rig integrated with a LabVIEW based data acquisition system was developed to understand the real time behavior of a vehicle. In the pilot experiment, only three primary suspension parameters, that is, spring-stiffness, damping, and sprung mass, were considered and the full factorial method was implemented for the purpose of optimization. But the regression analysis of the data obtained rendered a very low goodness of fit which indicated that other parameters are likely to influence the response. Subsequently, steering geometry angles, camber and toe and tire pressure, were included in the design. Fractional factorial method with six factors was implemented to optimize ride comfort. The resultant optimum combination was then verified on the test rig with high correlation.

A topology optimization method based on the level set method for the design of negative permeability dielectric metamaterials

DEFF Research Database (Denmark)

Otomori, Masaki; Yamada, Takayuki; Izui, Kazuhiro

2012-01-01

This paper presents a level set-based topology optimization method for the design of negative permeability dielectric metamaterials. Metamaterials are artificial materials that display extraordinary physical properties that are unavailable with natural materials. The aim of the formulated...... optimization problem is to find optimized layouts of a dielectric material that achieve negative permeability. The presence of grayscale areas in the optimized configurations critically affects the performance of metamaterials, positively as well as negatively, but configurations that contain grayscale areas...... are highly impractical from an engineering and manufacturing point of view. Therefore, a topology optimization method that can obtain clear optimized configurations is desirable. Here, a level set-based topology optimization method incorporating a fictitious interface energy is applied to a negative...

Study on Feasibility of Applying Function Approximation Moment Method to Achieve Reliability-Based Design Optimization

International Nuclear Information System (INIS)

Huh, Jae Sung; Kwak, Byung Man

2011-01-01

Robust optimization or reliability-based design optimization are some of the methodologies that are employed to take into account the uncertainties of a system at the design stage. For applying such methodologies to solve industrial problems, accurate and efficient methods for estimating statistical moments and failure probability are required, and further, the results of sensitivity analysis, which is needed for searching direction during the optimization process, should also be accurate. The aim of this study is to employ the function approximation moment method into the sensitivity analysis formulation, which is expressed as an integral form, to verify the accuracy of the sensitivity results, and to solve a typical problem of reliability-based design optimization. These results are compared with those of other moment methods, and the feasibility of the function approximation moment method is verified. The sensitivity analysis formula with integral form is the efficient formulation for evaluating sensitivity because any additional function calculation is not needed provided the failure probability or statistical moments are calculated

An Optimal Design Method of Centrifugal Compressors in Consideration of the Efficiency and the Noise

International Nuclear Information System (INIS)

Ha, K. G.; Sung, S. M.; Kang, S. H.

2007-01-01

A centrifugal compressor is a principal part of the fuelcell vehicles, aircraft and home appliances. Therefore not only efficiency but also compact size and a low operation RPM for noise reducing turn into important criteria of centrifugal compressors design. But those criteria are in conflict each other often. In the case of a RPM in particular, it is profitable to lower the RPM for a noise reduction and an endurance. But for a compact size and a light weight, the reverse has a beneficial effect undoubtedly. So it is necessary to introduce a new optimization concept in the centrifugal compressor design. An one dimensional optimal design method for the centrifugal compressor considering a impeller, a vaneless diffuser and a volute at a time is described. The new optimization process and underlying design methods of centrifugal compressors and some optimal design results are included in the paper

Robust design optimization using the price of robustness, robust least squares and regularization methods

Science.gov (United States)

Bukhari, Hassan J.

2017-12-01

In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.

Design of microfluidic bioreactors using topology optimization

DEFF Research Database (Denmark)

Okkels, Fridolin; Bruus, Henrik

2007-01-01

We address the design of optimal reactors for supporting biological cultures using the method of topology optimization. For some years this method have been used to design various optimal microfluidic devices.1-4 We apply this method to distribute optimally biologic cultures within a flow...

Robust design optimization method for centrifugal impellers under surface roughness uncertainties due to blade fouling

Science.gov (United States)

Ju, Yaping; Zhang, Chuhua

2016-03-01

Blade fouling has been proved to be a great threat to compressor performance in operating stage. The current researches on fouling-induced performance degradations of centrifugal compressors are based mainly on simplified roughness models without taking into account the realistic factors such as spatial non-uniformity and randomness of the fouling-induced surface roughness. Moreover, little attention has been paid to the robust design optimization of centrifugal compressor impellers with considerations of blade fouling. In this paper, a multi-objective robust design optimization method is developed for centrifugal impellers under surface roughness uncertainties due to blade fouling. A three-dimensional surface roughness map is proposed to describe the nonuniformity and randomness of realistic fouling accumulations on blades. To lower computational cost in robust design optimization, the support vector regression (SVR) metamodel is combined with the Monte Carlo simulation (MCS) method to conduct the uncertainty analysis of fouled impeller performance. The analyzed results show that the critical fouled region associated with impeller performance degradations lies at the leading edge of blade tip. The SVR metamodel has been proved to be an efficient and accurate means in the detection of impeller performance variations caused by roughness uncertainties. After design optimization, the robust optimal design is found to be more efficient and less sensitive to fouling uncertainties while maintaining good impeller performance in the clean condition. This research proposes a systematic design optimization method for centrifugal compressors with considerations of blade fouling, providing a practical guidance to the design of advanced centrifugal compressors.

A Comparative Study on Recently-Introduced Nature-Based Global Optimization Methods in Complex Mechanical System Design

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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.

Interactive design optimization of magnetorheological-brake actuators using the Taguchi method

Science.gov (United States)

Erol, Ozan; Gurocak, Hakan

2011-10-01

This research explored an optimization method that would automate the process of designing a magnetorheological (MR)-brake but still keep the designer in the loop. MR-brakes apply resistive torque by increasing the viscosity of an MR fluid inside the brake. This electronically controllable brake can provide a very large torque-to-volume ratio, which is very desirable for an actuator. However, the design process is quite complex and time consuming due to many parameters. In this paper, we adapted the popular Taguchi method, widely used in manufacturing, to the problem of designing a complex MR-brake. Unlike other existing methods, this approach can automatically identify the dominant parameters of the design, which reduces the search space and the time it takes to find the best possible design. While automating the search for a solution, it also lets the designer see the dominant parameters and make choices to investigate only their interactions with the design output. The new method was applied for re-designing MR-brakes. It reduced the design time from a week or two down to a few minutes. Also, usability experiments indicated significantly better brake designs by novice users.

Interactive design optimization of magnetorheological-brake actuators using the Taguchi method

International Nuclear Information System (INIS)

Erol, Ozan; Gurocak, Hakan

2011-01-01

This research explored an optimization method that would automate the process of designing a magnetorheological (MR)-brake but still keep the designer in the loop. MR-brakes apply resistive torque by increasing the viscosity of an MR fluid inside the brake. This electronically controllable brake can provide a very large torque-to-volume ratio, which is very desirable for an actuator. However, the design process is quite complex and time consuming due to many parameters. In this paper, we adapted the popular Taguchi method, widely used in manufacturing, to the problem of designing a complex MR-brake. Unlike other existing methods, this approach can automatically identify the dominant parameters of the design, which reduces the search space and the time it takes to find the best possible design. While automating the search for a solution, it also lets the designer see the dominant parameters and make choices to investigate only their interactions with the design output. The new method was applied for re-designing MR-brakes. It reduced the design time from a week or two down to a few minutes. Also, usability experiments indicated significantly better brake designs by novice users

Design Optimization Toolkit: Users' Manual

Energy Technology Data Exchange (ETDEWEB)

Aguilo Valentin, Miguel Alejandro [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Computational Solid Mechanics and Structural Dynamics

2014-07-01

The Design Optimization Toolkit (DOTk) is a stand-alone C++ software package intended to solve complex design optimization problems. DOTk software package provides a range of solution methods that are suited for gradient/nongradient-based optimization, large scale constrained optimization, and topology optimization. DOTk was design to have a flexible user interface to allow easy access to DOTk solution methods from external engineering software packages. This inherent flexibility makes DOTk barely intrusive to other engineering software packages. As part of this inherent flexibility, DOTk software package provides an easy-to-use MATLAB interface that enables users to call DOTk solution methods directly from the MATLAB command window.

An optimal design of wind turbine and ship structure based on neuro-response surface method

Directory of Open Access Journals (Sweden)

Jae-Chul Lee

2015-07-01

Full Text Available The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface. The Response Surface Method (RSM is generally used to predict the system performance in engi-neering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN which is considered as Neuro-Response Surface Method (NRSM. The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II. Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance, we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.

An optimal design of wind turbine and ship structure based on neuro-response surface method

Science.gov (United States)

Lee, Jae-Chul; Shin, Sung-Chul; Kim, Soo-Young

2015-07-01

The geometry of engineering systems affects their performances. For this reason, the shape of engineering systems needs to be optimized in the initial design stage. However, engineering system design problems consist of multi-objective optimization and the performance analysis using commercial code or numerical analysis is generally time-consuming. To solve these problems, many engineers perform the optimization using the approximation model (response surface). The Response Surface Method (RSM) is generally used to predict the system performance in engineering research field, but RSM presents some prediction errors for highly nonlinear systems. The major objective of this research is to establish an optimal design method for multi-objective problems and confirm its applicability. The proposed process is composed of three parts: definition of geometry, generation of response surface, and optimization process. To reduce the time for performance analysis and minimize the prediction errors, the approximation model is generated using the Backpropagation Artificial Neural Network (BPANN) which is considered as Neuro-Response Surface Method (NRSM). The optimization is done for the generated response surface by non-dominated sorting genetic algorithm-II (NSGA-II). Through case studies of marine system and ship structure (substructure of floating offshore wind turbine considering hydrodynamics performances and bulk carrier bottom stiffened panels considering structure performance), we have confirmed the applicability of the proposed method for multi-objective side constraint optimization problems.

Methods of mathematical optimization

Science.gov (United States)

Vanderplaats, G. N.

The fundamental principles of numerical optimization methods are reviewed, with an emphasis on potential engineering applications. The basic optimization process is described; unconstrained and constrained minimization problems are defined; a general approach to the design of optimization software programs is outlined; and drawings and diagrams are shown for examples involving (1) the conceptual design of an aircraft, (2) the aerodynamic optimization of an airfoil, (3) the design of an automotive-engine connecting rod, and (4) the optimization of a 'ski-jump' to assist aircraft in taking off from a very short ship deck.

An optimizing design method for a compact iron shielded superconducting magnet for use in MRI

International Nuclear Information System (INIS)

Tang Xin; Zu Donglin; Wang Tao; Han Baohui

2010-01-01

A method is developed for designing a special iron shielded superconducting magnet for MRI in this paper. The shield is designed as an integral part of the cryostat and high permeability and high saturated magnetization iron material is adopted. This scheme will result in a compact iron shielded magnet. In the presented design, the finite element (FE) method is adopted to calculate the magnetic field produced by superconducting coils and nonlinear iron material. The FE method is incorporated into the simulated annealing method which is employed for corresponding optimization. Therefore, geometrical configurations of both coils and iron shield can be optimized together. This method can deal with discrete design variables which are defined to describe the cable arrangements of coil cross sections. A detailed algorithm of the present design is described and an example for designing a 1.5 T clinical iron shielded magnet for MRI is shown.

An analytical method for optimal design of MR valve structures

International Nuclear Information System (INIS)

Nguyen, Q H; Choi, S B; Lee, Y S; Han, M S

2009-01-01

This paper proposes an analytical methodology for the optimal design of a magnetorheological (MR) valve structure. The MR valve structure is constrained in a specific volume and the optimization problem identifies geometric dimensions of the valve structure that maximize the yield stress pressure drop of a MR valve or the yield stress damping force of a MR damper. In this paper, the single-coil and two-coil annular MR valve structures are considered. After describing the schematic configuration and operating principle of a typical MR valve and damper, a quasi-static model is derived based on the Bingham model of a MR fluid. The magnetic circuit of the valve and damper is then analyzed by applying Kirchoff's law and the magnetic flux conservation rule. Based on quasi-static modeling and magnetic circuit analysis, the optimization problem of the MR valve and damper is built. In order to reduce the computation load, the optimization problem is simplified and a procedure to obtain the optimal solution of the simplified optimization problem is presented. The optimal solution of the simplified optimization problem of the MR valve structure constrained in a specific volume is then obtained and compared with the solution of the original optimization problem and the optimal solution obtained from the finite element method

Design optimization of axial flow hydraulic turbine runner: Part II - multi-objective constrained optimization method

Science.gov (United States)

Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji

2002-06-01

This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright

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.

Adjoint Parameter Sensitivity Analysis for the Hydrodynamic Lattice Boltzmann Method with Applications to Design Optimization

DEFF Research Database (Denmark)

Pingen, Georg; Evgrafov, Anton; Maute, Kurt

2009-01-01

We present an adjoint parameter sensitivity analysis formulation and solution strategy for the lattice Boltzmann method (LBM). The focus is on design optimization applications, in particular topology optimization. The lattice Boltzmann method is briefly described with an in-depth discussion...

The Design of Optimal PID Control Method for Quadcopter Movement Control

Directory of Open Access Journals (Sweden)

Hanum Arrosida

2018-02-01

Full Text Available Nowadays, quadcopter motion control has become a popular research topic because of its versatile ability as an unmanned aircraft can be used to alleviate human labor and also be able to reach dangerous areas or areas which is unreachable to humans. On the other hand, the Optimal PID control method, which incorporates PID and Linear Quadratic Regulator (LQR control methods, has also been widely used in industry and research field because it has advantages that are easy to operate, easy design, and a good level of precision. In the PID control method, the main problem to be solved is the accuracy of the gain value Kp, Ki, and Kd because the inappropriateness of those value will result in an imprecise control action. Based on these problems and referring to the previous study, the optimal PID control method was developed by using PID controller structure with tuning gain parameter of PID through Linear Quadratic Regulator (LQR method. Through the integration of these two control methods, the optimum solutions can be obtained: easier controller design process for quadcopter control when crossing the determined trajectories, steady state error values less than 5% and a stable quadcopter movement with roll and pitch angle stabilization at position 0 radians with minimum energy function.

Nonuniform Overlapping Method in Designing Microstrip Patch Antennas Using Genetic Algorithm Optimization

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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.

Design Optimization Method for Composite Components Based on Moment Reliability-Sensitivity Criteria

Science.gov (United States)

Sun, Zhigang; Wang, Changxi; Niu, Xuming; Song, Yingdong

2017-08-01

In this paper, a Reliability-Sensitivity Based Design Optimization (RSBDO) methodology for the design of the ceramic matrix composites (CMCs) components has been proposed. A practical and efficient method for reliability analysis and sensitivity analysis of complex components with arbitrary distribution parameters are investigated by using the perturbation method, the respond surface method, the Edgeworth series and the sensitivity analysis approach. The RSBDO methodology is then established by incorporating sensitivity calculation model into RBDO methodology. Finally, the proposed RSBDO methodology is applied to the design of the CMCs components. By comparing with Monte Carlo simulation, the numerical results demonstrate that the proposed methodology provides an accurate, convergent and computationally efficient method for reliability-analysis based finite element modeling engineering practice.

Optimal design of geometrically nonlinear shells of revolution with using the mixed finite element method

Science.gov (United States)

Stupishin, L. U.; Nikitin, K. E.; Kolesnikov, A. G.

2018-02-01

The article is concerned with a methodology of optimal design of geometrically nonlinear (flexible) shells of revolution of minimum weight with strength, stability and strain constraints. The problem of optimal design with constraints is reduced to the problem of unconstrained minimization using the penalty functions method. Stress-strain state of shell is determined within the geometrically nonlinear deformation theory. A special feature of the methodology is the use of a mixed finite-element formulation based on the Galerkin method. Test problems for determining the optimal form and thickness distribution of a shell of minimum weight are considered. The validity of the results obtained using the developed methodology is analyzed, and the efficiency of various optimization algorithms is compared to solve the set problem. The developed methodology has demonstrated the possibility and accuracy of finding the optimal solution.

A two-stage optimal planning and design method for combined cooling, heat and power microgrid system

International Nuclear Information System (INIS)

Guo, Li; Liu, Wenjian; Cai, Jiejin; Hong, Bowen; Wang, Chengshan

2013-01-01

Highlights: • A two-stage optimal method is presented for CCHP microgrid system. • Economic and environmental performance are considered as assessment indicators. • Application case demonstrates its good economic and environmental performance. - Abstract: In this paper, a two-stage optimal planning and design method for combined cooling, heat and power (CCHP) microgrid system was presented. The optimal objective was to simultaneously minimize the total net present cost and carbon dioxide emission in life circle. On the first stage, multi-objective genetic algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) was applied to solve the optimal design problem including the optimization of equipment type and capacity. On the second stage, mixed-integer linear programming (MILP) algorithm was used to solve the optimal dispatch problem. The approach was applied to a typical CCHP microgrid system in a hospital as a case study, and the effectiveness of the proposed method was verified

An Integrated Method for Airfoil Optimization

Science.gov (United States)

Okrent, Joshua B.

Design exploration and optimization is a large part of the initial engineering and design process. To evaluate the aerodynamic performance of a design, viscous Navier-Stokes solvers can be used. However this method can prove to be overwhelmingly time consuming when performing an initial design sweep. Therefore, another evaluation method is needed to provide accurate results at a faster pace. To accomplish this goal, a coupled viscous-inviscid method is used. This thesis proposes an integrated method for analyzing, evaluating, and optimizing an airfoil using a coupled viscous-inviscid solver along with a genetic algorithm to find the optimal candidate. The method proposed is different from prior optimization efforts in that it greatly broadens the design space, while allowing the optimization to search for the best candidate that will meet multiple objectives over a characteristic mission profile rather than over a single condition and single optimization parameter. The increased design space is due to the use of multiple parametric airfoil families, namely the NACA 4 series, CST family, and the PARSEC family. Almost all possible airfoil shapes can be created with these three families allowing for all possible configurations to be included. This inclusion of multiple airfoil families addresses a possible criticism of prior optimization attempts since by only focusing on one airfoil family, they were inherently limiting the number of possible airfoil configurations. By using multiple parametric airfoils, it can be assumed that all reasonable airfoil configurations are included in the analysis and optimization and that a global and not local maximum is found. Additionally, the method used is amenable to customization to suit any specific needs as well as including the effects of other physical phenomena or design criteria and/or constraints. This thesis found that an airfoil configuration that met multiple objectives could be found for a given set of nominal

A surrogate assisted evolutionary optimization method with application to the transonic airfoil design

Science.gov (United States)

Shahrokhi, Ava; Jahangirian, Alireza

2010-06-01

A multi-layer perceptron neural network (NN) method is used for efficient estimation of the expensive objective functions in the evolutionary optimization with the genetic algorithm (GA). The estimation capability of the NN is improved by dynamic retraining using the data from successive generations. In addition, the normal distribution of the training data variables is used to determine well-trained parts of the design space for the NN approximation. The efficiency of the method is demonstrated by two transonic airfoil design problems considering inviscid and viscous flow solvers. Results are compared with those of the simple GA and an alternative surrogate method. The total number of flow solver calls is reduced by about 40% using this fitness approximation technique, which in turn reduces the total computational time without influencing the convergence rate of the optimization algorithm. The accuracy of the NN estimation is considerably improved using the normal distribution approach compared with the alternative method.

Reliability-based design optimization via high order response surface method

International Nuclear Information System (INIS)

Li, Hong Shuang

2013-01-01

To reduce the computational effort of reliability-based design optimization (RBDO), the response surface method (RSM) has been widely used to evaluate reliability constraints. We propose an efficient methodology for solving RBDO problems based on an improved high order response surface method (HORSM) that takes advantage of an efficient sampling method, Hermite polynomials and uncertainty contribution concept to construct a high order response surface function with cross terms for reliability analysis. The sampling method generates supporting points from Gauss-Hermite quadrature points, which can be used to approximate response surface function without cross terms, to identify the highest order of each random variable and to determine the significant variables connected with point estimate method. The cross terms between two significant random variables are added to the response surface function to improve the approximation accuracy. Integrating the nested strategy, the improved HORSM is explored in solving RBDO problems. Additionally, a sampling based reliability sensitivity analysis method is employed to reduce the computational effort further when design variables are distributional parameters of input random variables. The proposed methodology is applied on two test problems to validate its accuracy and efficiency. The proposed methodology is more efficient than first order reliability method based RBDO and Monte Carlo simulation based RBDO, and enables the use of RBDO as a practical design tool.

Genetic-evolution-based optimization methods for engineering design

Science.gov (United States)

Rao, S. S.; Pan, T. S.; Dhingra, A. K.; Venkayya, V. B.; Kumar, V.

1990-01-01

This paper presents the applicability of a biological model, based on genetic evolution, for engineering design optimization. Algorithms embodying the ideas of reproduction, crossover, and mutation are developed and applied to solve different types of structural optimization problems. Both continuous and discrete variable optimization problems are solved. A two-bay truss for maximum fundamental frequency is considered to demonstrate the continuous variable case. The selection of locations of actuators in an actively controlled structure, for minimum energy dissipation, is considered to illustrate the discrete variable case.

Design and Optimization of Composite Automotive Hatchback Using Integrated Material-Structure-Process-Performance Method

Science.gov (United States)

Yang, Xudong; Sun, Lingyu; Zhang, Cheng; Li, Lijun; Dai, Zongmiao; Xiong, Zhenkai

2018-03-01

The application of polymer composites as a substitution of metal is an effective approach to reduce vehicle weight. However, the final performance of composite structures is determined not only by the material types, structural designs and manufacturing process, but also by their mutual restrict. Hence, an integrated "material-structure-process-performance" method is proposed for the conceptual and detail design of composite components. The material selection is based on the principle of composite mechanics such as rule of mixture for laminate. The design of component geometry, dimension and stacking sequence is determined by parametric modeling and size optimization. The selection of process parameters are based on multi-physical field simulation. The stiffness and modal constraint conditions were obtained from the numerical analysis of metal benchmark under typical load conditions. The optimal design was found by multi-discipline optimization. Finally, the proposed method was validated by an application case of automotive hatchback using carbon fiber reinforced polymer. Compared with the metal benchmark, the weight of composite one reduces 38.8%, simultaneously, its torsion and bending stiffness increases 3.75% and 33.23%, respectively, and the first frequency also increases 44.78%.

An efficient multilevel optimization method for engineering design

Science.gov (United States)

Vanderplaats, G. N.; Yang, Y. J.; Kim, D. S.

1988-01-01

An efficient multilevel deisgn optimization technique is presented. The proposed method is based on the concept of providing linearized information between the system level and subsystem level optimization tasks. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to use. The disadvantage is that the coupling between subsystems is not dealt with in a precise mathematical manner.

Core design and operation optimization methods based on time-dependent perturbation theory

International Nuclear Information System (INIS)

Greenspan, E.

1983-08-01

A general approach for the optimization of nuclear reactor core design and operation is outlined; it is based on two cornerstones: a newly developed time-dependent (or burnup-dependent) perturbation theory for nonlinear problems and a succesive iteration technique. The resulting approach is capable of handling realistic reactor models using computational methods of any degree of sophistication desired, while accounting for all the constraints imposed. Three general optimization strategies, different in the way for handling the constraints, are formulated. (author)

Experimental design and multicriteria decision making methods for the optimization of ice cream composition

Directory of Open Access Journals (Sweden)

Cristian Rojas

2012-03-01

Full Text Available The aim of the present work was to optimize the sensorial and technological features of ice cream. The experimental work was performed in two stages: 1 optimization of lactose enzymatic hydrolysis, and 2 optimization of the process and product. For the first stage a complete factorial design was developed, optimized using both response surface and the steepest ascent method. In the second stage a mixture design was performed, combining the process variables. The product with the best sensorial acceptance, high yield and low cost was selected. The acceptance of the product was developed by an untrained taster’s panel. As a main result the sensorial and technological features of the final product were improved, establishing the optimum parameters for its elaboration.

Reliability-Based Robust Design Optimization of Structures Considering Uncertainty in Design Variables

Directory of Open Access Journals (Sweden)

Shujuan Wang

2015-01-01

Full Text Available This paper investigates the structural design optimization to cover both the reliability and robustness under uncertainty in design variables. The main objective is to improve the efficiency of the optimization process. To address this problem, a hybrid reliability-based robust design optimization (RRDO method is proposed. Prior to the design optimization, the Sobol sensitivity analysis is used for selecting key design variables and providing response variance as well, resulting in significantly reduced computational complexity. The single-loop algorithm is employed to guarantee the structural reliability, allowing fast optimization process. In the case of robust design, the weighting factor balances the response performance and variance with respect to the uncertainty in design variables. The main contribution of this paper is that the proposed method applies the RRDO strategy with the usage of global approximation and the Sobol sensitivity analysis, leading to the reduced computational cost. A structural example is given to illustrate the performance of the proposed method.

Optimized design of low energy buildings

DEFF Research Database (Denmark)

Rudbeck, Claus Christian; Esbensen, Peter Kjær; Svendsen, Sv Aa Højgaard

1999-01-01

concern which can be seen during the construction of new buildings. People want energy-friendly solutions, but they should be economical optimized. An exonomical optimized building design with respect to energy consumption is the design with the lowest total cost (investment plus operational cost over its...... to evaluate different separate solutions when they interact in the building.When trying to optimize several parameters there is a need for a method, which will show the correct price-performance of each part of a building under design. The problem with not having such a method will first be showed...

A simple method of calculating Stirling engines for engine design optimization

Science.gov (United States)

Martini, W. R.

1978-01-01

A calculation method is presented for a rhombic drive Stirling engine with a tubular heater and cooler and a screen type regenerator. Generally the equations presented describe power generation and consumption and heat losses. It is the simplest type of analysis that takes into account the conflicting requirements inherent in Stirling engine design. The method itemizes the power and heat losses for intelligent engine optimization. The results of engine analysis of the GPU-3 Stirling engine are compared with more complicated engine analysis and with engine measurements.

Optimization of preparation method for ketoprofen-loaded microspheres consisting polymeric blends using simplex lattice mixture design

Energy Technology Data Exchange (ETDEWEB)

Das, Sanjoy Kumar, E-mail: sanjoydasju@gmail.com; Khanam, Jasmina; Nanda, Arunabha

2016-12-01

In the present investigation, simplex lattice mixture design was applied for formulation development and optimization of a controlled release dosage form of ketoprofen microspheres consisting polymers like ethylcellulose and Eudragit{sup ®}RL 100; when those were formed by oil-in-oil emulsion solvent evaporation method. The investigation was carried out to observe the effects of polymer amount, stirring speed and emulsifier concentration (% w/w) on percentage yield, average particle size, drug entrapment efficiency and in vitro drug release in 8 h from the microspheres. Analysis of variance (ANOVA) was used to estimate the significance of the models. Based on the desirability function approach numerical optimization was carried out. Optimized formulation (KTF-O) showed close match between actual and predicted responses with desirability factor 0.811. No adverse reaction between drug and polymers were observed on the basis of Fourier transform infrared (FTIR) spectroscopy and Differential scanning calorimetric (DSC) analysis. Scanning electron microscopy (SEM) was carried out to show discreteness of microspheres (149.2 ± 1.25 μm) and their surface conditions during pre and post dissolution operations. The drug release pattern from KTF-O was best explained by Korsmeyer-Peppas and Higuchi models. The batch of optimized microspheres were found with maximum entrapment (~ 90%), minimum loss (~ 10%) and prolonged drug release for 8 h (91.25%) which may be considered as favourable criteria of controlled release dosage form. - Graphical abstract: Optimization of preparation method for ketoprofen-loaded microspheres consisting polymeric blends using simplex lattice mixture design. - Highlights: • Simplex lattice design was used to optimize ketoprofen-loaded microspheres. • Polymeric blend (Ethylcellulose and Eudragit® RL 100) was used. • Microspheres were prepared by oil-in-oil emulsion solvent evaporation method. • Optimized formulation depicted favourable

Design of materials with extreme thermal expansion using a three-phase topology optimization method

DEFF Research Database (Denmark)

Sigmund, Ole; Torquato, S.

1997-01-01

Composites with extremal or unusual thermal expansion coefficients are designed using a three-phase topology optimization method. The composites are made of two different material phases and a void phase. The topology optimization method consists in finding the distribution of material phases...... materials having maximum directional thermal expansion (thermal actuators), zero isotropic thermal expansion, and negative isotropic thermal expansion. It is shown that materials with effective negative thermal expansion coefficients can be obtained by mixing two phases with positive thermal expansion...

A New Multidisciplinary Design Optimization Method Accounting for Discrete and Continuous Variables under Aleatory and Epistemic Uncertainties

Directory of Open Access Journals (Sweden)

Hong-Zhong Huang

2012-02-01

Full Text Available Various uncertainties are inevitable in complex engineered systems and must be carefully treated in design activities. Reliability-Based Multidisciplinary Design Optimization (RBMDO has been receiving increasing attention in the past decades to facilitate designing fully coupled systems but also achieving a desired reliability considering uncertainty. In this paper, a new formulation of multidisciplinary design optimization, namely RFCDV (random/fuzzy/continuous/discrete variables Multidisciplinary Design Optimization (RFCDV-MDO, is developed within the framework of Sequential Optimization and Reliability Assessment (SORA to deal with multidisciplinary design problems in which both aleatory and epistemic uncertainties are present. In addition, a hybrid discrete-continuous algorithm is put forth to efficiently solve problems where both discrete and continuous design variables exist. The effectiveness and computational efficiency of the proposed method are demonstrated via a mathematical problem and a pressure vessel design problem.

Consideration of a design optimization method for advanced nuclear power plant thermal-hydraulic components

International Nuclear Information System (INIS)

Ridluan, Artit; Tokuhiro, Akira; Manic, Milos; Patterson, Michael; Danchus, William

2009-01-01

In order to meet the global energy demand and also mitigate climate change, we anticipate a significant resurgence of nuclear power in the next 50 years. Globally, Generation III plants (ABWR) have been built; Gen' III+ plants (EPR, AP1000 others) are anticipated in the near term. The U.S. DOE and Japan are respectively pursuing the NGNP and MSFR. There is renewed interest in closing the fuel cycle and gradually introducing the fast reactor into the LWR-dominated global fleet. In order to meet Generation IV criteria, i.e. thermal efficiency, inherent safety, proliferation resistance and economic competitiveness, plant and energy conversion system engineering design have to increasingly meet strict design criteria with reduced margin for reliable safety and uncertainties. Here, we considered a design optimization approach using an anticipated NGNP thermal system component as a Case Study. A systematic, efficient methodology is needed to reduce time consuming trial-and-error and computationally-intensive analyses. We thus developed a design optimization method linking three elements; that is, benchmarked CFD used as a 'design tool', artificial neural networks (ANN) to accommodate non-linear system behavior and enhancement of the 'design space', and finally, response surface methodology (RSM) to optimize the design solution with targeted constraints. The paper presents the methodology including guiding principles, an integration of CFD into design theory and practice, consideration of system non-linearities (such as fluctuating operating conditions) and systematic enhancement of the design space via application of ANN, and a stochastic optimization approach (RSM) with targeted constraints. Results from a Case Study optimizing the printed circuit heat exchanger for the NGNP energy conversion system will be presented. (author)

An Expert System-Driven Method for Parametric Trajectory Optimization During Conceptual Design

Science.gov (United States)

Dees, Patrick D.; Zwack, Mathew R.; Steffens, Michael; Edwards, Stephen; Diaz, Manuel J.; Holt, James B.

2015-01-01

During the early phases of engineering design, the costs committed are high, costs incurred are low, and the design freedom is high. It is well documented that decisions made in these early design phases drive the entire design's life cycle cost. In a traditional paradigm, key design decisions are made when little is known about the design. As the design matures, design changes become more difficult in both cost and schedule to enact. The current capability-based paradigm, which has emerged because of the constrained economic environment, calls for the infusion of knowledge usually acquired during later design phases into earlier design phases, i.e. bringing knowledge acquired during preliminary and detailed design into pre-conceptual and conceptual design. An area of critical importance to launch vehicle design is the optimization of its ascent trajectory, as the optimal trajectory will be able to take full advantage of the launch vehicle's capability to deliver a maximum amount of payload into orbit. Hence, the optimal ascent trajectory plays an important role in the vehicle's affordability posture yet little of the information required to successfully optimize a trajectory is known early in the design phase. Thus, the current paradigm of optimizing ascent trajectories involves generating point solutions for every change in a vehicle's design parameters. This is often a very tedious, manual, and time-consuming task for the analysts. Moreover, the trajectory design space is highly non-linear and multi-modal due to the interaction of various constraints. When these obstacles are coupled with the Program to Optimize Simulated Trajectories (POST), an industry standard program to optimize ascent trajectories that is difficult to use, expert trajectory analysts are required to effectively optimize a vehicle's ascent trajectory. Over the course of this paper, the authors discuss a methodology developed at NASA Marshall's Advanced Concepts Office to address these issues

A buffer material optimal design in the radioactive wastes geological disposal using the satisficing trade-off method and the self-organizing map

International Nuclear Information System (INIS)

Okamoto, Takashi; Hanaoka, Yuya; Aiyoshi, Eitaro; Kobayashi, Yoko

2012-01-01

In this paper, we consider a multi-objective optimization method in order to obtain a preferred solution for the buffer material optimal design problem in the high-level radioactive wastes geological disposal. The buffer material optimal design problem is formulated as a constrained multi-objective optimization problem. Its Pareto optimal solutions are distributed evenly on whole bounds of the feasible region. Hence, we develop a search method to find a preferred solution easily for a decision maker from the Pareto optimal solutions which are distributed evenly and vastly. In the preferred solution search method, the visualization technique of a Pareto optimal solution set using the self-organizing map is introduced into the satisficing trade-off method which is the interactive method to obtain a Pareto optimal solution that satisfies a decision maker. We confirm the effectiveness of the preferred solution search method in the buffer material optimal design problem. (author)

Divertor design through shape optimization

International Nuclear Information System (INIS)

Dekeyser, W.; Baelmans, M.; Reiter, D.

2012-01-01

Due to the conflicting requirements, complex physical processes and large number of design variables, divertor design for next step fusion reactors is a challenging problem, often relying on large numbers of computationally expensive numerical simulations. In this paper, we attempt to partially automate the design process by solving an appropriate shape optimization problem. Design requirements are incorporated in a cost functional which measures the performance of a certain design. By means of changes in the divertor shape, which in turn lead to changes in the plasma state, this cost functional can be minimized. Using advanced adjoint methods, optimal solutions are computed very efficiently. The approach is illustrated by designing divertor targets for optimal power load spreading, using a simplified edge plasma model (copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Optimal Design of Porous Materials

DEFF Research Database (Denmark)

Andreassen, Erik

The focus of this thesis is topology optimization of material microstructures. That is, creating new materials, with attractive properties, by combining classic materials in periodic patterns. First, large-scale topology optimization is used to design complicated three-dimensional materials......, throughout the thesis extra attention is given to obtain structures that can be manufactured. That is also the case in the final part, where a simple multiscale method for the optimization of structural damping is presented. The method can be used to obtain an optimized component with structural details...

Optimal design criteria - prediction vs. parameter estimation

Science.gov (United States)

Waldl, Helmut

2014-05-01

G-optimality is a popular design criterion for optimal prediction, it tries to minimize the kriging variance over the whole design region. A G-optimal design minimizes the maximum variance of all predicted values. If we use kriging methods for prediction it is self-evident to use the kriging variance as a measure of uncertainty for the estimates. Though the computation of the kriging variance and even more the computation of the empirical kriging variance is computationally very costly and finding the maximum kriging variance in high-dimensional regions can be time demanding such that we cannot really find the G-optimal design with nowadays available computer equipment in practice. We cannot always avoid this problem by using space-filling designs because small designs that minimize the empirical kriging variance are often non-space-filling. D-optimality is the design criterion related to parameter estimation. A D-optimal design maximizes the determinant of the information matrix of the estimates. D-optimality in terms of trend parameter estimation and D-optimality in terms of covariance parameter estimation yield basically different designs. The Pareto frontier of these two competing determinant criteria corresponds with designs that perform well under both criteria. Under certain conditions searching the G-optimal design on the above Pareto frontier yields almost as good results as searching the G-optimal design in the whole design region. In doing so the maximum of the empirical kriging variance has to be computed only a few times though. The method is demonstrated by means of a computer simulation experiment based on data provided by the Belgian institute Management Unit of the North Sea Mathematical Models (MUMM) that describe the evolution of inorganic and organic carbon and nutrients, phytoplankton, bacteria and zooplankton in the Southern Bight of the North Sea.

How to use an optimization-based method capable of balancing safety, reliability, and weight in an aircraft design process

International Nuclear Information System (INIS)

Johansson, Cristina; Derelov, Micael; Olvander, Johan

2017-01-01

In order to help decision-makers in the early design phase to improve and make more cost-efficient system safety and reliability baselines of aircraft design concepts, a method (Multi-objective Optimization for Safety and Reliability Trade-off) that is able to handle trade-offs such as system safety, system reliability, and other characteristics, for instance weight and cost, is used. Multi-objective Optimization for Safety and Reliability Trade-off has been developed and implemented at SAAB Aeronautics. The aim of this paper is to demonstrate how the implemented method might work to aid the selection of optimal design alternatives. The method is a three-step method: step 1 involves the modelling of each considered target, step 2 is optimization, and step 3 is the visualization and selection of results (results processing). The analysis is performed within Architecture Design and Preliminary Design steps, according to the company's Product Development Process. The lessons learned regarding the use of the implemented trade-off method in the three cases are presented. The results are a handful of solutions, a basis to aid in the selection of a design alternative. While the implementation of the trade-off method is performed for companies, there is nothing to prevent adapting this method, with minimal modifications, for use in other industrial applications

How to use an optimization-based method capable of balancing safety, reliability, and weight in an aircraft design process

Energy Technology Data Exchange (ETDEWEB)

Johansson, Cristina [Mendeley, Broderna Ugglasgatan, Linkoping (Sweden); Derelov, Micael; Olvander, Johan [Linkoping University, IEI, Dept. of Machine Design, Linkoping (Sweden)

2017-03-15

In order to help decision-makers in the early design phase to improve and make more cost-efficient system safety and reliability baselines of aircraft design concepts, a method (Multi-objective Optimization for Safety and Reliability Trade-off) that is able to handle trade-offs such as system safety, system reliability, and other characteristics, for instance weight and cost, is used. Multi-objective Optimization for Safety and Reliability Trade-off has been developed and implemented at SAAB Aeronautics. The aim of this paper is to demonstrate how the implemented method might work to aid the selection of optimal design alternatives. The method is a three-step method: step 1 involves the modelling of each considered target, step 2 is optimization, and step 3 is the visualization and selection of results (results processing). The analysis is performed within Architecture Design and Preliminary Design steps, according to the company's Product Development Process. The lessons learned regarding the use of the implemented trade-off method in the three cases are presented. The results are a handful of solutions, a basis to aid in the selection of a design alternative. While the implementation of the trade-off method is performed for companies, there is nothing to prevent adapting this method, with minimal modifications, for use in other industrial applications.

Drying of water based foundry coatings: Innovative test, process design and optimization methods

DEFF Research Database (Denmark)

Di Muoio, Giovanni Luca; Johansen, Bjørn Budolph

on real industrial cases. These tools have been developed in order to simulate and optimize the drying process and reduce drying time and power consumption as well as production process design time and cost of expensive drying equipment. Results show that test methods from other industries can be used...... capacity goals there is a need to understand how to design, control and optimize drying processes. The main focus of this project was on the critical parameters and properties to be controlled in production in order to achieve a stable and predictable drying process. We propose for each of these parameters...... of Denmark with the overall aim to optimize the drying process of water based foundry coatings. Drying of foundry coatings is a relatively new process in the foundry industry that followed the introduction of water as a solvent. In order to avoid moisture related quality problems and reach production...

On simultaneous shape and orientational design for eigenfrequency optimization

DEFF Research Database (Denmark)

Pedersen, Niels Leergaard

2007-01-01

Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design of an or......Plates with an internal hole of fixed area are designed in order to maximize the performance with respect to eigenfrequencies. The optimization is performed by simultaneous shape, material, and orientational design. The shape of the hole is designed, and the material design is the design...... of an orthotropic material that can be considered as a fiber-net within each finite element. This fiber-net is optimally oriented in the individual elements of the finite element discretization. The optimizations are performed using the finite element method for analysis, and the optimization approach is a two......-step method. In the first step, we find the best design on the basis of a recursive optimization procedure based on optimality criteria. In the second step, mathematical programming and sensitivity analysis are applied to find the final optimized design....

Rotor Design of IPMSM Traction Motor Based on Multi- Objective Optimization using BFGS Method and Train Motion Equations

Directory of Open Access Journals (Sweden)

S. Ahmadi

2015-09-01

Full Text Available In this paper a multiobjective optimal design method of interior permanent magnet synchronous motor ( IPMSM for traction applications so as to maximize average torque and to minimize torque ripple has been presented. Based on train motion equations and physical properties of train, desired specifications such as steady state speed, rated output power, acceleration time and rated speed of traction motor are related to each other. By considering the same output power, steady state speed, rated voltage, rated current and different acceleration time for a specified train, multiobjective optimal design has been performed by Broyden–Fletcher–Goldfarb–Shanno (BFGS method and finite element method (FEM has been chosen as an analysis tool. BFGS method is one of Quasi Newton methods and is counted in classic approaches. Classic optimization methods are appropriate when FEM is applied as an analysis tool and objective function isn’t expressed in closed form in terms of optimization variables.

GPU-accelerated CFD Simulations for Turbomachinery Design Optimization

NARCIS (Netherlands)

Aissa, M.H.

2017-01-01

Design optimization relies heavily on time-consuming simulations, especially when using gradient-free optimization methods. These methods require a large number of simulations in order to get a remarkable improvement over reference designs, which are nowadays based on the accumulated engineering

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.

Concurrent Aeroservoelastic Design and Optimization of Wind Turbines

DEFF Research Database (Denmark)

Tibaldi, Carlo

This work develops and investigates methods to integrate controllers in the wind turbine design process and to perform wind turbine optimization. These techniques can exploit the synergy between wind turbine components and generate new design solutions. Two frameworks to perform wind turbine...... optimization design are presented. These tools handle workflows to model a wind turbine and to evaluate loads and performances under specific conditions. Three approaches to evaluate loads are proposed and integrated in the optimization codes. The first method is based on time domain simulations, the second...... simulations, allows the selection of any controller parameter. The methods to evaluate loads and the pole-placement technique are then employed to carry out wind turbine optimization design from an aeroservoelastic prospective. Several analysis of the NREL 5 MW Reference Wind Turbine and the DTU 10 MW...

Optimal design method for a digital human–computer interface based on human reliability in a nuclear power plant. Part 3: Optimization method for interface task layout

International Nuclear Information System (INIS)

Jiang, Jianjun; Wang, Yiqun; Zhang, Li; Xie, Tian; Li, Min; Peng, Yuyuan; Wu, Daqing; Li, Peiyao; Ma, Congmin; Shen, Mengxu; Wu, Xing; Weng, Mengyun; Wang, Shiwei; Xie, Cen

2016-01-01

Highlights: • The authors present an optimization algorithm for interface task layout. • The performing process of the proposed algorithm was depicted. • The performance evaluation method adopted neural network method. • The optimization layouts of an event interface tasks were obtained by experiments. - Abstract: This is the last in a series of papers describing the optimal design for a digital human–computer interface of a nuclear power plant (NPP) from three different points based on human reliability. The purpose of this series is to propose different optimization methods from varying perspectives to decrease human factor events that arise from the defects of a human–computer interface. The present paper mainly solves the optimization method as to how to effectively layout interface tasks into different screens. The purpose of this paper is to decrease human errors by reducing the distance that an operator moves among different screens in each operation. In order to resolve the problem, the authors propose an optimization process of interface task layout for digital human–computer interface of a NPP. As to how to automatically layout each interface task into one of screens in each operation, the paper presents a shortest moving path optimization algorithm with dynamic flag based on human reliability. To test the algorithm performance, the evaluation method uses neural network based on human reliability. The less the human error probabilities are, the better the interface task layouts among different screens are. Thus, by analyzing the performance of each interface task layout, the optimization result is obtained. Finally, the optimization layouts of spurious safety injection event interface tasks of the NPP are obtained by an experiment, the proposed methods has a good accuracy and stabilization.

Reliability-Based Topology Optimization Using Stochastic Response Surface Method with Sparse Grid Design

Directory of Open Access Journals (Sweden)

Qinghai Zhao

2015-01-01

Full Text Available A mathematical framework is developed which integrates the reliability concept into topology optimization to solve reliability-based topology optimization (RBTO problems under uncertainty. Two typical methodologies have been presented and implemented, including the performance measure approach (PMA and the sequential optimization and reliability assessment (SORA. To enhance the computational efficiency of reliability analysis, stochastic response surface method (SRSM is applied to approximate the true limit state function with respect to the normalized random variables, combined with the reasonable design of experiments generated by sparse grid design, which was proven to be an effective and special discretization technique. The uncertainties such as material property and external loads are considered on three numerical examples: a cantilever beam, a loaded knee structure, and a heat conduction problem. Monte-Carlo simulations are also performed to verify the accuracy of the failure probabilities computed by the proposed approach. Based on the results, it is demonstrated that application of SRSM with SGD can produce an efficient reliability analysis in RBTO which enables a more reliable design than that obtained by DTO. It is also found that, under identical accuracy, SORA is superior to PMA in view of computational efficiency.

On CAD-integrated Structural Topology and Design Optimization

DEFF Research Database (Denmark)

Olhoff, Niels; Bendsøe, M.P.; Rasmussen, John

1991-01-01

Concepts underlying an interactive CAD-based engineering design optimization system are developed, and methods of optimizing the topology, shape and sizing of mechanical components are presented. These methods are integrated in the system, and the method for determining the optimal topology is used...

Systematic design of microstructures by topology optimization

DEFF Research Database (Denmark)

Sigmund, Ole

2003-01-01

The topology optimization method can be used to determine the material distribution in a design domain such that an objective function is maximized and constraints are fulfilled. The method which is based on Finite Element Analysis may be applied to all kinds of material distribution problems like...... extremal material design, sensor and actuator design and MEMS synthesis. The state-of-the-art in topology optimization will be reviewed and older as well as new applications in phononic and photonic crystals design will be presented....

Optimal design methods for a digital human-computer interface based on human reliability in a nuclear power plant

International Nuclear Information System (INIS)

Jiang, Jianjun; Zhang, Li; Xie, Tian; Wu, Daqing; Li, Min; Wang, Yiqun; Peng, Yuyuan; Peng, Jie; Zhang, Mengjia; Li, Peiyao; Ma, Congmin; Wu, Xing

2017-01-01

Highlights: • A complete optimization process is established for digital human-computer interfaces of Npps. • A quick convergence search method is proposed. • The authors propose an affinity error probability mapping function to test human reliability. - Abstract: This is the second in a series of papers describing the optimal design method for a digital human-computer interface of nuclear power plant (Npp) from three different points based on human reliability. The purpose of this series is to explore different optimization methods from varying perspectives. This present paper mainly discusses the optimal design method for quantity of components of the same factor. In monitoring process, quantity of components has brought heavy burden to operators, thus, human errors are easily triggered. To solve the problem, the authors propose an optimization process, a quick convergence search method and an affinity error probability mapping function. Two balanceable parameter values of the affinity error probability function are obtained by experiments. The experimental results show that the affinity error probability mapping function about human-computer interface has very good sensitivity and stability, and that quick convergence search method for fuzzy segments divided by component quantity has better performance than general algorithm.

Enhancing product robustness in reliability-based design optimization

International Nuclear Information System (INIS)

Zhuang, Xiaotian; Pan, Rong; Du, Xiaoping

2015-01-01

Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example. - Highlights: • A unifying framework for integrating RBDO and RPD is proposed. • Implicit product performance function is considered. • The design problem is solved by sequential optimization and reliability assessment. • A sequential sampling technique is developed for improving design optimization. • The comparison with traditional RBDO is provided

Methods for the Optimal Design of Grid-Connected PV Inverters

DEFF Research Database (Denmark)

Koutroulis, Eftichios; Blaabjerg, Frede

2011-01-01

and the efficient processing of this power by the DC/AC inverter. In this paper two new methods are presented for the optimal design of a PV inverter power section, output filter and MPPT control strategy. The influences of the electric grid regulations and standards as well as the PV array operational......The DC/AC inverters are used in grid-connected PV energy production systems as the power processing interface between the PV energy source and the electric grid. The energy injected into the electric grid by the PV installation depends on the amount of power extracted from the PV power source...

Exergy based methods for economic and risk design optimization of energy systems: Application to a gas turbine

International Nuclear Information System (INIS)

Cassetti, G.; Rocco, M.V.; Colombo, E.

2014-01-01

Exergy based analyses are considered by the scientific community appropriate tools for the design and the performance evaluation and improvements of energy systems. Moreover, they are today recognized as proper instruments to assess economic, environmental and social externalities of energy systems. This paper presents the results of a study in which different exergy analysis methods are adopted to determine the optimal design configuration of a gas turbine operating in simple Joule Brayton cycle. Standard exergy and Thermoeconomic analyses are performed to identify the highest thermodynamic efficiency and minimum economic cost configurations of the system, while for the environmental analysis Authors propose an innovative method in which the exergy analysis is combined with a Risk Analysis. With this method the total risk associated to the system is used as objective function in the same way as monetary cost is for standard Thermoeconomic analysis. These three methods aims therefore to determine the optimal design configurations of the system with respect to their specific objective functions, respectively: exergy cost (J/J), monetary (exergoeconomic) cost (€/J) and risk (injured/J) of the product. Results lead to three different optimal design parameters for the system, according to the objective of each analysis procedure. - Highlights: • An original implementation of Thermoeconomic framework is proposed. • Standard Exergy and Thermoeconomic analysis are performed on a case study. • A new model using exergy as allocation criteria for Risk Analysis is performed. • Different optimal configurations are obtained and compared

Optimal cure cycle design of a resin-fiber composite laminate

Science.gov (United States)

Hou, Jean W.; Sheen, Jeenson

1987-01-01

A unified computed aided design method was studied for the cure cycle design that incorporates an optimal design technique with the analytical model of a composite cure process. The preliminary results of using this proposed method for optimal cure cycle design are reported and discussed. The cure process of interest is the compression molding of a polyester which is described by a diffusion reaction system. The finite element method is employed to convert the initial boundary value problem into a set of first order differential equations which are solved simultaneously by the DE program. The equations for thermal design sensitivities are derived by using the direct differentiation method and are solved by the DE program. A recursive quadratic programming algorithm with an active set strategy called a linearization method is used to optimally design the cure cycle, subjected to the given design performance requirements. The difficulty of casting the cure cycle design process into a proper mathematical form is recognized. Various optimal design problems are formulated to address theses aspects. The optimal solutions of these formulations are compared and discussed.

Topology Optimization Design of 3D Continuum Structure with Reserved Hole Based on Variable Density Method

Directory of Open Access Journals (Sweden)

Bai Shiye

2016-05-01

Full Text Available An objective function defined by minimum compliance of topology optimization for 3D continuum structure was established to search optimal material distribution constrained by the predetermined volume restriction. Based on the improved SIMP (solid isotropic microstructures with penalization model and the new sensitivity filtering technique, basic iteration equations of 3D finite element analysis were deduced and solved by optimization criterion method. All the above procedures were written in MATLAB programming language, and the topology optimization design examples of 3D continuum structure with reserved hole were examined repeatedly by observing various indexes, including compliance, maximum displacement, and density index. The influence of mesh, penalty factors, and filter radius on the topology results was analyzed. Computational results showed that the finer or coarser the mesh number was, the larger the compliance, maximum displacement, and density index would be. When the filtering radius was larger than 1.0, the topology shape no longer appeared as a chessboard problem, thus suggesting that the presented sensitivity filtering method was valid. The penalty factor should be an integer because iteration steps increased greatly when it is a noninteger. The above modified variable density method could provide technical routes for topology optimization design of more complex 3D continuum structures in the future.

The optimal design support system for shell components of vehicles using the methods of artificial intelligence

Science.gov (United States)

Szczepanik, M.; Poteralski, A.

2016-11-01

The paper is devoted to an application of the evolutionary methods and the finite element method to the optimization of shell structures. Optimization of thickness of a car wheel (shell) by minimization of stress functional is considered. A car wheel geometry is built from three surfaces of revolution: the central surface with the holes destined for the fastening bolts, the surface of the ring of the wheel and the surface connecting the two mentioned earlier. The last one is subjected to the optimization process. The structures are discretized by triangular finite elements and subjected to the volume constraints. Using proposed method, material properties or thickness of finite elements are changing evolutionally and some of them are eliminated. As a result the optimal shape, topology and material or thickness of the structures are obtained. The numerical examples demonstrate that the method based on evolutionary computation is an effective technique for solving computer aided optimal design.

Helium gas turbine conceptual design by genetic/gradient optimization

International Nuclear Information System (INIS)

Yang, Long; Yu, Suyuan

2003-01-01

Helium gas turbine is the key component of the power conversion system for direct cycle High Temperature Gas-cooled Reactors (HTGR), of which an optimal design is essential for high efficiency. Gas turbine design currently is a multidisciplinary process in which the relationships between constraints, objective functions and variables are very noisy. Due to the ever-increasing complexity of the process, it has becomes very hard for the engineering designer to foresee the consequences of changing certain parts. With classic design procedures which depend on adaptation to baseline design, this problem is usually averted by choosing a large number of design variables based on the engineer's judgment or experience in advance, then reaching a solution through iterative computation and modification. This, in fact, leads to a reduction of the degree of freedom of the design problem, and therefore to a suboptimal design. Furthermore, helium is very different in thermal properties from normal gases; it is uncertain whether the operation experiences of a normal gas turbine could be used in the conceptual design of a helium gas turbine. Therefore, it is difficult to produce an optimal design with the general method of adaptation to baseline. Since their appearance in the 1970s, Genetic algorithms (GAs) have been broadly used in many research fields due to their robustness. GAs have also been used recently in the design and optimization of turbo-machines. Researchers at the General Electronic Company (GE) developed an optimization software called Engineous, and used GAs in the basic design and optimization of turbines. The ITOP study group from Xi'an Transportation University also did some work on optimization of transonic turbine blades. However, since GAs do not have a rigorous theory base, many problems in utilities have arisen, such as premature convergence and uncertainty; the GA doesn't know how to locate the optimal design, and doesn't even know if the optimal solution

Systematic design of acoustic devices by topology optimization

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard; Sigmund, Ole

2005-01-01

We present a method to design acoustic devices with topology optimization. The general algorithm is exemplified by the design of a reflection chamber that minimizes the transmission of acoustic waves in a specified frequency range.......We present a method to design acoustic devices with topology optimization. The general algorithm is exemplified by the design of a reflection chamber that minimizes the transmission of acoustic waves in a specified frequency range....

LMI–based robust controller design approach in aircraft multidisciplinary design optimization problem

Directory of Open Access Journals (Sweden)

Qinghua Zeng

2015-07-01

Full Text Available This article proposes a linear matrix inequality–based robust controller design approach to implement the synchronous design of aircraft control discipline and other disciplines, in which the variation in design parameters is treated as equivalent perturbations. Considering the complicated mapping relationships between the coefficient arrays of aircraft motion model and the aircraft design parameters, the robust controller designed is directly based on the variation in these coefficient arrays so conservative that the multidisciplinary design optimization problem would be too difficult to solve, or even if there is a solution, the robustness of design result is generally poor. Therefore, this article derives the uncertainty model of disciplinary design parameters based on response surface approximation, converts the design problem of the robust controller into a problem of solving a standard linear matrix inequality, and theoretically gives a less conservative design method of the robust controller which is based on the variation in design parameters. Furthermore, the concurrent subspace approach is applied to the multidisciplinary system with this kind of robust controller in the design loop. A multidisciplinary design optimization of a tailless aircraft as example is shown that control discipline can be synchronous optimal design with other discipline, especially this method will greatly reduce the calculated amount of multidisciplinary design optimization and make multidisciplinary design optimization results more robustness of flight performance.

Optimal Layout Design using the Element Connectivity Parameterization Method: Application to Three Dimensional Geometrical Nonlinear Structures

DEFF Research Database (Denmark)

Yoon, Gil Ho; Joung, Young Soo; Kim, Yoon Young

2005-01-01

The topology design optimization of “three-dimensional geometrically-nonlinear” continuum structures is still a difficult problem not only because of its problem size but also the occurrence of unstable continuum finite elements during the design optimization. To overcome this difficulty, the ele......) stiffness matrix of continuum finite elements. Therefore, any finite element code, including commercial codes, can be readily used for the ECP implementation. The key ideas and characteristics of these methods will be presented in this paper....

A short numerical study on the optimization methods influence on topology optimization

DEFF Research Database (Denmark)

Rojas Labanda, Susana; Sigmund, Ole; Stolpe, Mathias

2017-01-01

Structural topology optimization problems are commonly defined using continuous design variables combined with material interpolation schemes. One of the challenges for density based topology optimization observed in the review article (Sigmund and Maute Struct Multidiscip Optim 48(6):1031–1055...... 2013) is the slow convergence that is often encountered in practice, when an almost solid-and-void design is found. The purpose of this forum article is to present some preliminary observations on how designs evolves during the optimization process for different choices of optimization methods...

Intelligent structural optimization: Concept, Model and Methods

International Nuclear Information System (INIS)

Lu, Dagang; Wang, Guangyuan; Peng, Zhang

2002-01-01

Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

Optimal design of lossy bandgap structures

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard

2004-01-01

The method of topology optimization is used to design structures for wave propagation with one lossy material component. Optimized designs for scalar elastic waves are presented for mininimum wave transmission as well as for maximum wave energy dissipation. The structures that are obtained...... are of the 1D or 2D bandgap type depending on the objective and the material parameters....

Solid Rocket Motor Design Using Hybrid Optimization

Directory of Open Access Journals (Sweden)

Kevin Albarado

2012-01-01

Full Text Available A particle swarm/pattern search hybrid optimizer was used to drive a solid rocket motor modeling code to an optimal solution. The solid motor code models tapered motor geometries using analytical burn back methods by slicing the grain into thin sections along the axial direction. Grains with circular perforated stars, wagon wheels, and dog bones can be considered and multiple tapered sections can be constructed. The hybrid approach to optimization is capable of exploring large areas of the solution space through particle swarming, but is also able to climb “hills” of optimality through gradient based pattern searching. A preliminary method for designing tapered internal geometry as well as tapered outer mold-line geometry is presented. A total of four optimization cases were performed. The first two case studies examines designing motors to match a given regressive-progressive-regressive burn profile. The third case study studies designing a neutrally burning right circular perforated grain (utilizing inner and external geometry tapering. The final case study studies designing a linearly regressive burning profile for right circular perforated (tapered grains.

A new experimental design method to optimize formulations focusing on a lubricant for hydrophilic matrix tablets.

Science.gov (United States)

Choi, Du Hyung; Shin, Sangmun; Khoa Viet Truong, Nguyen; Jeong, Seong Hoon

2012-09-01

A robust experimental design method was developed with the well-established response surface methodology and time series modeling to facilitate the formulation development process with magnesium stearate incorporated into hydrophilic matrix tablets. Two directional analyses and a time-oriented model were utilized to optimize the experimental responses. Evaluations of tablet gelation and drug release were conducted with two factors x₁ and x₂: one was a formulation factor (the amount of magnesium stearate) and the other was a processing factor (mixing time), respectively. Moreover, different batch sizes (100 and 500 tablet batches) were also evaluated to investigate an effect of batch size. The selected input control factors were arranged in a mixture simplex lattice design with 13 experimental runs. The obtained optimal settings of magnesium stearate for gelation were 0.46 g, 2.76 min (mixing time) for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The optimal settings for drug release were 0.33 g, 7.99 min for a 100 tablet batch and 1.54 g, 6.51 min for a 500 tablet batch. The exact ratio and mixing time of magnesium stearate could be formulated according to the resulting hydrophilic matrix tablet properties. The newly designed experimental method provided very useful information for characterizing significant factors and hence to obtain optimum formulations allowing for a systematic and reliable experimental design method.

Acoustic design by topology optimization

DEFF Research Database (Denmark)

Dühring, Maria Bayard; Jensen, Jakob Søndergaard; Sigmund, Ole

2008-01-01

To bring down noise levels in human surroundings is an important issue and a method to reduce noise by means of topology optimization is presented here. The acoustic field is modeled by Helmholtz equation and the topology optimization method is based on continuous material interpolation functions...... in the density and bulk modulus. The objective function is the squared sound pressure amplitude. First, room acoustic problems are considered and it is shown that the sound level can be reduced in a certain part of the room by an optimized distribution of reflecting material in a design domain along the ceiling...

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 (

Multi-objective three stage design optimization for island microgrids

International Nuclear Information System (INIS)

Sachs, Julia; Sawodny, Oliver

2016-01-01

Highlights: • An enhanced multi-objective three stage design optimization for microgrids is given. • Use of an optimal control problem for the calculation of the optimal operation. • The inclusion of a detailed battery model with CC/CV charging control. • The determination of a representative profile with optimized number of days. • The proposed method finds its direct application in a design tool for microgids. - Abstract: Hybrid off-grid energy systems enable a cost efficient and reliable energy supply to rural areas around the world. The main potential for a low cost operation and uninterrupted power supply lies in the optimal sizing and operation of such microgrids. In particular, sudden variations in load demand or in the power supply from renewables underline the need for an optimally sized system. This paper presents an efficient multi-objective model based optimization approach for the optimal sizing of all components and the determination of the best power electronic layout. The presented method is divided into three optimization problems to minimize economic and environmental objectives. This design optimization includes detailed components models and an optimized energy dispatch strategy which enables the optimal design of the energy system with respect to an adequate control for the specific configuration. To significantly reduce the computation time without loss of accuracy, the presented method contains the determination of a representative load profile using a k-means clustering method. The k-means algorithm itself is embedded in an optimization problem for the calculation of the optimal number of clusters. The benefits in term of reduced computation time, inclusion of optimal energy dispatch and optimization of power electronic architecture, of the presented optimization method are illustrated using a case study.

Shape optimization of high power centrifugal compressor using multi-objective optimal method

Energy Technology Data Exchange (ETDEWEB)

Kang, Hyun Soo; Lee, Jeong Min; Kim, Youn Jea [School of Mechanical Engineering, Sungkyunkwan University, Seoul (Korea, Republic of)

2015-03-15

In this study, a method for optimal design of impeller and diffuser blades in the centrifugal compressor using response surface method (RSM) and multi-objective genetic algorithm (MOGA) was evaluated. A numerical simulation was conducted using ANSYS CFX with various values of impeller and diffuser parameters, which consist of leading edge (LE) angle, trailing edge (TE) angle, and blade thickness. Each of the parameters was divided into three levels. A total of 45 design points were planned using central composite design (CCD), which is one of the design of experiment (DOE) techniques. Response surfaces that were generated on the basis of the results of DOE were used to determine the optimal shape of impeller and diffuser blade. The entire process of optimization was conducted using ANSYS Design Xplorer (DX). Through the optimization, isentropic efficiency and pressure recovery coefficient, which are the main performance parameters of the centrifugal compressor, were increased by 0.3 and 5, respectively.

Shape optimization of high power centrifugal compressor using multi-objective optimal method

International Nuclear Information System (INIS)

Kang, Hyun Soo; Lee, Jeong Min; Kim, Youn Jea

2015-01-01

In this study, a method for optimal design of impeller and diffuser blades in the centrifugal compressor using response surface method (RSM) and multi-objective genetic algorithm (MOGA) was evaluated. A numerical simulation was conducted using ANSYS CFX with various values of impeller and diffuser parameters, which consist of leading edge (LE) angle, trailing edge (TE) angle, and blade thickness. Each of the parameters was divided into three levels. A total of 45 design points were planned using central composite design (CCD), which is one of the design of experiment (DOE) techniques. Response surfaces that were generated on the basis of the results of DOE were used to determine the optimal shape of impeller and diffuser blade. The entire process of optimization was conducted using ANSYS Design Xplorer (DX). Through the optimization, isentropic efficiency and pressure recovery coefficient, which are the main performance parameters of the centrifugal compressor, were increased by 0.3 and 5, respectively

Optimal experimental design with R

CERN Document Server

Rasch, Dieter; Verdooren, L R; Gebhardt, Albrecht

2011-01-01

Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experimental question. Providing a concise introduction to experimental design theory, Optimal Experimental Design with R: Introduces the philosophy of experimental design Provides an easy process for constructing experimental designs and calculating necessary sample size using R programs Teaches by example using a custom made R program package: OPDOE Consisting of detailed, data-rich examples, this book introduces experimenters to the philosophy of experimentation, experimental design, and data collection. It gives researchers and statisticians guidance in the construction of optimum experimental designs using R programs, including sample size calculations, hypothesis te...

The use of methods of structural optimization at the stage of designing high-rise buildings with steel construction

Science.gov (United States)

Vasilkin, Andrey

2018-03-01

The more designing solutions at the search stage for design for high-rise buildings can be synthesized by the engineer, the more likely that the final adopted version will be the most efficient and economical. However, in modern market conditions, taking into account the complexity and responsibility of high-rise buildings the designer does not have the necessary time to develop, analyze and compare any significant number of options. To solve this problem, it is expedient to use the high potential of computer-aided designing. To implement automated search for design solutions, it is proposed to develop the computing facilities, the application of which will significantly increase the productivity of the designer and reduce the complexity of designing. Methods of structural and parametric optimization have been adopted as the basis of the computing facilities. Their efficiency in the synthesis of design solutions is shown, also the schemes, that illustrate and explain the introduction of structural optimization in the traditional design of steel frames, are constructed. To solve the problem of synthesis and comparison of design solutions for steel frames, it is proposed to develop the computing facilities that significantly reduces the complexity of search designing and based on the use of methods of structural and parametric optimization.

A method for optimizing the performance of buildings

DEFF Research Database (Denmark)

Pedersen, Frank

2007-01-01

needed for solving the optimization problem. Furthermore, the algorithm uses so-called domain constraint functions in order to ensure that the input to the simulation software is feasible. Using this technique avoids performing time-consuming simulations for unrealistic design decisions. The algorithm......This thesis describes a method for optimizing the performance of buildings. Design decisions made in early stages of the building design process have a significant impact on the performance of buildings, for instance, the performance with respect to the energy consumption, economical aspects......, and the indoor environment. The method is intended for supporting design decisions for buildings, by combining methods for calculating the performance of buildings with numerical optimization methods. The method is able to find optimum values of decision variables representing different features of the building...

Manufacturing error sensitivity analysis and optimal design method of cable-network antenna structures

Science.gov (United States)

Zong, Yali; Hu, Naigang; Duan, Baoyan; Yang, Guigeng; Cao, Hongjun; Xu, Wanye

2016-03-01

Inevitable manufacturing errors and inconsistency between assumed and actual boundary conditions can affect the shape precision and cable tensions of a cable-network antenna, and even result in failure of the structure in service. In this paper, an analytical sensitivity analysis method of the shape precision and cable tensions with respect to the parameters carrying uncertainty was studied. Based on the sensitivity analysis, an optimal design procedure was proposed to alleviate the effects of the parameters that carry uncertainty. The validity of the calculated sensitivities is examined by those computed by a finite difference method. Comparison with a traditional design method shows that the presented design procedure can remarkably reduce the influence of the uncertainties on the antenna performance. Moreover, the results suggest that especially slender front net cables, thick tension ties, relatively slender boundary cables and high tension level can improve the ability of cable-network antenna structures to resist the effects of the uncertainties on the antenna performance.

Optimal design of RTCs in digital circuit fault self-repair based on global signal optimization

Institute of Scientific and Technical Information of China (English)

Zhang Junbin; Cai Jinyan; Meng Yafeng

2016-01-01

Since digital circuits have been widely and thoroughly applied in various fields, electronic systems are increasingly more complicated and require greater reliability. Faults may occur in elec-tronic systems in complicated environments. If immediate field repairs are not made on the faults, elec-tronic systems will not run normally, and this will lead to serious losses. The traditional method for improving system reliability based on redundant fault-tolerant technique has been unable to meet the requirements. Therefore, on the basis of (evolvable hardware)-based and (reparation balance technology)-based electronic circuit fault self-repair strategy proposed in our preliminary work, the optimal design of rectification circuits (RTCs) in electronic circuit fault self-repair based on global sig-nal optimization is deeply researched in this paper. First of all, the basic theory of RTC optimal design based on global signal optimization is proposed. Secondly, relevant considerations and suitable ranges are analyzed. Then, the basic flow of RTC optimal design is researched. Eventually, a typical circuit is selected for simulation verification, and detailed simulated analysis is made on five circumstances that occur during RTC evolution. The simulation results prove that compared with the conventional design method based RTC, the global signal optimization design method based RTC is lower in hardware cost, faster in circuit evolution, higher in convergent precision, and higher in circuit evolution success rate. Therefore, the global signal optimization based RTC optimal design method applied in the elec-tronic circuit fault self-repair technology is proven to be feasible, effective, and advantageous.

Design and fabrication of topologically optimized structures;

DEFF Research Database (Denmark)

Feringa, Jelle; Søndergaard, Asbjørn

2012-01-01

Integral structural optimization and fabrication seeks the synthesis of two original approaches; that of topological optimization (TO) and robotic hotwire cutting (HWC) (Mcgee 2011). TO allows for the reduction of up to 70% of the volume of concrete to support a given structure (Sondergaard...... & Dombernowsky 2011). A strength of the method is that it allows to come up with structural designs that lie beyond the grasp of traditional means of design. A design space is a discretized volume, delimiting where the optimization will take place. The number of cells used to discretize the design space thus...

Multi-modal distribution crossover method based on two crossing segments bounded by selected parents applied to multi-objective design optimization

Energy Technology Data Exchange (ETDEWEB)

Ariyarit, Atthaphon; Kanazaki, Masahiro [Tokyo Metropolitan University, Tokyo (Japan)

2015-04-15

This paper discusses airfoil design optimization using a genetic algorithm (GA) with multi-modal distribution crossover (MMDX). The proposed crossover method creates four segments from four parents, of which two segments are bounded by selected parents and two segments are bounded by one parent and another segment. After these segments are defined, four offsprings are generated. This study applied the proposed optimization to a real-world, multi-objective airfoil design problem using class-shape function transformation parameterization, which is an airfoil representation that uses polynomial function, to investigate the effectiveness of this algorithm. The results are compared with the results of the blend crossover (BLX) and unimodal normal distribution crossover (UNDX) algorithms. The objective of these airfoil design problems is to successfully find the optimal design. The outcome of using this algorithm is superior to that of the BLX and UNDX crossover methods because the proposed method can maintain higher diversity than the BLX and UNDX methods. This advantage is desirable for real-world problems.

Multi-modal distribution crossover method based on two crossing segments bounded by selected parents applied to multi-objective design optimization

International Nuclear Information System (INIS)

Ariyarit, Atthaphon; Kanazaki, Masahiro

2015-01-01

This paper discusses airfoil design optimization using a genetic algorithm (GA) with multi-modal distribution crossover (MMDX). The proposed crossover method creates four segments from four parents, of which two segments are bounded by selected parents and two segments are bounded by one parent and another segment. After these segments are defined, four offsprings are generated. This study applied the proposed optimization to a real-world, multi-objective airfoil design problem using class-shape function transformation parameterization, which is an airfoil representation that uses polynomial function, to investigate the effectiveness of this algorithm. The results are compared with the results of the blend crossover (BLX) and unimodal normal distribution crossover (UNDX) algorithms. The objective of these airfoil design problems is to successfully find the optimal design. The outcome of using this algorithm is superior to that of the BLX and UNDX crossover methods because the proposed method can maintain higher diversity than the BLX and UNDX methods. This advantage is desirable for real-world problems.

Structural Design Optimization On Thermally Induced Vibration

International Nuclear Information System (INIS)

Gu, Yuanxian; Chen, Biaosong; Zhang, Hongwu; Zhao, Guozhong

2002-01-01

The numerical method of design optimization for structural thermally induced vibration is originally studied in this paper and implemented in application software JIFEX. The direct and adjoint methods of sensitivity analysis for thermal induced vibration coupled with both linear and nonlinear transient heat conduction is firstly proposed. Based on the finite element method, the structural linear dynamics is treated simultaneously with coupled linear and nonlinear transient heat structural linear dynamics is treated simultaneously with coupled linear and nonlinear transient heat conduction. In the thermal analysis model, the nonlinear heat conduction considered is result from the radiation and temperature-dependent materials. The sensitivity analysis of transient linear and nonlinear heat conduction is performed with the precise time integration method. And then, the sensitivity analysis of structural transient dynamics is performed by the Newmark method. Both the direct method and the adjoint method are employed to derive the sensitivity equations of thermal vibration, and there are two adjoint vectors of structure and heat conduction respectively. The coupling effect of heat conduction on thermal vibration in the sensitivity analysis is particularly investigated. With coupling sensitivity analysis, the optimization model is constructed and solved by the sequential linear programming or sequential quadratic programming algorithm. The methods proposed have been implemented in the application software JIFEX of structural design optimization, and numerical examples are given to illustrate the methods and usage of structural design optimization on thermally induced vibration

Performative Computation-aided Design Optimization

Directory of Open Access Journals (Sweden)

Ming Tang

2012-12-01

Full Text Available This article discusses a collaborative research and teaching project between the University of Cincinnati, Perkins+Will’s Tech Lab, and the University of North Carolina Greensboro. The primary investigation focuses on the simulation, optimization, and generation of architectural designs using performance-based computational design approaches. The projects examine various design methods, including relationships between building form, performance and the use of proprietary software tools for parametric design.

Transformation-based spherical cloaks designed by an implicit transformation-independent method: theory and optimization

International Nuclear Information System (INIS)

Novitsky, Andrey; Qiu, C-W; Zouhdi, Said

2009-01-01

Based on the concept of the cloak generating function, we propose an implicit transformation-independent method for the required parameters of spherical cloaks without knowing the needed coordinate transformation beforehand. A non-ideal discrete model is used to calculate and optimize the total scattering cross-sections of different profiles of the generating function. A bell-shaped quadratic spherical cloak is found to be the best candidate, which is further optimized by controlling the design parameters involved. Such improved invisibility is steady even when the model is highly discretized.

New approaches to optimization in aerospace conceptual design

Science.gov (United States)

Gage, Peter J.

1995-01-01

Aerospace design can be viewed as an optimization process, but conceptual studies are rarely performed using formal search algorithms. Three issues that restrict the success of automatic search are identified in this work. New approaches are introduced to address the integration of analyses and optimizers, to avoid the need for accurate gradient information and a smooth search space (required for calculus-based optimization), and to remove the restrictions imposed by fixed complexity problem formulations. (1) Optimization should be performed in a flexible environment. A quasi-procedural architecture is used to conveniently link analysis modules and automatically coordinate their execution. It efficiently controls a large-scale design tasks. (2) Genetic algorithms provide a search method for discontinuous or noisy domains. The utility of genetic optimization is demonstrated here, but parameter encodings and constraint-handling schemes must be carefully chosen to avoid premature convergence to suboptimal designs. The relationship between genetic and calculus-based methods is explored. (3) A variable-complexity genetic algorithm is created to permit flexible parameterization, so that the level of description can change during optimization. This new optimizer automatically discovers novel designs in structural and aerodynamic tasks.

A topology optimization method for design of negative permeability metamaterials

DEFF Research Database (Denmark)

Diaz, A. R.; Sigmund, Ole

2010-01-01

A methodology based on topology optimization for the design of metamaterials with negative permeability is presented. The formulation is based on the design of a thin layer of copper printed on a dielectric, rectangular plate of fixed dimensions. An effective media theory is used to estimate the ...

Multi-physics and multi-objective design of heterogeneous SFR core: development of an optimization method under uncertainty

International Nuclear Information System (INIS)

Ammar, Karim

2014-01-01

Since Phenix shutting down in 2010, CEA does not have Sodium Fast Reactor (SFR) in operating condition. According to global energetic challenge and fast reactor abilities, CEA launched a program of industrial demonstrator called ASTRID (Advanced Sodium Technological Reactor for Industrial Demonstration), a reactor with electric power capacity equal to 600 MW. Objective of the prototype is, in first to be a response to environmental constraints, in second demonstrates the industrial viability of SFR reactor. The goal is to have a safety level at least equal to 3. generation reactors. ASTRID design integrates Fukushima feedback; Waste reprocessing (with minor actinide transmutation) and it linked industry. Installation safety is the priority. In all cases, no radionuclide should be released into environment. To achieve this objective, it is imperative to predict the impact of uncertainty sources on reactor behaviour. In this context, this thesis aims to develop new optimization methods for SFR cores. The goal is to improve the robustness and reliability of reactors in response to existing uncertainties. We will use ASTRID core as reference to estimate interest of new methods and tools developed. The impact of multi-Physics uncertainties in the calculation of the core performance and the use of optimization methods introduce new problems: How to optimize 'complex' cores (i.e. associated with design spaces of high dimensions with more than 20 variable parameters), taking into account the uncertainties? What is uncertainties behaviour for optimization core compare to reference core? Taking into account uncertainties, optimization core are they still competitive? Optimizations improvements are higher than uncertainty margins? The thesis helps to develop and implement methods necessary to take into account uncertainties in the new generation of simulation tools. Statistical methods to ensure consistency of complex multi-Physics simulation results are also

Airfoil design and optimization

Energy Technology Data Exchange (ETDEWEB)

Lutz, T. [Stuttgart Univ. (Germany). Inst. fuer Aerodynamik und Gasdynamik

2001-07-01

The aerodynamic efficiency of mildly swept wings is mainly influenced by the characteristics of the airfoil sections. The specific design of airfoils is therefore one of the classical tasks of aerodynamics. Since the airfoil characteristics are directly dependent on the inviscid pressure distribution the application of inverse calculation methods is obvious. The direct numerical airfoil optimization offers an alternative to the manual design and attracts increasing interest. (orig.)

Automated magnetic divertor design for optimal power exhaust

Energy Technology Data Exchange (ETDEWEB)

Blommaert, Maarten

2017-07-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation

Automated magnetic divertor design for optimal power exhaust

International Nuclear Information System (INIS)

Blommaert, Maarten

2017-01-01

The so-called divertor is the standard particle and power exhaust system of nuclear fusion tokamaks. In essence, the magnetic configuration hereby 'diverts' the plasma to a specific divertor structure. The design of this divertor is still a key issue to be resolved to evolve from experimental fusion tokamaks to commercial power plants. The focus of this dissertation is on one particular design requirement: avoiding excessive heat loads on the divertor structure. The divertor design process is assisted by plasma edge transport codes that simulate the plasma and neutral particle transport in the edge of the reactor. These codes are computationally extremely demanding, not in the least due to the complex collisional processes between plasma and neutrals that lead to strong radiation sinks and macroscopic heat convection near the vessel walls. One way of improving the heat exhaust is by modifying the magnetic confinement that governs the plasma flow. In this dissertation, automated design of the magnetic configuration is pursued using adjoint based optimization methods. A simple and fast perturbation model is used to compute the magnetic field in the vacuum vessel. A stable optimal design method of the nested type is then elaborated that strictly accounts for several nonlinear design constraints and code limitations. Using appropriate cost function definitions, the heat is spread more uniformly over the high-heat load plasma-facing components in a practical design example. Furthermore, practical in-parts adjoint sensitivity calculations are presented that provide a way to an efficient optimization procedure. Results are elaborated for a fictituous JET (Joint European Torus) case. The heat load is strongly reduced by exploiting an expansion of the magnetic flux towards the solid divertor structure. Subsequently, shortcomings of the perturbation model for magnetic field calculations are discussed in comparison to a free boundary equilibrium (FBE) simulation. These flaws

Refining design of superconducting magnets synchronous with winding using particle swarm optimization

International Nuclear Information System (INIS)

Du, J.J.; Wu, W.; Mei, E.M.; Yuan, P.; Ma, L.Z.; Dong, Z.W.

2013-01-01

Highlights: ► A method of synchronous optimization design of superconducting magnets is proposed. ► We get a refining design of a main magnet on Lanzhou Penning Trap by the method. ► We expounds the necessity of tracking optimizing of coils for magnets. ► Particle swarm optimization shows effectiveness in magnet optimization. ► The expected homogeneity of the magnet improves considerably. -- Abstract: A methodology of synchronous optimization design of magnets under construction according to original design scheme is put forward in this paper, and it has been successfully used for refining design of a superconducting magnet on Lanzhou Penning Trap (LPT). This paper expounds the necessity of tracking optimization of magnet coil in the process of traditional manufacturing, and optimization design of magnet coils by particle swarm optimization is proposed. Particle swarm optimization is turned out to be an effective design method for magnet optimization. The expected homogeneity of the magnet is improved to 200 ppm from 1150 ppm through the refining optimizing, which provides important guarantee for required homogeneity of the whole magnet

On the design of 1-3 piezo-composites using topology optimization

DEFF Research Database (Denmark)

Sigmund, Ole; Torquato, S.; Aksay, I.A.

1998-01-01

(h)((*))g(h)((*)), and the electromechanical coupling factor k(h)((*)). The piezocomposite consists of piezoelectric rods embedded in an optimal polymer matrix. We use the topology optimization method to design the optimal (porous) matrix microstructure. When we design for maximum d(h)((*)) and d(h)((*))g(h)((*)) the optimal transversally......We use a topology optimization method to design 1-3 piezocomposites with optimal performance characteristics for hydrophone applications. The performance characteristics we focus on are the hydrostatic charge coefficient d(h)((*)), the hydrophone figure of merit d...

Transportation package design using numerical optimization

International Nuclear Information System (INIS)

Harding, D.C.; Witkowski, W.R.

1992-01-01

The design of structures and engineering systems has always been an iterative process whose complexity was dependent upon the boundary conditions, constraints and available analytical tools. Transportation packaging design is no exception with structural, thermal and radiation shielding constraints based on regulatory hypothetical accident conditions. Transportation packaging design is often accomplished by a group of specialists, each designing a single component based on one or more simple criteria, pooling results with the group, evaluating the open-quotes pooledclose quotes design, and then reiterating the entire process until a satisfactory design is reached. The manual iterative methods used by the designer/analyst can be summarized in the following steps: design the part, analyze the part, interpret the analysis results, modify the part, and re-analyze the part. The inefficiency of this design practice and the frequently conservative result suggests the need for a more structured design methodology, which can simultaneously consider all of the design constraints. Numerical optimization is a structured design methodology whose maturity in development has allowed it to become a primary design tool in many industries. The purpose of this overview is twofold: first, to outline the theory and basic elements of numerical optimization; and second, to show how numerical optimization can be applied to the transportation packaging industry and used to increase efficiency and safety of radioactive and hazardous material transportation packages. A more extensive review of numerical optimization and its applications to radioactive material transportation package design was performed previously by the authors (Witkowski and Harding 1992). A proof-of-concept Type B package design is also presented as a simplified example of potential improvements achievable using numerical optimization in the design process

Development of a novel method for surgical implant design optimization through noninvasive assessment of local bone properties.

Science.gov (United States)

Schiuma, D; Brianza, S; Tami, A E

2011-03-01

A method was developed to improve the design of locking implants by finding the optimal paths for the anchoring elements, based on a high resolution pQCT assessment of local bone mineral density (BMD) distribution and bone micro-architecture (BMA). The method consists of three steps: (1) partial fixation of the implant to the bone and creation of a reference system, (2) implant removal and pQCT scan of the bone, and (3) determination of BMD and BMA of all implant-anchoring locations along the actual and alternative directions. Using a PHILOS plate, the method uncertainty was tested on an artificial humerus bone model. A cadaveric humerus was used to quantify how the uncertainty of the method affects the assessment of bone parameters. BMD and BMA were determined along four possible alternative screw paths as possible criteria for implant optimization. The method is biased by a 0.87 ± 0.12 mm systematic uncertainty and by a 0.44 ± 0.09 mm random uncertainty in locating the virtual screw position. This study shows that this method can be used to find alternative directions for the anchoring elements, which may possess better bone properties. This modification will thus produce an optimized implant design. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Asteroid Rendezvous Mission Design Using Multiobjective Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Ya-zhong Luo

2014-01-01

Full Text Available A new preliminary trajectory design method for asteroid rendezvous mission using multiobjective optimization techniques is proposed. This method can overcome the disadvantages of the widely employed Pork-Chop method. The multiobjective integrated launch window and multi-impulse transfer trajectory design model is formulated, which employes minimum-fuel cost and minimum-time transfer as two objective functions. The multiobjective particle swarm optimization (MOPSO is employed to locate the Pareto solution. The optimization results of two different asteroid mission designs show that the proposed approach can effectively and efficiently demonstrate the relations among the mission characteristic parameters such as launch time, transfer time, propellant cost, and number of maneuvers, which will provide very useful reference for practical asteroid mission design. Compared with the PCP method, the proposed approach is demonstrated to be able to provide much more easily used results, obtain better propellant-optimal solutions, and have much better efficiency. The MOPSO shows a very competitive performance with respect to the NSGA-II and the SPEA-II; besides a proposed boundary constraint optimization strategy is testified to be able to improve its performance.

Present-day Problems and Methods of Optimization in Mechatronics

Directory of Open Access Journals (Sweden)

Tarnowski Wojciech

2017-06-01

Full Text Available It is justified that design is an inverse problem, and the optimization is a paradigm. Classes of design problems are proposed and typical obstacles are recognized. Peculiarities of the mechatronic designing are specified as a proof of a particle importance of optimization in the mechatronic design. Two main obstacles of optimization are discussed: a complexity of mathematical models and an uncertainty of the value system, in concrete case. Then a set of non-standard approaches and methods are presented and discussed, illustrated by examples: a fuzzy description, a constraint-based iterative optimization, AHP ranking method and a few MADM functions in Matlab.

Sequential optimization and reliability assessment method for metal forming processes

International Nuclear Information System (INIS)

Sahai, Atul; Schramm, Uwe; Buranathiti, Thaweepat; Chen Wei; Cao Jian; Xia, Cedric Z.

2004-01-01

Uncertainty is inevitable in any design process. The uncertainty could be due to the variations in geometry of the part, material properties or due to the lack of knowledge about the phenomena being modeled itself. Deterministic design optimization does not take uncertainty into account and worst case scenario assumptions lead to vastly over conservative design. Probabilistic design, such as reliability-based design and robust design, offers tools for making robust and reliable decisions under the presence of uncertainty in the design process. Probabilistic design optimization often involves double-loop procedure for optimization and iterative probabilistic assessment. This results in high computational demand. The high computational demand can be reduced by replacing computationally intensive simulation models with less costly surrogate models and by employing Sequential Optimization and reliability assessment (SORA) method. The SORA method uses a single-loop strategy with a series of cycles of deterministic optimization and reliability assessment. The deterministic optimization and reliability assessment is decoupled in each cycle. This leads to quick improvement of design from one cycle to other and increase in computational efficiency. This paper demonstrates the effectiveness of Sequential Optimization and Reliability Assessment (SORA) method when applied to designing a sheet metal flanging process. Surrogate models are used as less costly approximations to the computationally expensive Finite Element simulations

Crashworthiness design of transient frame structures using topology optimization

DEFF Research Database (Denmark)

Pedersen, Claus B. Wittendorf

2004-01-01

The aim of this paper is to present topology optimization as a method to obtain conceptual designs for crash-worthiness. The topology optimization formulation uses rigorously computed sensitivities. The large displacements and plasticity of the 2D beam elements are modelled with the co-rotational......The aim of this paper is to present topology optimization as a method to obtain conceptual designs for crash-worthiness. The topology optimization formulation uses rigorously computed sensitivities. The large displacements and plasticity of the 2D beam elements are modelled with the co...

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.

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.)

Time-oriented experimental design method to optimize hydrophilic matrix formulations with gelation kinetics and drug release profiles.

Science.gov (United States)

Shin, Sangmun; Choi, Du Hyung; Truong, Nguyen Khoa Viet; Kim, Nam Ah; Chu, Kyung Rok; Jeong, Seong Hoon

2011-04-04

A new experimental design methodology was developed by integrating the response surface methodology and the time series modeling. The major purposes were to identify significant factors in determining swelling and release rate from matrix tablets and their relative factor levels for optimizing the experimental responses. Properties of tablet swelling and drug release were assessed with ten factors and two default factors, a hydrophilic model drug (terazosin) and magnesium stearate, and compared with target values. The selected input control factors were arranged in a mixture simplex lattice design with 21 experimental runs. The obtained optimal settings for gelation were PEO, LH-11, Syloid, and Pharmacoat with weight ratios of 215.33 (88.50%), 5.68 (2.33%), 19.27 (7.92%), and 3.04 (1.25%), respectively. The optimal settings for drug release were PEO and citric acid with weight ratios of 191.99 (78.91%) and 51.32 (21.09%), respectively. Based on the results of matrix swelling and drug release, the optimal solutions, target values, and validation experiment results over time were similar and showed consistent patterns with very small biases. The experimental design methodology could be a very promising experimental design method to obtain maximum information with limited time and resources. It could also be very useful in formulation studies by providing a systematic and reliable screening method to characterize significant factors in the sustained release matrix tablet. Copyright © 2011 Elsevier B.V. All rights reserved.

Integrated topology and shape optimization in structural design

Science.gov (United States)

Bremicker, M.; Chirehdast, M.; Kikuchi, N.; Papalambros, P. Y.

1990-01-01

Structural optimization procedures usually start from a given design topology and vary its proportions or boundary shapes to achieve optimality under various constraints. Two different categories of structural optimization are distinguished in the literature, namely sizing and shape optimization. A major restriction in both cases is that the design topology is considered fixed and given. Questions concerning the general layout of a design (such as whether a truss or a solid structure should be used) as well as more detailed topology features (e.g., the number and connectivities of bars in a truss or the number of holes in a solid) have to be resolved by design experience before formulating the structural optimization model. Design quality of an optimized structure still depends strongly on engineering intuition. This article presents a novel approach for initiating formal structural optimization at an earlier stage, where the design topology is rigorously generated in addition to selecting shape and size dimensions. A three-phase design process is discussed: an optimal initial topology is created by a homogenization method as a gray level image, which is then transformed to a realizable design using computer vision techniques; this design is then parameterized and treated in detail by sizing and shape optimization. A fully automated process is described for trusses. Optimization of two dimensional solid structures is also discussed. Several application-oriented examples illustrate the usefulness of the proposed methodology.

Software for CATV Design and Frequency Plan Optimization

OpenAIRE

Hala, O.

2007-01-01

The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

PARAMETER COORDINATION AND ROBUST OPTIMIZATION FOR MULTIDISCIPLINARY DESIGN

Institute of Scientific and Technical Information of China (English)

HU Jie; PENG Yinghong; XIONG Guangleng

2006-01-01

A new parameter coordination and robust optimization approach for multidisciplinary design is presented. Firstly, the constraints network model is established to support engineering change, coordination and optimization. In this model, interval boxes are adopted to describe the uncertainty of design parameters quantitatively to enhance the design robustness. Secondly, the parameter coordination method is presented to solve the constraints network model, monitor the potential conflicts due to engineering changes, and obtain the consistency solution space corresponding to the given product specifications. Finally, the robust parameter optimization model is established, and genetic arithmetic is used to obtain the robust optimization parameter. An example of bogie design is analyzed to show the scheme to be effective.

Optimizing the design of international safeguards inspection systems

International Nuclear Information System (INIS)

Markin, J.T.; Coulter, C.A.; Gutmacher, R.G.; Whitty, W.J.

1983-01-01

Efficient implementation of international inspections for verifying the operation of a nuclear facility requires that available resources be allocated among inspection activities to maximize detection of misoperation. This report describes a design and evaluation method for selecting an inspection system that is optimal for accomplishing inspection objectives. The discussion includes methods for identifying system objectives, defining performance measures, and choosing between candidate systems. Optimization theory is applied in selecting the most preferred inspection design for a single nuclear facility, and an extension to optimal allocation of inspection resources among States containing multiple facilities is outlined. 3 figures, 5 tables

A neural network-based optimal spatial filter design method for motor imagery classification.

Directory of Open Access Journals (Sweden)

Ayhan Yuksel

Full Text Available In this study, a novel spatial filter design method is introduced. Spatial filtering is an important processing step for feature extraction in motor imagery-based brain-computer interfaces. This paper introduces a new motor imagery signal classification method combined with spatial filter optimization. We simultaneously train the spatial filter and the classifier using a neural network approach. The proposed spatial filter network (SFN is composed of two layers: a spatial filtering layer and a classifier layer. These two layers are linked to each other with non-linear mapping functions. The proposed method addresses two shortcomings of the common spatial patterns (CSP algorithm. First, CSP aims to maximize the between-classes variance while ignoring the minimization of within-classes variances. Consequently, the features obtained using the CSP method may have large within-classes variances. Second, the maximizing optimization function of CSP increases the classification accuracy indirectly because an independent classifier is used after the CSP method. With SFN, we aimed to maximize the between-classes variance while minimizing within-classes variances and simultaneously optimizing the spatial filter and the classifier. To classify motor imagery EEG signals, we modified the well-known feed-forward structure and derived forward and backward equations that correspond to the proposed structure. We tested our algorithm on simple toy data. Then, we compared the SFN with conventional CSP and its multi-class version, called one-versus-rest CSP, on two data sets from BCI competition III. The evaluation results demonstrate that SFN is a good alternative for classifying motor imagery EEG signals with increased classification accuracy.

Numerical methods for metamaterial design

CERN Document Server

2013-01-01

This book describes a relatively new approach for the design of electromagnetic metamaterials.  Numerical optimization routines are combined with electromagnetic simulations to tailor the broadband optical properties of a metamaterial to have predetermined responses at predetermined wavelengths. After a review of both the major efforts within the field of metamaterials and the field of mathematical optimization, chapters covering both gradient-based and derivative-free design methods are considered.  Selected topics including surrogate-base optimization, adaptive mesh search, and genetic algorithms are shown to be effective, gradient-free optimization strategies.  Additionally, new techniques for representing dielectric distributions in two dimensions, including level sets, are demonstrated as effective methods for gradient-based optimization.  Each chapter begins with a rigorous review of the optimization strategy used, and is followed by numerous examples that combine the strategy with either electromag...

Optimal Design of Composite Structures Under Manufacturing Constraints

DEFF Research Database (Denmark)

Marmaras, Konstantinos

determination of the appropriate laminate thickness and the material choice in the structure. The optimal design problems that arise are stated as nonconvex mixed integer programming problems. We resort to different reformulation techniques to state the optimization problems as either linear or nonlinear convex....... The continuous relaxation of the mixed integer programming problems is being solved by an implementation of a primal–dual interior point method for nonlinear programming that updates the barrier parameter adaptively. The method is chosen for its excellent convergence properties and the ability of the method...... design phase results in structures with better structural performance reducing the need of manually post–processing the found designs....

An optimized target-field method for MRI transverse biplanar gradient coil design

International Nuclear Information System (INIS)

Zhang, Rui; Xu, Jing; Huang, Kefu; Zhang, Jue; Fang, Jing; Fu, Youyi; Li, Yangjing

2011-01-01

Gradient coils are essential components of magnetic resonance imaging (MRI) systems. In this paper, we present an optimized target-field method for designing a transverse biplanar gradient coil with high linearity, low inductance and small resistance, which can well satisfy the requirements of permanent-magnet MRI systems. In this new method, the current density is expressed by trigonometric basis functions with unknown coefficients in polar coordinates. Following the standard procedures, we construct an objective function with respect to the total square errors of the magnetic field at all target-field points with the penalty items associated with the stored magnetic energy and the dissipated power. By adjusting the two penalty factors and minimizing the objective function, the appropriate coefficients of the current density are determined. Applying the stream function method to the current density, the specific winding patterns on the planes can be obtained. A novel biplanar gradient coil has been designed using this method to operate in a permanent-magnet MRI system. In order to verify the validity of the proposed approach, the gradient magnetic field generated by the resulted current density has been calculated via the Biot–Savart law. The results have demonstrated the effectiveness and advantage of this proposed method

Cost Optimal System Identification Experiment Design

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning

A structural system identification experiment design method is formulated in the light of decision theory, structural reliability theory and optimization theory. The experiment design is based on a preposterior analysis, well-known from the classical decision theory. I.e. the decisions concerning...... reflecting the cost of the experiment and the value of obtained additional information. An example concerning design of an experiment for parametric identification of a single degree of freedom structural system shows the applicability of the experiment design method....... the experiment design are not based on obtained experimental data. Instead the decisions are based on the expected experimental data assumed to be obtained from the measurements, estimated based on prior information and engineering judgement. The design method provides a system identification experiment design...

Development Optimization and Uncertainty Analysis Methods for Oil and Gas Reservoirs

Energy Technology Data Exchange (ETDEWEB)

Ettehadtavakkol, Amin, E-mail: amin.ettehadtavakkol@ttu.edu [Texas Tech University (United States); Jablonowski, Christopher [Shell Exploration and Production Company (United States); Lake, Larry [University of Texas at Austin (United States)

2017-04-15

Uncertainty complicates the development optimization of oil and gas exploration and production projects, but methods have been devised to analyze uncertainty and its impact on optimal decision-making. This paper compares two methods for development optimization and uncertainty analysis: Monte Carlo (MC) simulation and stochastic programming. Two example problems for a gas field development and an oilfield development are solved and discussed to elaborate the advantages and disadvantages of each method. Development optimization involves decisions regarding the configuration of initial capital investment and subsequent operational decisions. Uncertainty analysis involves the quantification of the impact of uncertain parameters on the optimum design concept. The gas field development problem is designed to highlight the differences in the implementation of the two methods and to show that both methods yield the exact same optimum design. The results show that both MC optimization and stochastic programming provide unique benefits, and that the choice of method depends on the goal of the analysis. While the MC method generates more useful information, along with the optimum design configuration, the stochastic programming method is more computationally efficient in determining the optimal solution. Reservoirs comprise multiple compartments and layers with multiphase flow of oil, water, and gas. We present a workflow for development optimization under uncertainty for these reservoirs, and solve an example on the design optimization of a multicompartment, multilayer oilfield development.

Development Optimization and Uncertainty Analysis Methods for Oil and Gas Reservoirs

International Nuclear Information System (INIS)

Ettehadtavakkol, Amin; Jablonowski, Christopher; Lake, Larry

2017-01-01

Uncertainty complicates the development optimization of oil and gas exploration and production projects, but methods have been devised to analyze uncertainty and its impact on optimal decision-making. This paper compares two methods for development optimization and uncertainty analysis: Monte Carlo (MC) simulation and stochastic programming. Two example problems for a gas field development and an oilfield development are solved and discussed to elaborate the advantages and disadvantages of each method. Development optimization involves decisions regarding the configuration of initial capital investment and subsequent operational decisions. Uncertainty analysis involves the quantification of the impact of uncertain parameters on the optimum design concept. The gas field development problem is designed to highlight the differences in the implementation of the two methods and to show that both methods yield the exact same optimum design. The results show that both MC optimization and stochastic programming provide unique benefits, and that the choice of method depends on the goal of the analysis. While the MC method generates more useful information, along with the optimum design configuration, the stochastic programming method is more computationally efficient in determining the optimal solution. Reservoirs comprise multiple compartments and layers with multiphase flow of oil, water, and gas. We present a workflow for development optimization under uncertainty for these reservoirs, and solve an example on the design optimization of a multicompartment, multilayer oilfield development.

Multidisciplinary Design Optimization (MDO) Methods: Their Synergy with Computer Technology in Design Process

Science.gov (United States)

Sobieszczanski-Sobieski, Jaroslaw

1998-01-01

The paper identifies speed, agility, human interface, generation of sensitivity information, task decomposition, and data transmission (including storage) as important attributes for a computer environment to have in order to support engineering design effectively. It is argued that when examined in terms of these attributes the presently available environment can be shown to be inadequate a radical improvement is needed, and it may be achieved by combining new methods that have recently emerged from multidisciplinary design optimization (MDO) with massively parallel processing computer technology. The caveat is that, for successful use of that technology in engineering computing, new paradigms for computing will have to be developed - specifically, innovative algorithms that are intrinsically parallel so that their performance scales up linearly with the number of processors. It may be speculated that the idea of simulating a complex behavior by interaction of a large number of very simple models may be an inspiration for the above algorithms, the cellular automata are an example. Because of the long lead time needed to develop and mature new paradigms, development should be now, even though the widespread availability of massively parallel processing is still a few years away.

Software for CATV Design and Frequency Plan Optimization

Directory of Open Access Journals (Sweden)

O. Hala

2007-09-01

Full Text Available The paper deals with the structure of a software medium used for design and sub-optimization of frequency plan in CATV networks, their description and design method. The software performance is described and a simple design example of energy balance of a simplified CATV network is given. The software was created in programming environment called Delphi and local optimization was made in Matlab.

Exergetic optimization of a thermoacoustic engine using the particle swarm optimization method

International Nuclear Information System (INIS)

Chaitou, Hussein; Nika, Philippe

2012-01-01

Highlights: ► Optimization of a thermoacoustic engine using the particle swarm optimization method. ► Exergetic efficiency, acoustic power and their product are the optimized functions. ► PSO method is used successfully for the first time in the TA research. ► The powerful PSO tool is advised to be more involved in the TA research and design. ► EE times AP optimized function is highly recommended to design any new TA devices. - Abstract: Thermoacoustic engines convert heat energy into acoustic energy. Then, the acoustic energy can be used to pump heat or to generate electricity. It is well-known that the acoustic energy and therefore the exergetic efficiency depend on parameters such as the stack’s hydraulic radius, the stack’s position in the resonator and the traveling–standing-wave ratio. In this paper, these three parameters are investigated in order to study and analyze the best value of the produced acoustic energy, the exergetic efficiency and the product of the acoustic energy by the exergetic efficiency of a thermoacoustic engine with a parallel-plate stack. The dimensionless expressions of the thermoacoustic equations are derived and calculated. Then, the Particle Swarm Optimization method (PSO) is introduced and used for the first time in the thermoacoustic research. The use of the PSO method and the optimization of the acoustic energy multiplied by the exergetic efficiency are novel contributions to this domain of research. This paper discusses some significant conclusions which are useful for the design of new thermoacoustic engines.

Optimal Design of Modern Transformerless PV Inverter Topologies

OpenAIRE

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inver...

Aircraft family design using enhanced collaborative optimization

Science.gov (United States)

Roth, Brian Douglas

Significant progress has been made toward the development of multidisciplinary design optimization (MDO) methods that are well-suited to practical large-scale design problems. However, opportunities exist for further progress. This thesis describes the development of enhanced collaborative optimization (ECO), a new decomposition-based MDO method. To support the development effort, the thesis offers a detailed comparison of two existing MDO methods: collaborative optimization (CO) and analytical target cascading (ATC). This aids in clarifying their function and capabilities, and it provides inspiration for the development of ECO. The ECO method offers several significant contributions. First, it enhances communication between disciplinary design teams while retaining the low-order coupling between them. Second, it provides disciplinary design teams with more authority over the design process. Third, it resolves several troubling computational inefficiencies that are associated with CO. As a result, ECO provides significant computational savings (relative to CO) for the test cases and practical design problems described in this thesis. New aircraft development projects seldom focus on a single set of mission requirements. Rather, a family of aircraft is designed, with each family member tailored to a different set of requirements. This thesis illustrates the application of decomposition-based MDO methods to aircraft family design. This represents a new application area, since MDO methods have traditionally been applied to multidisciplinary problems. ECO offers aircraft family design the same benefits that it affords to multidisciplinary design problems. Namely, it simplifies analysis integration, it provides a means to manage problem complexity, and it enables concurrent design of all family members. In support of aircraft family design, this thesis introduces a new wing structural model with sufficient fidelity to capture the tradeoffs associated with component

Superalloy design - A Monte Carlo constrained optimization method

CSIR Research Space (South Africa)

Stander, CM

1996-01-01

Full Text Available optimization method C. M. Stander Division of Materials Science and Technology, CSIR, PO Box 395, Pretoria, Republic of South Africa Received 74 March 1996; accepted 24 June 1996 A method, based on Monte Carlo constrained... successful hit, i.e. when Liow < LMP,,, < Lhiph, and for all the properties, Pj?, < P, < Pi@?. If successful this hit falls within the ROA. Repeat steps 4 and 5 to find at least ten (or more) successful hits with values...

A hybrid finite element analysis and evolutionary computation method for the design of lightweight lattice components with optimized strut diameter

DEFF Research Database (Denmark)

Salonitis, Konstantinos; Chantzis, Dimitrios; Kappatos, Vasileios

2017-01-01

approaches or with the use of topology optimization methodologies. An optimization approach utilizing multipurpose optimization algorithms has not been proposed yet. This paper presents a novel user-friendly method for the design optimization of lattice components towards weight minimization, which combines...... finite element analysis and evolutionary computation. The proposed method utilizes the cell homogenization technique in order to reduce the computational cost of the finite element analysis and a genetic algorithm in order to search for the most lightweight lattice configuration. A bracket consisting...

Simple heuristics: A bridge between manual core design and automated optimization methods

International Nuclear Information System (INIS)

White, J.R.; Delmolino, P.M.

1993-01-01

The primary function of RESCUE is to serve as an aid in the analysis and identification of feasible loading patterns for LWR reload cores. The unique feature of RESCUE is that its physics model is based on some recent advances in generalized perturbation theory (GPT) methods. The high order GPT techniques offer the accuracy, computational efficiency, and flexibility needed for the implementation of a full range of capabilities within a set of compatible interactive (manual and semi-automated) and automated design tools. The basic design philosophy and current features within RESCUE are reviewed, and the new semi-automated capability is highlighted. The online advisor facility appears quite promising and it provides a natural bridge between the traditional trial-and-error manual process and the recent progress towards fully automated optimization sequences. (orig.)

A flexible layout design method for passive micromixers.

Science.gov (United States)

Deng, Yongbo; Liu, Zhenyu; Zhang, Ping; Liu, Yongshun; Gao, Qingyong; Wu, Yihui

2012-10-01

This paper discusses a flexible layout design method of passive micromixers based on the topology optimization of fluidic flows. Being different from the trial and error method, this method obtains the detailed layout of a passive micromixer according to the desired mixing performance by solving a topology optimization problem. Therefore, the dependence on the experience of the designer is weaken, when this method is used to design a passive micromixer with acceptable mixing performance. Several design disciplines for the passive micromixers are considered to demonstrate the flexibility of the layout design method for passive micromixers. These design disciplines include the approximation of the real 3D micromixer, the manufacturing feasibility, the spacial periodic design, and effects of the Péclet number and Reynolds number on the designs obtained by this layout design method. The capability of this design method is validated by several comparisons performed between the obtained layouts and the optimized designs in the recently published literatures, where the values of the mixing measurement is improved up to 40.4% for one cycle of the micromixer.

Expert systems and their use in augmenting design optimization

Science.gov (United States)

Kidwell, G. H.; Eskey, M. A.

1985-01-01

The challenging requirements that are evolving for future aircraft demand that each design be optimally integrated, for the penalties imposed by nonoptimal performance are significant. Classic numerical optimization algorithms have been and will continue to be important tools for aircraft designers. These methods are, however, limited to certain categories of aircraft design variables, leaving the remainder to be determined by the user. A method that makes use of knowledge-based expert systems offers the potential for aiding the conceptual design process in a way that is similar to that of numerical optimization, except that it would address discrete, discontinuous, abstract, or any other unoptimized aspect of vehicle design and integration. Other unique capabilities such as automatic discovery and learning in design may also be achievable in the near term. This paper discusses current practice in conceptual aircraft design and knowledge-based systems, and how knowledge-based systems can be used in conceptual design.

SOLVING ENGINEERING OPTIMIZATION PROBLEMS WITH THE SWARM INTELLIGENCE METHODS

Directory of Open Access Journals (Sweden)

V. Panteleev Andrei

2017-01-01

Full Text Available An important stage in problem solving process for aerospace and aerostructures designing is calculating their main charac- teristics optimization. The results of the four constrained optimization problems related to the design of various technical systems: such as determining the best parameters of welded beams, pressure vessel, gear, spring are presented. The purpose of each task is to minimize the cost and weight of the construction. The object functions in optimization practical problem are nonlinear functions with a lot of variables and a complex layer surface indentations. That is why using classical approach for extremum seeking is not efficient. Here comes the necessity of using such methods of optimization that allow to find a near optimal solution in acceptable amount of time with the minimum waste of computer power. Such methods include the methods of Swarm Intelligence: spiral dy- namics algorithm, stochastic diffusion search, hybrid seeker optimization algorithm. The Swarm Intelligence methods are designed in such a way that a swarm consisting of agents carries out the search for extremum. In search for the point of extremum, the parti- cles exchange information and consider their experience as well as the experience of population leader and the neighbors in some area. To solve the listed problems there has been designed a program complex, which efficiency is illustrated by the solutions of four applied problems. Each of the considered applied optimization problems is solved with all the three chosen methods. The ob- tained numerical results can be compared with the ones found in a swarm with a particle method. The author gives recommenda- tions on how to choose methods parameters and penalty function value, which consider inequality constraints.

Topology optimization based design of unilateral NMR for generating a remote homogeneous field.

Science.gov (United States)

Wang, Qi; Gao, Renjing; Liu, Shutian

2017-06-01

This paper presents a topology optimization based design method for the design of unilateral nuclear magnetic resonance (NMR), with which a remote homogeneous field can be obtained. The topology optimization is actualized by seeking out the optimal layout of ferromagnetic materials within a given design domain. The design objective is defined as generating a sensitive magnetic field with optimal homogeneity and maximal field strength within a required region of interest (ROI). The sensitivity of the objective function with respect to the design variables is derived and the method for solving the optimization problem is presented. A design example is provided to illustrate the utility of the design method, specifically the ability to improve the quality of the magnetic field over the required ROI by determining the optimal structural topology for the ferromagnetic poles. Both in simulations and experiments, the sensitive region of the magnetic field achieves about 2 times larger than that of the reference design, validating validates the feasibility of the design method. Copyright © 2017. Published by Elsevier Inc.

A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments

KAUST Repository

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

KAUST Repository

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.

A novel experimental design method to optimize hydrophilic matrix formulations with drug release profiles and mechanical properties.

Science.gov (United States)

Choi, Du Hyung; Lim, Jun Yeul; Shin, Sangmun; Choi, Won Jun; Jeong, Seong Hoon; Lee, Sangkil

2014-10-01

To investigate the effects of hydrophilic polymers on the matrix system, an experimental design method was developed to integrate response surface methodology and the time series modeling. Moreover, the relationships among polymers on the matrix system were studied with the evaluation of physical properties including water uptake, mass loss, diffusion, and gelling index. A mixture simplex lattice design was proposed while considering eight input control factors: Polyethylene glycol 6000 (x1 ), polyethylene oxide (PEO) N-10 (x2 ), PEO 301 (x3 ), PEO coagulant (x4 ), PEO 303 (x5 ), hydroxypropyl methylcellulose (HPMC) 100SR (x6 ), HPMC 4000SR (x7 ), and HPMC 10(5) SR (x8 ). With the modeling, optimal formulations were obtained depending on the four types of targets. The optimal formulations showed the four significant factors (x1 , x2 , x3 , and x8 ) and other four input factors (x4 , x5 , x6 , and x7 ) were not significant based on drug release profiles. Moreover, the optimization results were analyzed with estimated values, targets values, absolute biases, and relative biases based on observed times for the drug release rates with four different targets. The result showed that optimal solutions and target values had consistent patterns with small biases. On the basis of the physical properties of the optimal solutions, the type and ratio of the hydrophilic polymer and the relationships between polymers significantly influenced the physical properties of the system and drug release. This experimental design method is very useful in formulating a matrix system with optimal drug release. Moreover, it can distinctly confirm the relationships between excipients and the effects on the system with extensive and intensive evaluations. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

A method for optimizing the performance of buildings

Energy Technology Data Exchange (ETDEWEB)

Pedersen, Frank

2006-07-01

This thesis describes a method for optimizing the performance of buildings. Design decisions made in early stages of the building design process have a significant impact on the performance of buildings, for instance, the performance with respect to the energy consumption, economical aspects, and the indoor environment. The method is intended for supporting design decisions for buildings, by combining methods for calculating the performance of buildings with numerical optimization methods. The method is able to find optimum values of decision variables representing different features of the building, such as its shape, the amount and type of windows used, and the amount of insulation used in the building envelope. The parties who influence design decisions for buildings, such as building owners, building users, architects, consulting engineers, contractors, etc., often have different and to some extent conflicting requirements to buildings. For instance, the building owner may be more concerned about the cost of constructing the building, rather than the quality of the indoor climate, which is more likely to be a concern of the building user. In order to support the different types of requirements made by decision-makers for buildings, an optimization problem is formulated, intended for representing a wide range of design decision problems for buildings. The problem formulation involves so-called performance measures, which can be calculated with simulation software for buildings. For instance, the annual amount of energy required by the building, the cost of constructing the building, and the annual number of hours where overheating occurs, can be used as performance measures. The optimization problem enables the decision-makers to specify many different requirements to the decision variables, as well as to the performance of the building. Performance measures can for instance be required to assume their minimum or maximum value, they can be subjected to upper or

Optimized Design of Spacer in Electrodialyzer Using CFD Simulation Method

Science.gov (United States)

Jia, Yuxiang; Yan, Chunsheng; Chen, Lijun; Hu, Yangdong

2018-06-01

In this study, the effects of length-width ratio and diversion trench of the spacer on the fluid flow behavior in an electrodialyzer have been investigated through CFD simulation method. The relevant information, including the pressure drop, velocity vector distribution and shear stress distribution, demonstrates the importance of optimized design of the spacer in an electrodialysis process. The results show width of the diversion trench has a great effect on the fluid flow compared with length. Increase of the diversion trench width could strength the fluid flow, but also increase the pressure drop. Secondly, the dead zone of the fluid flow decreases with increase of length-width ratio of the spacer, but the pressure drop increases with the increase of length-width ratio of the spacer. So the appropriate length-width ratio of the space should be moderate.

Topology Optimization - Engineering Contribution to Architectural Design

Science.gov (United States)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

The idea of the topology optimization is to find within a considered design domain the distribution of material that is optimal in some sense. Material, during optimization process, is redistributed and parts that are not necessary from objective point of view are removed. The result is a solid/void structure, for which an objective function is minimized. This paper presents an application of topology optimization to multi-material structures. The design domain defined by shape of a structure is divided into sub-regions, for which different materials are assigned. During design process material is relocated, but only within selected region. The proposed idea has been inspired by architectural designs like multi-material facades of buildings. The effectiveness of topology optimization is determined by proper choice of numerical optimization algorithm. This paper utilises very efficient heuristic method called Cellular Automata. Cellular Automata are mathematical, discrete idealization of a physical systems. Engineering implementation of Cellular Automata requires decomposition of the design domain into a uniform lattice of cells. It is assumed, that the interaction between cells takes place only within the neighbouring cells. The interaction is governed by simple, local update rules, which are based on heuristics or physical laws. The numerical studies show, that this method can be attractive alternative to traditional gradient-based algorithms. The proposed approach is evaluated by selected numerical examples of multi-material bridge structures, for which various material configurations are examined. The numerical studies demonstrated a significant influence the material sub-regions location on the final topologies. The influence of assumed volume fraction on final topologies for multi-material structures is also observed and discussed. The results of numerical calculations show, that this approach produces different results as compared with classical one

Multiobjective hyper heuristic scheme for system design and optimization

Science.gov (United States)

Rafique, Amer Farhan

2012-11-01

As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.

Optimization design and application of composite ultrasonic extraction method for effective constituents of green tea

Directory of Open Access Journals (Sweden)

Cheng-Chi Wang

2015-12-01

Full Text Available A composite ultrasonic process is used to extract five constituent components of green tea, namely caffeine, catechin, epigallocatechin gallate, epicatechin, and chlorogenic acid. The optimal parameters of the extraction process are determined using the robust Taguchi design method. The extracted products are analyzed using gas chromatography and high-performance liquid chromatography. The experimental results confirm the effectiveness of the proposed ultrasonic technique in extracting the components of interest. Moreover, it is shown that the optimal extraction parameters depend on the particular component. In general, the present findings provide a useful reference for further research on the processing of green tea.

Optimization of reload core design for PWR

International Nuclear Information System (INIS)

Shen Wei; Xie Zhongsheng; Yin Banghua

1995-01-01

A direct efficient optimization technique has been effected for automatically optimizing the reload of PWR. The objective functions include: maximization of end-of-cycle (EOC) reactivity and maximization of average discharge burnup. The fuel loading optimization and burnable poison (BP) optimization are separated into two stages by using Haling principle. In the first stage, the optimum fuel reloading pattern without BP is determined by the linear programming method using enrichments as control variable, while in the second stage the optimum BP allocation is determined by the flexible tolerance method using the number of BP rods as control variable. A practical and efficient PWR reloading optimization program based on above theory has been encoded and successfully applied to Qinshan Nuclear Power Plant (QNP) cycle 2 reloading design

Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER

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Jiaxin Lu

2017-10-01

Full Text Available Implementation of hybrid energy system (HES is generally considered as a promising way to satisfy the electrification requirements for remote areas. In the present study, a novel decision making methodology is proposed to identify the best compromise configuration of HES from a set of feasible combinations obtained from HOMER. For this purpose, a multi-objective function, which comprises four crucial and representative indices, is formulated by applying the weighted sum method. The entropy weight method is employed as a quantitative methodology for weighting factors calculation to enhance the objectivity of decision-making. Moreover, the optimal design of a stand-alone PV/wind/battery/diesel HES in Yongxing Island, China, is conducted as a case study to validate the effectiveness of the proposed method. Both the simulation and optimization results indicate that, the optimization method is able to identify the best trade-off configuration among system reliability, economy, practicability and environmental sustainability. Several useful conclusions are given by analyzing the operation of the best configuration.

Truss Structure Optimization with Subset Simulation and Augmented Lagrangian Multiplier Method

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Feng Du

2017-11-01

Full Text Available This paper presents a global optimization method for structural design optimization, which integrates subset simulation optimization (SSO and the dynamic augmented Lagrangian multiplier method (DALMM. The proposed method formulates the structural design optimization as a series of unconstrained optimization sub-problems using DALMM and makes use of SSO to find the global optimum. The combined strategy guarantees that the proposed method can automatically detect active constraints and provide global optimal solutions with finite penalty parameters. The accuracy and robustness of the proposed method are demonstrated by four classical truss sizing problems. The results are compared with those reported in the literature, and show a remarkable statistical performance based on 30 independent runs.

Optimal Design of Gravitational Sewer Networks with General Cellular Automata

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Mohammad Hadi Afshar

2014-05-01

Full Text Available In this paper, a Cellular Automata method is applied for the optimal design of sewer networks. The solution of sewer network optimization problems requires the determination of pipe diameters and average pipe cover depths, minimizing the total cost of the sewer network subject to operational constraints. In this paper, the network nodes and upstream and downstream pipe cover depths are considered as CA cells and cell states, respectively, and the links around each cell are taken into account as neighborhood. The proposed method is a general and flexible method for the optimization of sewer networks as it can be used to optimally design both gravity and pumped network due to the use of pipe nodal cover depths as the decision variables. The proposed method is tested against two  gravitational sewer networks and the  comparison of results with other methods such as  Genetic algorithm, Cellular Automata, Ant Colony Optimization Algorithm and Particle Swarm Optimization show the efficiency and effectiveness of the proposed method.

Preliminary Structural Design Using Topology Optimization with a Comparison of Results from Gradient and Genetic Algorithm Methods

Science.gov (United States)

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.

Fast Bayesian optimal experimental design and its applications

KAUST Repository

Long, Quan

2015-01-01

We summarize our Laplace method and multilevel method of accelerating the computation of the expected information gain in a Bayesian Optimal Experimental Design (OED). Laplace method is a widely-used method to approximate an integration

Comparative study for the design of optimal composite pressure vessels

International Nuclear Information System (INIS)

Butt, A.M.; Haq, S.W.U.

2009-01-01

Composite pressure vessels require special design attention to the dome region because of the varying wind angles generated using the filament winding process. Geometric variations in the dome region cause the fiber to change angels and thickness and hence offer difficulty to acquire a constant stress profile (isotensoid). Therefore a dome contour which allows an isotensoid behavior is the required structure. Two design methods to generate dome profiles for similar dome openings were investigated namely Netting Analysis and Optimal Design method. Both methods assume that loads are carried by the fiber alone (monotropic) ignoring the complete composite behavior. Former method produced a lower dome internal volume and a higher fiber thickness as compared to the later optimal design method when studied against different normalized dome opening radiuses. The optimal dome contour was studied in ANSYS with a trial design. The dome was considered to have transversely isotropic property with a dome contour based on monotropic model. While investigating the dome with non linear large displacement finite element analysis, the dome still exhibited isotensoid behavior with transverse isotropic material assignment. Elliptic integrals were used to generate the optimal dome contours and hence elliptic dome contours were formed which were isotensoid in nature with complete composite representation. (author)

A procedure for multi-objective optimization of tire design parameters

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Nikola Korunović

2015-04-01

Full Text Available The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zones inside the tire. It consists of four main stages: pre-analysis, design of experiment, mathematical modeling and multi-objective optimization. Advantage of the proposed procedure is reflected in the fact that multi-objective optimization is based on the Pareto concept, which enables design engineers to obtain a complete set of optimization solutions and choose a suitable tire design. Furthermore, modeling of the relationships between tire design parameters and objective functions based on multiple regression analysis minimizes computational and modeling effort. The adequacy of the proposed tire design multi-objective optimization procedure has been validated by performing experimental trials based on finite element method.

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

Science.gov (United States)

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.

Optimal Design of Modern Transformerless PV Inverter Topologies

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inverter design variables are derived for each PV inverter topology and installation site. The H5, H6, neutral point...... clamped, active-neutral point clamped and conergy-NPC PV inverters designed using the proposed optimization process feature lower levelized cost of generated electricity and lifetime cost, longer mean time between failures and inject more PV-generated energy into the electric grid than their nonoptimized......The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during...

Technical Training: EMAG-2005 - Electromagnetic Design and Mathematical Optimization Methods in Magnet Technology

CERN Multimedia

Monique Duval

2005-01-01

CERN Technical Training 2005: Learning for the LHC! CERN Technical Training, in collaboration with the AT-MEL-EM section, is organising a new course series in the framework of the 2005 CERN Technical Training programme: EMAG-2005 - Electromagnetic Design and Mathematical Optimization Methods in Magnet Technology, composed of three-hour lectures in the morning and topical seminars in the afternoon. The EMAG-2005 course series will run at CERN from Monday April 4 until Thursday April 14 (no lectures on Friday 8). The course series, in English, will focus on the foundations of electromagnetism and the design of accelerator magnets, both normal conducting and superconducting, employing analytical and numerical field computations. Examples of the LHC magnet design using the CERN field computation program ROXIE will be presented. However, EMAG-2005 is not a ROXIE user course: it is rather a course for users or potential users of numerical field computation software, and for magnet designers. The course will be o...

Incorporating Servqual-QFD with Taguchi Design for optimizing service quality design

Science.gov (United States)

Arbi Hadiyat, M.

2018-03-01

Deploying good service design in service companies has been updated issue in improving customer satisfaction, especially based on the level of service quality measured by Parasuraman’s SERVQUAL. Many researchers have been proposing methods in designing the service, and some of them are based on engineering viewpoint, especially by implementing the QFD method or even using robust Taguchi method. The QFD method would found the qualitative solution by generating the “how’s”, while Taguchi method gives more quantitative calculation in optimizing best solution. However, incorporating both QFD and Taguchi has been done in this paper and yields better design process. The purposes of this research is to evaluate the incorporated methods by implemented it to a case study, then analyze the result and see the robustness of those methods to customer perception of service quality. Started by measuring service attributes using SERVQUAL and find the improvement with QFD, the deployment of QFD solution then generated by defining Taguchi factors levels and calculating the Signal-to-noise ratio in its orthogonal array, and optimized Taguchi response then found. A case study was given for designing service in local bank. Afterward, the service design obtained from previous analysis was then evaluated and shows that it was still meet the customer satisfaction. Incorporating QFD and Taguchi has performed well and can be adopted and developed for another research for evaluating the robustness of result.

The Potential Role of Cache Mechanism for Complicated Design Optimization

International Nuclear Information System (INIS)

Noriyasu, Hirokawa; Fujita, Kikuo

2002-01-01

This paper discusses the potential role of cache mechanism for complicated design optimization While design optimization is an application of mathematical programming techniques to engineering design problems over numerical computation, its progress has been coevolutionary. The trend in such progress indicates that more complicated applications become the next target of design optimization beyond growth of computational resources. As the progress in the past two decades had required response surface techniques, decomposition techniques, etc., any new framework must be introduced for the future of design optimization methods. This paper proposes a possibility of what we call cache mechanism for mediating the coming challenge and briefly demonstrates some promises in the idea of Voronoi diagram based cumulative approximation as an example of its implementation, development of strict robust design, extension of design optimization for product variety

Classical and modern optimization methods in minimum weight design of elastic rotating disk with variable thickness and density

International Nuclear Information System (INIS)

Jafari, S.; Hojjati, M.H.; Fathi, A.

2012-01-01

Rotating disks work mostly at high angular velocity and this results a large centrifugal force and consequently induce large stresses and deformations. Minimizing weight of such disks yields to benefits such as low dead weights and lower costs. This paper aims at finding an optimal disk profiles for minimum weight design using the Karush-Kuhn-Tucker method (KKT) as a classical optimization method, simulated annealing (SA) and particle swarm optimization (PSO) as two modern optimization techniques. Some semi-analytical solutions for the elastic stress distribution in a rotating annular disk with uniform and variable thickness and density proposed by the authors in the previous works have been used. The von Mises failure criterion of optimum disk is used as an inequality constraint to make sure that the rotating disk does not fail. The results show that the minimum weight obtained for all three methods is almost identical. The KKT method gives a profile with slightly less weight (6% less than SA and 1% less than PSO) while the implementation of PSO and SA methods are easier and provide more flexibility compared with those of the KKT method. The effectiveness of the proposed optimization methods is shown. - Highlights: ► Karush-Kuhn-Tucker, simulated annealing and particle swarm methods are used. ► The KKT gives slightly less weight (6% less than SA and 1% less than PSO). ► Implementation of PSO and SA methods are easier and provide more flexibility. ► The effectiveness of the proposed optimization methods is shown.

Classical and modern optimization methods in minimum weight design of elastic rotating disk with variable thickness and density

Energy Technology Data Exchange (ETDEWEB)

Jafari, S. [Faculty of Mechanical Engineering, Babol University of Technology, P.O. Box 484, Babol (Iran, Islamic Republic of); Hojjati, M.H., E-mail: Hojjati@nit.ac.ir [Faculty of Mechanical Engineering, Babol University of Technology, P.O. Box 484, Babol (Iran, Islamic Republic of); Fathi, A. [Faculty of Mechanical Engineering, Babol University of Technology, P.O. Box 484, Babol (Iran, Islamic Republic of)

2012-04-15

Rotating disks work mostly at high angular velocity and this results a large centrifugal force and consequently induce large stresses and deformations. Minimizing weight of such disks yields to benefits such as low dead weights and lower costs. This paper aims at finding an optimal disk profiles for minimum weight design using the Karush-Kuhn-Tucker method (KKT) as a classical optimization method, simulated annealing (SA) and particle swarm optimization (PSO) as two modern optimization techniques. Some semi-analytical solutions for the elastic stress distribution in a rotating annular disk with uniform and variable thickness and density proposed by the authors in the previous works have been used. The von Mises failure criterion of optimum disk is used as an inequality constraint to make sure that the rotating disk does not fail. The results show that the minimum weight obtained for all three methods is almost identical. The KKT method gives a profile with slightly less weight (6% less than SA and 1% less than PSO) while the implementation of PSO and SA methods are easier and provide more flexibility compared with those of the KKT method. The effectiveness of the proposed optimization methods is shown. - Highlights: Black-Right-Pointing-Pointer Karush-Kuhn-Tucker, simulated annealing and particle swarm methods are used. Black-Right-Pointing-Pointer The KKT gives slightly less weight (6% less than SA and 1% less than PSO). Black-Right-Pointing-Pointer Implementation of PSO and SA methods are easier and provide more flexibility. Black-Right-Pointing-Pointer The effectiveness of the proposed optimization methods is shown.

Integrated Reliability-Based Optimal Design of Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Thoft-Christensen, Palle

1987-01-01

In conventional optimal design of structural systems the weight or the initial cost of the structure is usually used as objective function. Further, the constraints require that the stresses and/or strains at some critical points have to be less than some given values. Finally, all variables......-based optimal design is discussed. Next, an optimal inspection and repair strategy for existing structural systems is presented. An optimization problem is formulated , where the objective is to minimize the expected total future cost of inspection and repair subject to the constraint that the reliability...... value. The reliability can be measured from an element and/or a systems point of view. A number of methods to solve reliability-based optimization problems has been suggested, see e.g. Frangopol [I]. Murotsu et al. (2], Thoft-Christensen & Sørensen (3] and Sørensen (4). For structures where...

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.

Review: Optimization methods for groundwater modeling and management

Science.gov (United States)

Yeh, William W.-G.

2015-09-01

Optimization methods have been used in groundwater modeling as well as for the planning and management of groundwater systems. This paper reviews and evaluates the various optimization methods that have been used for solving the inverse problem of parameter identification (estimation), experimental design, and groundwater planning and management. Various model selection criteria are discussed, as well as criteria used for model discrimination. The inverse problem of parameter identification concerns the optimal determination of model parameters using water-level observations. In general, the optimal experimental design seeks to find sampling strategies for the purpose of estimating the unknown model parameters. A typical objective of optimal conjunctive-use planning of surface water and groundwater is to minimize the operational costs of meeting water demand. The optimization methods include mathematical programming techniques such as linear programming, quadratic programming, dynamic programming, stochastic programming, nonlinear programming, and the global search algorithms such as genetic algorithms, simulated annealing, and tabu search. Emphasis is placed on groundwater flow problems as opposed to contaminant transport problems. A typical two-dimensional groundwater flow problem is used to explain the basic formulations and algorithms that have been used to solve the formulated optimization problems.

A Finite Element Removal Method for 3D Topology Optimization

Directory of Open Access Journals (Sweden)

M. Akif Kütük

2013-01-01

Full Text Available Topology optimization provides great convenience to designers during the designing stage in many industrial applications. With this method, designers can obtain a rough model of any part at the beginning of a designing stage by defining loading and boundary conditions. At the same time the optimization can be used for the modification of a product which is being used. Lengthy solution time is a disadvantage of this method. Therefore, the method cannot be widespread. In order to eliminate this disadvantage, an element removal algorithm has been developed for topology optimization. In this study, the element removal algorithm is applied on 3-dimensional parts, and the results are compared with the ones available in the related literature. In addition, the effects of the method on solution times are investigated.

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.

Hybrid PV/diesel solar power system design using multi-level factor analysis optimization

Science.gov (United States)

Drake, Joshua P.

Solar power systems represent a large area of interest across a spectrum of organizations at a global level. It was determined that a clear understanding of current state of the art software and design methods, as well as optimization methods, could be used to improve the design methodology. Solar power design literature was researched for an in depth understanding of solar power system design methods and algorithms. Multiple software packages for the design and optimization of solar power systems were analyzed for a critical understanding of their design workflow. In addition, several methods of optimization were studied, including brute force, Pareto analysis, Monte Carlo, linear and nonlinear programming, and multi-way factor analysis. Factor analysis was selected as the most efficient optimization method for engineering design as it applied to solar power system design. The solar power design algorithms, software work flow analysis, and factor analysis optimization were combined to develop a solar power system design optimization software package called FireDrake. This software was used for the design of multiple solar power systems in conjunction with an energy audit case study performed in seven Tibetan refugee camps located in Mainpat, India. A report of solar system designs for the camps, as well as a proposed schedule for future installations was generated. It was determined that there were several improvements that could be made to the state of the art in modern solar power system design, though the complexity of current applications is significant.

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

Optimization Method of a Low Cost, High Performance Ceramic Proppant by Orthogonal Experimental Design

Science.gov (United States)

Zhou, Y.; Tian, Y. M.; Wang, K. Y.; Li, G.; Zou, X. W.; Chai, Y. S.

2017-09-01

This study focused on optimization method of a ceramic proppant material with both low cost and high performance that met the requirements of Chinese Petroleum and Gas Industry Standard (SY/T 5108-2006). The orthogonal experimental design of L9(34) was employed to study the significance sequence of three factors, including weight ratio of white clay to bauxite, dolomite content and sintering temperature. For the crush resistance, both the range analysis and variance analysis reflected the optimally experimental condition was weight ratio of white clay to bauxite=3/7, dolomite content=3 wt.%, temperature=1350°C. For the bulk density, the most important factor was the sintering temperature, followed by the dolomite content, and then the ratio of white clay to bauxite.

Nonlinear Shaping Architecture Designed with Using Evolutionary Structural Optimization Tools

Science.gov (United States)

Januszkiewicz, Krystyna; Banachowicz, Marta

2017-10-01

The paper explores the possibilities of using Structural Optimization Tools (ESO) digital tools in an integrated structural and architectural design in response to the current needs geared towards sustainability, combining ecological and economic efficiency. The first part of the paper defines the Evolutionary Structural Optimization tools, which were developed specifically for engineering purposes using finite element analysis as a framework. The development of ESO has led to several incarnations, which are all briefly discussed (Additive ESO, Bi-directional ESO, Extended ESO). The second part presents result of using these tools in structural and architectural design. Actual building projects which involve optimization as a part of the original design process will be presented (Crematorium in Kakamigahara Gifu, Japan, 2006 SANAA“s Learning Centre, EPFL in Lausanne, Switzerland 2008 among others). The conclusion emphasizes that the structural engineering and architectural design mean directing attention to the solutions which are used by Nature, designing works optimally shaped and forming their own environments. Architectural forms never constitute the optimum shape derived through a form-finding process driven only by structural optimization, but rather embody and integrate a multitude of parameters. It might be assumed that there is a similarity between these processes in nature and the presented design methods. Contemporary digital methods make the simulation of such processes possible, and thus enable us to refer back to the empirical methods of previous generations.

Cost-Optimal Analysis for Nearly Zero Energy Buildings Design and Optimization: A Critical Review

Directory of Open Access Journals (Sweden)

Maria Ferrara

2018-06-01

Full Text Available Since the introduction of the recast of the EPBD European Directive 2010/31/EU, many studies on the cost-effective feasibility of nearly zero-energy buildings (NZEBs were carried out either by academic research bodies and by national bodies. In particular, the introduction of the cost-optimal methodology has given a strong impulse to research in this field. This paper presents a comprehensive and significant review on scientific works based on the application of cost-optimal analysis applications in Europe since the EPBD recast entered into force, pointing out the differences in the analyzed studies and comparing their outcomes before the new recast of EPBD enters into force in 2018. The analysis is conducted with special regard to the methods used for the energy performance assessment, the global cost calculation, and for the selection of the energy efficiency measures leading to design optimization. A critical discussion about the assumptions on which the studies are based and the resulting gaps between the resulting cost-optimal performance and the zero energy target is provided together with a summary of the resulting cost-optimal set of technologies to be used for cost-optimal NZEB design in different contexts. It is shown that the cost-optimal approach results as an effective method for delineating the future of NZEB design throughout Europe while emerging criticalities and open research issues are presented.

Design optimization on the drive train of a light-weight robotic arm

DEFF Research Database (Denmark)

Zhou, Lelai; Bai, Shaoping; Hansen, Michael Rygaard

2011-01-01

A drive train optimization method for design of light-weight robots is proposed. Optimal selections of motors and gearboxes from a limited catalog of commercially available components are done simultaneously for all joints of a robotic arm. Characteristics of the motor and gearbox, including gear...... ratio, gear inertia, motor inertia, and gear efficiency, are considered in the drive train modeling. A co-simulation method is developed for dynamic simulation of the arm. A design example is included to demonstrate the proposed design optimization method....

Application of Orthogonal Design to Optimize Extraction of ...

African Journals Online (AJOL)

Purpose: To optimize the extraction technology of polysaccharides from Cynomorium songaricum Rupr by ultrasonic-assisted extraction (UAE). Methods: Four parameters including ultrasonic power, ratio of raw material to water, extraction temperature, and extraction time were optimized by orthogonal design. The effects of ...

Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight

Directory of Open Access Journals (Sweden)

Zhu Hao

2015-06-01

Full Text Available In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity analysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization (DDO and uncertainty-based design optimization (UDO are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation (KMCS and Kriging-based Taylor series approximation (KTSA, are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.

Design and multi-physics optimization of rotary MRF brakes

Science.gov (United States)

Topcu, Okan; Taşcıoğlu, Yiğit; Konukseven, Erhan İlhan

2018-03-01

Particle swarm optimization (PSO) is a popular method to solve the optimization problems. However, calculations for each particle will be excessive when the number of particles and complexity of the problem increases. As a result, the execution speed will be too slow to achieve the optimized solution. Thus, this paper proposes an automated design and optimization method for rotary MRF brakes and similar multi-physics problems. A modified PSO algorithm is developed for solving multi-physics engineering optimization problems. The difference between the proposed method and the conventional PSO is to split up the original single population into several subpopulations according to the division of labor. The distribution of tasks and the transfer of information to the next party have been inspired by behaviors of a hunting party. Simulation results show that the proposed modified PSO algorithm can overcome the problem of heavy computational burden of multi-physics problems while improving the accuracy. Wire type, MR fluid type, magnetic core material, and ideal current inputs have been determined by the optimization process. To the best of the authors' knowledge, this multi-physics approach is novel for optimizing rotary MRF brakes and the developed PSO algorithm is capable of solving other multi-physics engineering optimization problems. The proposed method has showed both better performance compared to the conventional PSO and also has provided small, lightweight, high impedance rotary MRF brake designs.

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...

Topology optimization and lattice Boltzmann methods

DEFF Research Database (Denmark)

Nørgaard, Sebastian Arlund

This thesis demonstrates the application of the lattice Boltzmann method for topology optimization problems. Specifically, the focus is on problems in which time-dependent flow dynamics have significant impact on the performance of the devices to be optimized. The thesis introduces new topology...... a discrete adjoint approach. To handle the complexity of the discrete adjoint approach more easily, a method for computing it based on automatic differentiation is introduced, which can be adapted to any lattice Boltzmann type method. For example, while it is derived in the context of an isothermal lattice...... Boltzmann model, it is shown that the method can be easily extended to a thermal model as well. Finally, the predicted behavior of an optimized design is compared to the equiva-lent prediction from a commercial finite element solver. It is found that the weakly compressible nature of the lattice Boltzmann...

Optimal design approach for heating irregular-shaped objects in three-dimensional radiant furnaces using a hybrid genetic algorithm-artificial neural network method

Science.gov (United States)

Darvishvand, Leila; Kamkari, Babak; Kowsary, Farshad

2018-03-01

In this article, a new hybrid method based on the combination of the genetic algorithm (GA) and artificial neural network (ANN) is developed to optimize the design of three-dimensional (3-D) radiant furnaces. A 3-D irregular shape design body (DB) heated inside a 3-D radiant furnace is considered as a case study. The uniform thermal conditions on the DB surfaces are obtained by minimizing an objective function. An ANN is developed to predict the objective function value which is trained through the data produced by applying the Monte Carlo method. The trained ANN is used in conjunction with the GA to find the optimal design variables. The results show that the computational time using the GA-ANN approach is significantly less than that of the conventional method. It is concluded that the integration of the ANN with GA is an efficient technique for optimization of the radiant furnaces.

Optimal Halbach permanent magnet designs for maximally pulling and pushing nanoparticles

Energy Technology Data Exchange (ETDEWEB)

Sarwar, A., E-mail: azeem@umd.edu [Fischell Department of Bioengineering, College Park, MD (United States); University of Maryland at College Park (United States); Nemirovski, A. [H. Milton Stewart School of Industrial and Systems Engineering (ISyE), Georgia Institute of Technology (United States); Shapiro, B. [Fischell Department of Bioengineering, College Park, MD (United States); Institute for Systems Research (United States); University of Maryland at College Park (United States)

2012-03-15

Optimization methods are presented to design Halbach arrays to maximize the forces applied on magnetic nanoparticles at deep tissue locations. In magnetic drug targeting, where magnets are used to focus therapeutic nanoparticles to disease locations, the sharp fall off of magnetic fields and forces with distances from magnets has limited the depth of targeting. Creating stronger forces at a depth by optimally designed Halbach arrays would allow treatment of a wider class of patients, e.g. patients with deeper tumors. The presented optimization methods are based on semi-definite quadratic programming, yield provably globally optimal Halbach designs in 2 and 3-dimensions, for maximal pull or push magnetic forces (stronger pull forces can collect nanoparticles against blood forces in deeper vessels; push forces can be used to inject particles into precise locations, e.g. into the inner ear). These Halbach designs, here tested in simulations of Maxwell's equations, significantly outperform benchmark magnets of the same size and strength. For example, a 3-dimensional 36 element 2000 cm{sup 3} volume optimal Halbach design yields a 5 Multiplication-Sign greater force at a 10 cm depth compared to a uniformly magnetized magnet of the same size and strength. The designed arrays should be feasible to construct, as they have a similar strength ({<=}1 T), size ({<=}2000 cm{sup 3}), and number of elements ({<=}36) as previously demonstrated arrays, and retain good performance for reasonable manufacturing errors (element magnetization direction errors {<=}5 Degree-Sign), thus yielding practical designs to improve magnetic drug targeting treatment depths. - Highlights: Black-Right-Pointing-Pointer Optimization methods presented to design Halbach arrays for drug targeting. Black-Right-Pointing-Pointer The goal is to maximize forces on magnetic nanoparticles at deep tissue locations. Black-Right-Pointing-Pointer The presented methods yield provably globally optimal Halbach

Optimal Halbach permanent magnet designs for maximally pulling and pushing nanoparticles

International Nuclear Information System (INIS)

Sarwar, A.; Nemirovski, A.; Shapiro, B.

2012-01-01

Optimization methods are presented to design Halbach arrays to maximize the forces applied on magnetic nanoparticles at deep tissue locations. In magnetic drug targeting, where magnets are used to focus therapeutic nanoparticles to disease locations, the sharp fall off of magnetic fields and forces with distances from magnets has limited the depth of targeting. Creating stronger forces at a depth by optimally designed Halbach arrays would allow treatment of a wider class of patients, e.g. patients with deeper tumors. The presented optimization methods are based on semi-definite quadratic programming, yield provably globally optimal Halbach designs in 2 and 3-dimensions, for maximal pull or push magnetic forces (stronger pull forces can collect nanoparticles against blood forces in deeper vessels; push forces can be used to inject particles into precise locations, e.g. into the inner ear). These Halbach designs, here tested in simulations of Maxwell's equations, significantly outperform benchmark magnets of the same size and strength. For example, a 3-dimensional 36 element 2000 cm 3 volume optimal Halbach design yields a 5× greater force at a 10 cm depth compared to a uniformly magnetized magnet of the same size and strength. The designed arrays should be feasible to construct, as they have a similar strength (≤1 T), size (≤2000 cm 3 ), and number of elements (≤36) as previously demonstrated arrays, and retain good performance for reasonable manufacturing errors (element magnetization direction errors ≤5°), thus yielding practical designs to improve magnetic drug targeting treatment depths. - Highlights: ► Optimization methods presented to design Halbach arrays for drug targeting. ► The goal is to maximize forces on magnetic nanoparticles at deep tissue locations. ► The presented methods yield provably globally optimal Halbach designs in 2D and 3D. ► These designs significantly outperform benchmark magnets of the same size and strength. ► These

Optimization of the Conical Angle Design in Conical Implant-Abutment Connections: A Pilot Study Based on the Finite Element Method.

Science.gov (United States)

Yao, Kuang-Ta; Chen, Chen-Sheng; Cheng, Cheng-Kung; Fang, Hsu-Wei; Huang, Chang-Hung; Kao, Hung-Chan; Hsu, Ming-Lun

2018-02-01

Conical implant-abutment connections are popular for their excellent connection stability, which is attributable to frictional resistance in the connection. However, conical angles, the inherent design parameter of conical connections, exert opposing effects on 2 influencing factors of the connection stability: frictional resistance and abutment rigidity. This pilot study employed an optimization approach through the finite element method to obtain an optimal conical angle for the highest connection stability in an Ankylos-based conical connection system. A nonlinear 3-dimensional finite element parametric model was developed according to the geometry of the Ankylos system (conical half angle = 5.7°) by using the ANSYS 11.0 software. Optimization algorithms were conducted to obtain the optimal conical half angle and achieve the minimal value of maximum von Mises stress in the abutment, which represents the highest connection stability. The optimal conical half angle obtained was 10.1°. Compared with the original design (5.7°), the optimal design demonstrated an increased rigidity of abutment (36.4%) and implant (25.5%), a decreased microgap at the implant-abutment interface (62.3%), a decreased contact pressure (37.9%) with a more uniform stress distribution in the connection, and a decreased stress in the cortical bone (4.5%). In conclusion, the methodology of design optimization to determine the optimal conical angle of the Ankylos-based system is feasible. Because of the heterogeneity of different systems, more studies should be conducted to define the optimal conical angle in various conical connection designs.

Stiffness design of geometrically nonlinear structures using topology optimization

DEFF Research Database (Denmark)

Buhl, Thomas; Pedersen, Claus B. Wittendorf; Sigmund, Ole

2000-01-01

of the objective functions are found with the adjoint method and the optimization problem is solved using the Method of Moving Asymptotes. A filtering scheme is used to obtain checkerboard-free and mesh-independent designs and a continuation approach improves convergence to efficient designs. Different objective......The paper deals with topology optimization of structures undergoing large deformations. The geometrically nonlinear behaviour of the structures are modelled using a total Lagrangian finite element formulation and the equilibrium is found using a Newton-Raphson iterative scheme. The sensitivities...... functions are tested. Minimizing compliance for a fixed load results in degenerated topologies which are very inefficient for smaller or larger loads. The problem of obtaining degenerated "optimal" topologies which only can support the design load is even more pronounced than for structures with linear...

Hybrid Design Optimization of High Voltage Pulse Transformers for Klystron Modulators

CERN Document Server

Sylvain, Candolfi; Davide, Aguglia; Jerome, Cros

2015-01-01

This paper presents a hybrid optimization methodology for the design of high voltage pulse transformers used in klystron modulators. The optimization process is using simplified 2D FEA design models of the 3D transformer structure. Each intermediate optimal solution is evaluated by 3D FEA and correction coefficients of the 2D FEA models are derived. A new optimization process using 2D FEA models is then performed. The convergence of this hybrid optimal design methodology is obtained with a limited number of time consuming 3D FEA simulations. The method is applied to the optimal design of a monolithic high voltage pulse transformer for the CLIC klystron modulator.

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)

Truss topology optimization with discrete design variables by outer approximation

DEFF Research Database (Denmark)

Stolpe, Mathias

2015-01-01

Several variants of an outer approximation method are proposed to solve truss topology optimization problems with discrete design variables to proven global optimality. The objective is to minimize the volume of the structure while satisfying constraints on the global stiffness of the structure...... for classical outer approximation approaches applied to optimal design problems. A set of two- and three-dimensional benchmark problems are solved and the numerical results suggest that the proposed approaches are competitive with other special-purpose global optimization methods for the considered class...... under the applied loads. We extend the natural problem formulation by adding redundant force variables and force equilibrium constraints. This guarantees that the designs suggested by the relaxed master problems are capable of carrying the applied loads, a property which is generally not satisfied...

Optimization and Inverse Design of Pump Impeller

International Nuclear Information System (INIS)

Miyauchi, S; Matsumoto, H; Sano, M; Kassai, N; Zhu, B; Luo, X; Piao, B

2012-01-01

As for pump impellers, the meridional flow channel and blade-to-blade flow channel, which are relatively independent of each other but greatly affect performance, are designed in parallel. And the optimization design is used for the former and the inverse design is used for the latter. To verify this new design method, a mixed-flow impeller was made. Next, we use Tani's inverse design method for the blade loading of inverse design. It is useful enough to change a deceleration rate freely and greatly. And it can integrally express the rear blade loading of various methods by NACA, Zangeneh and Stratford. We controlled the deceleration rate by shape parameter m, and its value became almost same with Tani's recommended value of the laminar airfoil.

Optimizing an experimental design for an electromagnetic experiment

Science.gov (United States)

Roux, Estelle; Garcia, Xavier

2013-04-01

Most of geophysical studies focus on data acquisition and analysis, but another aspect which is gaining importance is the discussion on acquisition of suitable datasets. This can be done through the design of an optimal experiment. Optimizing an experimental design implies a compromise between maximizing the information we get about the target and reducing the cost of the experiment, considering a wide range of constraints (logistical, financial, experimental …). We are currently developing a method to design an optimal controlled-source electromagnetic (CSEM) experiment to detect a potential CO2 reservoir and monitor this reservoir during and after CO2 injection. Our statistical algorithm combines the use of linearized inverse theory (to evaluate the quality of one given design via the objective function) and stochastic optimization methods like genetic algorithm (to examine a wide range of possible surveys). The particularity of our method is that it uses a multi-objective genetic algorithm that searches for designs that fit several objective functions simultaneously. One main advantage of this kind of technique to design an experiment is that it does not require the acquisition of any data and can thus be easily conducted before any geophysical survey. Our new experimental design algorithm has been tested with a realistic one-dimensional resistivity model of the Earth in the region of study (northern Spain CO2 sequestration test site). We show that a small number of well distributed observations have the potential to resolve the target. This simple test also points out the importance of a well chosen objective function. Finally, in the context of CO2 sequestration that motivates this study, we might be interested in maximizing the information we get about the reservoir layer. In that case, we show how the combination of two different objective functions considerably improve its resolution.

Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools.

Science.gov (United States)

Wöhling, Thomas; Geiges, Andreas; Nowak, Wolfgang

2016-11-01

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data-worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south-western Germany, which has been established to monitor river-groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model-based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy-to-implement tools for an otherwise complex task and (2) yet to consider data-worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types. © 2016, National Ground Water Association.

Iron Pole Shape Optimization of IPM Motors Using an Integrated Method

Directory of Open Access Journals (Sweden)

JABBARI, A.

2010-02-01

Full Text Available An iron pole shape optimization method to reduce cogging torque in Interior Permanent Magnet (IPM motors is developed by using the reduced basis technique coupled by finite element and design of experiments methods. Objective function is defined as the minimum cogging torque. The experimental design of Taguchi method is used to build the approximation model and to perform optimization. This method is demonstrated on the rotor pole shape optimization of a 4-poles/24-slots IPM motor.

Optimal design of tilt carrier frequency computer-generated holograms to measure aspherics.

Science.gov (United States)

Peng, Jiantao; Chen, Zhe; Zhang, Xingxiang; Fu, Tianjiao; Ren, Jianyue

2015-08-20

Computer-generated holograms (CGHs) provide an approach to high-precision metrology of aspherics. A CGH is designed under the trade-off among size, mapping distortion, and line spacing. This paper describes an optimal design method based on the parametric model for tilt carrier frequency CGHs placed outside the interferometer focus points. Under the condition of retaining an admissible size and a tolerable mapping distortion, the optimal design method has two advantages: (1) separating the parasitic diffraction orders to improve the contrast of the interferograms and (2) achieving the largest line spacing to minimize sensitivity to fabrication errors. This optimal design method is applicable to common concave aspherical surfaces and illustrated with CGH design examples.

Design Optimization of Piles for Offshore Wind Turbine Jacket Foundations

DEFF Research Database (Denmark)

Sandal, Kasper; Zania, Varvara

Numerical methods can optimize the pile design. The aim of this study is to automatically design optimal piles for offshore wind turbine jacket foundations (Figure 1). Pile mass is minimized with constraints on axial and lateral capacity. Results indicate that accurate knowledge about soil...

Truss topology optimization with discrete design variables — Guaranteed global optimality and benchmark examples

DEFF Research Database (Denmark)

Achtziger, Wolfgang; Stolpe, Mathias

2007-01-01

this problem is well-studied for continuous bar areas, we consider in this study the case of discrete areas. This problem is of major practical relevance if the truss must be built from pre-produced bars with given areas. As a special case, we consider the design problem for a single available bar area, i.......e., a 0/1 problem. In contrast to the heuristic methods considered in many other approaches, our goal is to compute guaranteed globally optimal structures. This is done by a branch-and-bound method for which convergence can be proven. In this branch-and-bound framework, lower bounds of the optimal......-integer problems. The main intention of this paper is to provide optimal solutions for single and multiple load benchmark examples, which can be used for testing and validating other methods or heuristics for the treatment of this discrete topology design problem....

Constrained Optimization Methods in Health Services Research-An Introduction: Report 1 of the ISPOR Optimization Methods Emerging Good Practices Task Force.

Science.gov (United States)

Crown, William; Buyukkaramikli, Nasuh; Thokala, Praveen; Morton, Alec; Sir, Mustafa Y; Marshall, Deborah A; Tosh, Jon; Padula, William V; Ijzerman, Maarten J; Wong, Peter K; Pasupathy, Kalyan S

2017-03-01

Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

A new optimal seam method for seamless image stitching

Science.gov (United States)

Xue, Jiale; Chen, Shengyong; Cheng, Xu; Han, Ying; Zhao, Meng

2017-07-01

A novel optimal seam method which aims to stitch those images with overlapping area more seamlessly has been propos ed. Considering the traditional gradient domain optimal seam method and fusion algorithm result in bad color difference measurement and taking a long time respectively, the input images would be converted to HSV space and a new energy function is designed to seek optimal stitching path. To smooth the optimal stitching path, a simplified pixel correction and weighted average method are utilized individually. The proposed methods exhibit performance in eliminating the stitching seam compared with the traditional gradient optimal seam and high efficiency with multi-band blending algorithm.

Design Optimization of Irregular Cellular Structure for Additive Manufacturing

Science.gov (United States)

Song, Guo-Hua; Jing, Shi-Kai; Zhao, Fang-Lei; Wang, Ye-Dong; Xing, Hao; Zhou, Jing-Tao

2017-09-01

Irregularcellular structurehas great potential to be considered in light-weight design field. However, the research on optimizing irregular cellular structures has not yet been reporteddue to the difficulties in their modeling technology. Based on the variable density topology optimization theory, an efficient method for optimizing the topology of irregular cellular structures fabricated through additive manufacturing processes is proposed. The proposed method utilizes tangent circles to automatically generate the main outline of irregular cellular structure. The topological layoutof each cellstructure is optimized using the relative density informationobtained from the proposed modified SIMP method. A mapping relationship between cell structure and relative densityelement is builtto determine the diameter of each cell structure. The results show that the irregular cellular structure can be optimized with the proposed method. The results of simulation and experimental test are similar for irregular cellular structure, which indicate that the maximum deformation value obtained using the modified Solid Isotropic Microstructures with Penalization (SIMP) approach is lower 5.4×10-5 mm than that using the SIMP approach under the same under the same external load. The proposed research provides the instruction to design the other irregular cellular structure.

Towards robust optimal design of storm water systems

Science.gov (United States)

Marquez Calvo, Oscar; Solomatine, Dimitri

2015-04-01

In this study the focus is on the design of a storm water or a combined sewer system. Such a system should be capable to handle properly most of the storm to minimize the damages caused by flooding due to the lack of capacity of the system to cope with rain water at peak times. This problem is a multi-objective optimization problem: we have to take into account the minimization of the construction costs, the minimization of damage costs due to flooding, and possibly other criteria. One of the most important factors influencing the design of storm water systems is the expected amount of water to deal with. It is common that this infrastructure is developed with the capacity to cope with events that occur once in, say 10 or 20 years - so-called design rainfall events. However, rainfall is a random variable and such uncertainty typically is not taken explicitly into account in optimization. Rainfall design data is based on historical information of rainfalls, but many times this data is based on unreliable measures; or in not enough historical information; or as we know, the patterns of rainfall are changing regardless of historical information. There are also other sources of uncertainty influencing design, for example, leakages in the pipes and accumulation of sediments in pipes. In the context of storm water or combined sewer systems design or rehabilitation, robust optimization technique should be able to find the best design (or rehabilitation plan) within the available budget but taking into account uncertainty in those variables that were used to design the system. In this work we consider various approaches to robust optimization proposed by various authors (Gabrel, Murat, Thiele 2013; Beyer, Sendhoff 2007) and test a novel method ROPAR (Solomatine 2012) to analyze robustness. References Beyer, H.G., & Sendhoff, B. (2007). Robust optimization - A comprehensive survey. Comput. Methods Appl. Mech. Engrg., 3190-3218. Gabrel, V.; Murat, C., Thiele, A. (2014

Design optimization and uncertainty analysis of SMA morphing structures

International Nuclear Information System (INIS)

Oehler, S D; Hartl, D J; Lopez, R; Malak, R J; Lagoudas, D C

2012-01-01

The continuing implementation of shape memory alloys (SMAs) as lightweight solid-state actuators in morphing structures has now motivated research into finding optimized designs for use in aerospace control systems. This work proposes methods that use iterative analysis techniques to determine optimized designs for morphing aerostructures and consider the impact of uncertainty in model variables on the solution. A combination of commercially available and custom coded tools is utilized. ModelCenter, a suite of optimization algorithms and simulation process management tools, is coupled with the Abaqus finite element analysis suite and a custom SMA constitutive model to assess morphing structure designs in an automated fashion. The chosen case study involves determining the optimized configuration of a morphing aerostructure assembly that includes SMA flexures. This is accomplished by altering design inputs representing the placement of active components to minimize a specified cost function. An uncertainty analysis is also conducted using design of experiment methods to determine the sensitivity of the solution to a set of uncertainty variables. This second study demonstrates the effective use of Monte Carlo techniques to simulate the variance of model variables representing the inherent uncertainty in component fabrication processes. This paper outlines the modeling tools used to execute each case study, details the procedures for constructing the optimization problem and uncertainty analysis, and highlights the results from both studies. (paper)

Rotorcraft Optimization Tools: Incorporating Rotorcraft Design Codes into Multi-Disciplinary Design, Analysis, and Optimization

Science.gov (United States)

Meyn, Larry A.

2018-01-01

One of the goals of NASA's Revolutionary Vertical Lift Technology Project (RVLT) is to provide validated tools for multidisciplinary design, analysis and optimization (MDAO) of vertical lift vehicles. As part of this effort, the software package, RotorCraft Optimization Tools (RCOTOOLS), is being developed to facilitate incorporating key rotorcraft conceptual design codes into optimizations using the OpenMDAO multi-disciplinary optimization framework written in Python. RCOTOOLS, also written in Python, currently supports the incorporation of the NASA Design and Analysis of RotorCraft (NDARC) vehicle sizing tool and the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics II (CAMRAD II) analysis tool into OpenMDAO-driven optimizations. Both of these tools use detailed, file-based inputs and outputs, so RCOTOOLS provides software wrappers to update input files with new design variable values, execute these codes and then extract specific response variable values from the file outputs. These wrappers are designed to be flexible and easy to use. RCOTOOLS also provides several utilities to aid in optimization model development, including Graphical User Interface (GUI) tools for browsing input and output files in order to identify text strings that are used to identify specific variables as optimization input and response variables. This paper provides an overview of RCOTOOLS and its use

Optimal design method to minimize users' thinking mapping load in human-machine interactions.

Science.gov (United States)

Huang, Yanqun; Li, Xu; Zhang, Jie

2015-01-01

The discrepancy between human cognition and machine requirements/behaviors usually results in serious mental thinking mapping loads or even disasters in product operating. It is important to help people avoid human-machine interaction confusions and difficulties in today's mental work mastered society. Improving the usability of a product and minimizing user's thinking mapping and interpreting load in human-machine interactions. An optimal human-machine interface design method is introduced, which is based on the purpose of minimizing the mental load in thinking mapping process between users' intentions and affordance of product interface states. By analyzing the users' thinking mapping problem, an operating action model is constructed. According to human natural instincts and acquired knowledge, an expected ideal design with minimized thinking loads is uniquely determined at first. Then, creative alternatives, in terms of the way human obtains operational information, are provided as digital interface states datasets. In the last, using the cluster analysis method, an optimum solution is picked out from alternatives, by calculating the distances between two datasets. Considering multiple factors to minimize users' thinking mapping loads, a solution nearest to the ideal value is found in the human-car interaction design case. The clustering results show its effectiveness in finding an optimum solution to the mental load minimizing problems in human-machine interaction design.

Solving bi-level optimization problems in engineering design using kriging models

Science.gov (United States)

Xia, Yi; Liu, Xiaojie; Du, Gang

2018-05-01

Stackelberg game-theoretic approaches are applied extensively in engineering design to handle distributed collaboration decisions. Bi-level genetic algorithms (BLGAs) and response surfaces have been used to solve the corresponding bi-level programming models. However, the computational costs for BLGAs often increase rapidly with the complexity of lower-level programs, and optimal solution functions sometimes cannot be approximated by response surfaces. This article proposes a new method, namely the optimal solution function approximation by kriging model (OSFAKM), in which kriging models are used to approximate the optimal solution functions. A detailed example demonstrates that OSFAKM can obtain better solutions than BLGAs and response surface-based methods, and at the same time reduce the workload of computation remarkably. Five benchmark problems and a case study of the optimal design of a thin-walled pressure vessel are also presented to illustrate the feasibility and potential of the proposed method for bi-level optimization in engineering design.

Evaluation of scalarization methods and NSGA-II/SPEA2 genetic algorithms for multi-objective optimization of green supply chain design

NARCIS (Netherlands)

C. van der Plas (Corne); T. Tervonen (Tommi); R. Dekker (Rommert)

2012-01-01

textabstractThis paper considers supply chain design in green logistics. We formulate the choice of an environmentally conscious chain design as a multi-objective optimization (MOO) problem and approximate the Pareto front using the weighted sum and epsilon constraint scalarization methods as well

Fast Bayesian optimal experimental design and its applications

KAUST Repository

Long, Quan

2015-01-07

We summarize our Laplace method and multilevel method of accelerating the computation of the expected information gain in a Bayesian Optimal Experimental Design (OED). Laplace method is a widely-used method to approximate an integration in statistics. We analyze this method in the context of optimal Bayesian experimental design and extend this method from the classical scenario, where a single dominant mode of the parameters can be completely-determined by the experiment, to the scenarios where a non-informative parametric manifold exists. We show that by carrying out this approximation the estimation of the expected Kullback-Leibler divergence can be significantly accelerated. While Laplace method requires a concentration of measure, multi-level Monte Carlo method can be used to tackle the problem when there is a lack of measure concentration. We show some initial results on this approach. The developed methodologies have been applied to various sensor deployment problems, e.g., impedance tomography and seismic source inversion.

Design and volume optimization of space structures

KAUST Repository

Jiang, Caigui; Tang, Chengcheng; Seidel, Hans-Peter; Wonka, Peter

2017-01-01

We study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.

Design and volume optimization of space structures

KAUST Repository

Jiang, Caigui

2017-07-21

We study the design and optimization of statically sound and materially efficient space structures constructed by connected beams. We propose a systematic computational framework for the design of space structures that incorporates static soundness, approximation of reference surfaces, boundary alignment, and geometric regularity. To tackle this challenging problem, we first jointly optimize node positions and connectivity through a nonlinear continuous optimization algorithm. Next, with fixed nodes and connectivity, we formulate the assignment of beam cross sections as a mixed-integer programming problem with a bilinear objective function and quadratic constraints. We solve this problem with a novel and practical alternating direction method based on linear programming relaxation. The capability and efficiency of the algorithms and the computational framework are validated by a variety of examples and comparisons.

Optimization Design of Multi-Parameters in Rail Launcher System

Directory of Open Access Journals (Sweden)

Yujiao Zhang

2014-05-01

Full Text Available Today the energy storage systems are still encumbering, therefore it is useful to think about the optimization of a railgun system in order to achieve the best performance with the lowest energy input. In this paper, an optimal design method considering 5 parameters is proposed to improve the energy conversion efficiency of a simple railgun. In order to avoid costly trials, the field- circuit method is employed to analyze the operations of different structural railguns with different parameters respectively. And the orthogonal test approach is used to guide the simulation for choosing the better parameter combinations, as well reduce the calculation cost. The research shows that the proposed method gives a better result in the energy efficiency of the system. To improve the energy conversion efficiency of electromagnetic rail launchers, the selection of more parameters must be considered in the design stage, such as the width, height and length of rail, the distance between rail pair, and pulse forming inductance. However, the relationship between these parameters and energy conversion efficiency cannot be directly described by one mathematical expression. So optimization methods must be applied to conduct design. In this paper, a rail launcher with five parameters was optimized by using orthogonal test method. According to the arrangement of orthogonal table, the better parameters’ combination can be obtained through less calculation. Under the condition of different parameters’ value, field and circuit simulation analysis were made. The results show that the energy conversion efficiency of the system is increased by 71.9 % after parameters optimization.

A Method to Determine Supply Voltage of Permanent Magnet Motor at Optimal Design Stage

Science.gov (United States)

Matustomo, Shinya; Noguchi, So; Yamashita, Hideo; Tanimoto, Shigeya

The permanent magnet motors (PM motors) are widely used in electrical machinery, such as air conditioner, refrigerator and so on. In recent years, from the point of view of energy saving, it is necessary to improve the efficiency of PM motor by optimization. However, in the efficiency optimization of PM motor, many design variables and many restrictions are required. In this paper, the efficiency optimization of PM motor with many design variables was performed by using the voltage driven finite element analysis with the rotating simulation of the motor and the genetic algorithm.

Numerical optimization of Combined Heat and Power Organic Rankine Cycles – Part A: Design optimization

International Nuclear Information System (INIS)

Martelli, Emanuele; Capra, Federico; Consonni, Stefano

2015-01-01

This two-part paper proposes an approach based on state-of-the-art numerical optimization methods for simultaneously determining the most profitable design and part-load operation of Combined Heat and Power Organic Rankine Cycles. Compared to the usual design practice, the important advantages of the proposed approach are (i) to consider the part-load performance of the ORC at the design stage, (ii) to optimize not only the cycle variables, but also the main turbine design variables (number of stages, stage loads, rotational speed). In this first part (Part A), the design model and the optimization algorithm are presented and tested on a real-world test case. PGS-COM, a recently proposed hybrid derivative-free algorithm, allows to efficiently tackle the challenging non-smooth black-box problem. - Highlights: • Algorithm for the simultaneous optimization Organic Rakine Cycle and turbine. • Thermodynamic and economic models of boiler, cycle, turbine are developed. • Non-smooth black-box optimization problem is successfully tackled with PGS-COM. • Test cases show that the algorithm returns optimal solutions within 4 min. • Toluene outperforms MDM (a siloxane) in terms of efficiency and costs.

Ferroelectric materials for piezoelectric actuators by optimal design

International Nuclear Information System (INIS)

Jayachandran, K.P.; Guedes, J.M.; Rodrigues, H.C.

2011-01-01

Research highlights: → Microstructure optimization of ferroelectric materials by stochastic optimization. → Polycrystalline ferroelectrics possess better piezo actuation than single crystals. → Randomness of the grain orientations would enhance the overall piezoelectricity. - Abstract: Optimization methods provide a systematic means of designing heterogeneous materials with tailored properties and microstructures focussing on a specific objective. An optimization procedure incorporating a continuum modeling is used in this work to identify the ideal orientation distribution of ferroelectrics (FEs) for application in piezoelectric actuators. Piezoelectric actuation is dictated primarily by the piezoelectric strain coefficients d iμ . Crystallographic orientation is inextricably related to the piezoelectric properties of FEs. This suggests that piezoelectric properties can be tailored by a proper choice of the parameters which control the orientation distribution. Nevertheless, this choice is complicated and it is impossible to analyze all possible combinations of the distribution parameters or the angles themselves. Stochastic optimization combined with a generalized Monte Carlo scheme is used to optimize the objective functions, the effective piezoelectric coefficients d 31 and d 15 . The procedure is applied to heterogeneous, polycrystalline, FE ceramics which are essentially an aggregate of variously oriented grains (crystallites). Global piezoelectric properties are calculated using the homogenization method at each grain configuration chosen by the optimization algorithm. Optimal design variables and microstructure that would generate polycrystalline configurations that multiply the macroscopic piezoelectricity are identified.

Systematic Optimization-Based Integrated Chemical Product–Process Design Framework

DEFF Research Database (Denmark)

Cignitti, Stefano; Mansouri, Seyed Soheil; Woodley, John M.

2018-01-01

An integrated optimization-based framework for product and process design is proposed. The framework uses a set of methods and tools to obtain the optimal product–process design solution given a set of economic and environmental sustainability targets. The methods and tools required are property...... of the framework is demonstrated through three case studies: (i) refrigeration cycle unit for R134a replacement, (ii) a mixed working fluid design problem for R134a replacement, and (iii) pure solvent design for water-acetic acid LLE extraction. Through the application of the framework it is demonstrated that all...... prediction through group contributions, unless supported with a database, computer-aided molecular and mixture/blend design for generation of novel as well as existing products and mathematical programming for formulating and solving multiscale integrated process–product design problems. The application...

Optimal Network-Topology Design

Science.gov (United States)

Li, Victor O. K.; Yuen, Joseph H.; Hou, Ting-Chao; Lam, Yuen Fung

1987-01-01

Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.

Optimization of laccase production from Marasmiellus palmivorus LA1 by Taguchi method of Design of experiments.

Science.gov (United States)

Chenthamarakshan, Aiswarya; Parambayil, Nayana; Miziriya, Nafeesathul; Soumya, P S; Lakshmi, M S Kiran; Ramgopal, Anala; Dileep, Anuja; Nambisan, Padma

2017-02-13

Fungal laccase has profound applications in different fields of biotechnology due to its broad specificity and high redox potential. Any successful application of the enzyme requires large scale production. As laccase production is highly dependent on medium components and cultural conditions, optimization of the same is essential for efficient product production. Production of laccase by fungal strain Marasmiellus palmivorus LA1 under solid state fermentation was optimized by the Taguchi design of experiments (DOE) methodology. An orthogonal array (L8) was designed using Qualitek-4 software to study the interactions and relative influence of the seven selected factors by one factor at a time approach. The optimum condition formulated was temperature (28 °C), pH (5), galactose (0.8%w/v), cupric sulphate (3 mM), inoculum concentration (number of mycelial agar pieces) (6Nos.) and substrate length (0.05 m). Overall yield increase of 17.6 fold was obtained after optimization. Statistical optimization leads to the elimination of an insignificant medium component ammonium dihydrogen phosphate from the process and contributes to a 1.06 fold increase in enzyme production. A final production of 667.4 ± 13 IU/mL laccase activity paves way for the application of this strain for industrial applications. Study optimized lignin degrading laccases from Marasmiellus palmivorus LA1. This laccases can thus be used for further applications in different scales of production after analyzing the properties of the enzyme. Study also confirmed the use of taguchi method for optimizations of product production.

Simulation-based optimization for product and process design

NARCIS (Netherlands)

Driessen, L.

2006-01-01

The design of products and processes has gradually shifted from a purely physical process towards a process that heavily relies on computer simulations (virtual prototyping). To optimize this virtual design process in terms of speed and final product quality, statistical methods and mathematical

Analysis of neighborhood behavior in lead optimization and array design.

Science.gov (United States)

Papadatos, George; Cooper, Anthony W J; Kadirkamanathan, Visakan; Macdonald, Simon J F; McLay, Iain M; Pickett, Stephen D; Pritchard, John M; Willett, Peter; Gillet, Valerie J

2009-02-01

Neighborhood behavior describes the extent to which small structural changes defined by a molecular descriptor are likely to lead to small property changes. This study evaluates two methods for the quantification of neighborhood behavior: the optimal diagonal method of Patterson et al. and the optimality criterion method of Horvath and Jeandenans. The methods are evaluated using twelve different types of fingerprint (both 2D and 3D) with screening data derived from several lead optimization projects at GlaxoSmithKline. The principal focus of the work is the design of chemical arrays during lead optimization, and the study hence considers not only biological activity but also important drug properties such as metabolic stability, permeability, and lipophilicity. Evidence is provided to suggest that the optimality criterion method may provide a better quantitative description of neighborhood behavior than the optimal diagonal method.

Design optimization of piezoresistive cantilevers for force sensing in air and water

Science.gov (United States)

Doll, Joseph C.; Park, Sung-Jin; Pruitt, Beth L.

2009-01-01

Piezoresistive cantilevers fabricated from doped silicon or metal films are commonly used for force, topography, and chemical sensing at the micro- and macroscales. Proper design is required to optimize the achievable resolution by maximizing sensitivity while simultaneously minimizing the integrated noise over the bandwidth of interest. Existing analytical design methods are insufficient for modeling complex dopant profiles, design constraints, and nonlinear phenomena such as damping in fluid. Here we present an optimization method based on an analytical piezoresistive cantilever model. We use an existing iterative optimizer to minimimize a performance goal, such as minimum detectable force. The design tool is available as open source software. Optimal cantilever design and performance are found to strongly depend on the measurement bandwidth and the constraints applied. We discuss results for silicon piezoresistors fabricated by epitaxy and diffusion, but the method can be applied to any dopant profile or material which can be modeled in a similar fashion or extended to other microelectromechanical systems. PMID:19865512

Optimal design for rectangular isolated footings using the real soil pressure

Directory of Open Access Journals (Sweden)

Arnulfo Luévanos Rojas

2017-05-01

Full Text Available The standard design method (classical method for reinforced concrete rectangular footings is: First, a dimension is proposed and should comply with the allowable stresses; subsequently, the effective depth is obtained from the maximum moment and is checked against the bending shear and the punching shear until, it complies with these conditions and, then, steel reinforcement is obtained, but it is not guarantee that the minimum cost will be obtained. This paper shows an optimal design for reinforced concrete rectangular footings using the new model. A numerical experimentation is presented to show the model capability to estimate the minimum cost design of the materials used for a rectangular footing that supports an axial load and moments in two directions in accordance to the building code requirements for structural concrete and commentary (ACI 318-13. Also, a comparison is made between the optimal design and current design for rectangular footings. The solutions show that the optimal design is more economical and more precise with respect to the current design, because standard design is done by trial and error. Then, the optimal design should be used to obtain the minimum cost design for reinforced concrete rectangular footings.

Conceptual optimal design of jackets

DEFF Research Database (Denmark)

Sandal, Kasper; Verbart, Alexander; Stolpe, Mathias

Structural optimization can explore a large design space (400 jackets) in a short time (2 hours), and thus lead to better conceptual jacket designs.......Structural optimization can explore a large design space (400 jackets) in a short time (2 hours), and thus lead to better conceptual jacket designs....

A Schur Method for Designing LQ-optimal Systems with Prescribed Eigenvalues

Directory of Open Access Journals (Sweden)

David Di Ruscio

1990-01-01

Full Text Available In this paper a new algorithm for solving the LQ-optimal pole placement problem is presented. The method studied is a variant of the classical eigenvector approach and instead uses a set of Schur vectors, thereby gaining substantial numerical advantages. An important task in this method is the LQ-optimal pole placement problem for a second order (sub system. The paper presents a detailed analytical solution to this problem. This part is not only important for solving the general n-dimensional problem but also provides an understanding of the behaviour of an optimal system: The paper shows that in some cases it is an infinite number; in others a finite number, and in still others, non state weighting matrices Q that give the system a set of prescribed eigenvalues. Equations are presented that uniquely determine these state weight matrices as a function of the new prescribed eigcnvalues. From this result we have been able to derive the maximum possible imaginary part of the eigenvalues in an LQ-optimal system, irrespective of how the state weight matrix is chosen.

Configurable intelligent optimization algorithm design and practice in manufacturing

CERN Document Server

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

Data Science and Optimal Learning for Material Discovery and Design

Science.gov (United States)

; Optimal Learning for Material Discovery & Design Data Science and Optimal Learning for Material inference and optimization methods that can constrain predictions using insights and results from theory directions in the application of information theoretic tools to materials problems related to learning from

Aerodynamic optimization of wind turbine rotor using CFD/AD method

Science.gov (United States)

Cao, Jiufa; Zhu, Weijun; Wang, Tongguang; Ke, Shitang

2018-05-01

The current work describes a novel technique for wind turbine rotor optimization. The aerodynamic design and optimization of wind turbine rotor can be achieved with different methods, such as the semi-empirical engineering methods and more accurate computational fluid dynamic (CFD) method. The CFD method often provides more detailed aerodynamics features during the design process. However, high computational cost limits the application, especially for rotor optimization purpose. In this paper, a CFD-based actuator disc (AD) model is used to represent turbulent flow over a wind turbine rotor. The rotor is modeled as a permeable disc of equivalent area where the forces from the blades are distributed on the circular disc. The AD model is coupled with a Reynolds Averaged Navier-Stokes (RANS) solver such that the thrust and power are simulated. The design variables are the shape parameters comprising the chord, the twist and the relative thickness of the wind turbine rotor blade. The comparative aerodynamic performance is analyzed between the original and optimized reference wind turbine rotor. The results showed that the optimization framework can be effectively and accurately utilized in enhancing the aerodynamic performance of the wind turbine rotor.

Optimization Design Method for the CMOS-type Capacitive Micro-Machined Ultrasonic Transducer

Directory of Open Access Journals (Sweden)

D. Y. Chiou

2011-12-01

Full Text Available In this study, an integrated modeling technique for characterization and optimization design of the complementary metal-oxide-semiconductor (CMOS capacitive micro-arrayed ultrasonic transducer (pCMOS-CMUT is presented. Electromechanical finite element simulations are performed to investigate its operational characteristics, such as the collapse voltage and the resonant frequency. Both the numerical and experimental results are in good agreement. In order to simultaneously customize the resonant frequency and minimize the collapse voltage, the genetic algorithm (GA is applied to optimize dimensional parameters of the transducer. From the present results, it is concluded that the FE/GA coupling approach provides another efficient numerical tool for multi-objective design of the pCMOS-CMUT.

Optimal control linear quadratic methods

CERN Document Server

Anderson, Brian D O

2007-01-01

This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material.The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the

Topology Optimization of Passive Micromixers Based on Lagrangian Mapping Method

Directory of Open Access Journals (Sweden)

Yuchen Guo

2018-03-01

Full Text Available This paper presents an optimization-based design method of passive micromixers for immiscible fluids, which means that the Peclet number infinitely large. Based on topology optimization method, an optimization model is constructed to find the optimal layout of the passive micromixers. Being different from the topology optimization methods with Eulerian description of the convection-diffusion dynamics, this proposed method considers the extreme case, where the mixing is dominated completely by the convection with negligible diffusion. In this method, the mixing dynamics is modeled by the mapping method, a Lagrangian description that can deal with the case with convection-dominance. Several numerical examples have been presented to demonstrate the validity of the proposed method.

Studies Regarding Design and Optimization of Mechanisms Using Modern Techniques of CAD and CAE

Directory of Open Access Journals (Sweden)

Marius Tufoi

2010-01-01

Full Text Available The paper presents applications of modern techniques of CAD (Computer Aided Design and CAE (Computer Aided Engineering to design and optimize the mechanisms used in mechanical engineering. The use exemplification of these techniques was achieved by designing and optimizing parts of a drawing installation for horizontal continuous casting of metals. By applying these design methods and using finite element method at simulations on designed mechanisms results a number of advantages over traditional methods of drawing and design: speed in drawing, design and optimization of parts and mechanisms, kinematic analysis option, kinetostatic and dynamic through simulation, without requiring physical realization of the part or mechanism, the determination by finite element method of tension, elongations, travel and safety factor and the possibility of optimization for these sizes to ensure the mechanical strength of each piece separately. Achieving these studies was possible using SolidWorks 2009 software suite.

Study on Design Optimization of Centrifugal Compressors Considering Efficiency and Weight

International Nuclear Information System (INIS)

Lee, Younghwan; Kang, Shinhyoung; Ha, Kyunggu

2015-01-01

Various centrifugal compressors are currently used extensively in industrial fields, where the design requirements are more complicated. This makes it more difficult to determine the optimal design point of a centrifugal compressor. Traditionally, the efficiency is an important factor for optimization. In this study, the weight of the compressor was also considered. The aim of this study was to present the design tendency considering the stage efficiency and weight. In addition, this study suggested possibility of a selection of compressor design objectives at an early design stage based on the optimization results. Only a vaneless diffuser was considered in this case. The Kriging method was used with sample points from 1D design program data. The optimal points were determined in a substitute design space.

Study on Design Optimization of Centrifugal Compressors Considering Efficiency and Weight

Energy Technology Data Exchange (ETDEWEB)

Lee, Younghwan; Kang, Shinhyoung [Seoul National University, Seoul (Korea, Republic of); Ha, Kyunggu [Hyundai Motor Group, Ulsan (Korea, Republic of)

2015-04-15

Various centrifugal compressors are currently used extensively in industrial fields, where the design requirements are more complicated. This makes it more difficult to determine the optimal design point of a centrifugal compressor. Traditionally, the efficiency is an important factor for optimization. In this study, the weight of the compressor was also considered. The aim of this study was to present the design tendency considering the stage efficiency and weight. In addition, this study suggested possibility of a selection of compressor design objectives at an early design stage based on the optimization results. Only a vaneless diffuser was considered in this case. The Kriging method was used with sample points from 1D design program data. The optimal points were determined in a substitute design space.

An Effective Experimental Optimization Method for Wireless Power Transfer System Design Using Frequency Domain Measurement

Directory of Open Access Journals (Sweden)

Sangyeong Jeong

2017-10-01

Full Text Available This paper proposes an experimental optimization method for a wireless power transfer (WPT system. The power transfer characteristics of a WPT system with arbitrary loads and various types of coupling and compensation networks can be extracted by frequency domain measurements. The various performance parameters of the WPT system, such as input real/imaginary/apparent power, power factor, efficiency, output power and voltage gain, can be accurately extracted in a frequency domain by a single passive measurement. Subsequently, the design parameters can be efficiently tuned by separating the overall design steps into two parts. The extracted performance parameters of the WPT system were validated with time-domain experiments.

Examples of radiation protection optimization in design and operation

International Nuclear Information System (INIS)

Gonzalez, A.J.; Palacios, E.; Curti, A.; Agatiello, O.; Majchrzak, J.

1982-01-01

The practical use of the requirement of optimization of radiological protection is presented. Application examples for designing ventilation systems and for maintenance operations of nuclear plants are given. A method is developed for the application of the optimization requirement to the design of ventilation systems in contaminated environments. Representative values of the main parameters are presented and their relevant features are discussed. A practical example shows actual results for a radioisotope production plant. Causes influencing collective doses incurred by the workers during maintenance operations are analyzed. A method is presented for the optimization of both the level of training of personnel and the apportionment of individual doses. As an example, this methodology is applied to the maintenance operations in a nuclear power plant. (author)

Optimal covariate designs theory and applications

CERN Document Server

Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar

2015-01-01

This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...

Design and optimization of membrane-type acoustic metamaterials

Science.gov (United States)

Blevins, Matthew Grant

One of the most common problems in noise control is the attenuation of low frequency noise. Typical solutions require barriers with high density and/or thickness. Membrane-type acoustic metamaterials are a novel type of engineered material capable of high low-frequency transmission loss despite their small thickness and light weight. These materials are ideally suited to applications with strict size and weight limitations such as aircraft, automobiles, and buildings. The transmission loss profile can be manipulated by changing the micro-level substructure, stacking multiple unit cells, or by creating multi-celled arrays. To date, analysis has focused primarily on experimental studies in plane-wave tubes and numerical modeling using finite element methods. These methods are inefficient when used for applications that require iterative changes to the structure of the material. To facilitate design and optimization of membrane-type acoustic metamaterials, computationally efficient dynamic models based on the impedance-mobility approach are proposed. Models of a single unit cell in a waveguide and in a baffle, a double layer of unit cells in a waveguide, and an array of unit cells in a baffle are studied. The accuracy of the models and the validity of assumptions used are verified using a finite element method. The remarkable computational efficiency of the impedance-mobility models compared to finite element methods enables implementation in design tools based on a graphical user interface and in optimization schemes. Genetic algorithms are used to optimize the unit cell design for a variety of noise reduction goals, including maximizing transmission loss for broadband, narrow-band, and tonal noise sources. The tools for design and optimization created in this work will enable rapid implementation of membrane-type acoustic metamaterials to solve real-world noise control problems.

Mathematical programming methods for large-scale topology optimization problems

DEFF Research Database (Denmark)

Rojas Labanda, Susana

for mechanical problems, but has rapidly extended to many other disciplines, such as fluid dynamics and biomechanical problems. However, the novelty and improvements of optimization methods has been very limited. It is, indeed, necessary to develop of new optimization methods to improve the final designs......, and at the same time, reduce the number of function evaluations. Nonlinear optimization methods, such as sequential quadratic programming and interior point solvers, have almost not been embraced by the topology optimization community. Thus, this work is focused on the introduction of this kind of second...... for the classical minimum compliance problem. Two of the state-of-the-art optimization algorithms are investigated and implemented for this structural topology optimization problem. A Sequential Quadratic Programming (TopSQP) and an interior point method (TopIP) are developed exploiting the specific mathematical...

An accurate and efficient reliability-based design optimization using the second order reliability method and improved stability transformation method

Science.gov (United States)

Meng, Zeng; Yang, Dixiong; Zhou, Huanlin; Yu, Bo

2018-05-01

The first order reliability method has been extensively adopted for reliability-based design optimization (RBDO), but it shows inaccuracy in calculating the failure probability with highly nonlinear performance functions. Thus, the second order reliability method is required to evaluate the reliability accurately. However, its application for RBDO is quite challenge owing to the expensive computational cost incurred by the repeated reliability evaluation and Hessian calculation of probabilistic constraints. In this article, a new improved stability transformation method is proposed to search the most probable point efficiently, and the Hessian matrix is calculated by the symmetric rank-one update. The computational capability of the proposed method is illustrated and compared to the existing RBDO approaches through three mathematical and two engineering examples. The comparison results indicate that the proposed method is very efficient and accurate, providing an alternative tool for RBDO of engineering structures.

Optimizing Nuclear Reaction Analysis (NRA) using Bayesian Experimental Design

International Nuclear Information System (INIS)

Toussaint, Udo von; Schwarz-Selinger, Thomas; Gori, Silvio

2008-01-01

Nuclear Reaction Analysis with 3 He holds the promise to measure Deuterium depth profiles up to large depths. However, the extraction of the depth profile from the measured data is an ill-posed inversion problem. Here we demonstrate how Bayesian Experimental Design can be used to optimize the number of measurements as well as the measurement energies to maximize the information gain. Comparison of the inversion properties of the optimized design with standard settings reveals huge possible gains. Application of the posterior sampling method allows to optimize the experimental settings interactively during the measurement process.

Design of two-channel filter bank using nature inspired optimization based fractional derivative constraints.

Science.gov (United States)

Kuldeep, B; Singh, V K; Kumar, A; Singh, G K

2015-01-01

In this article, a novel approach for 2-channel linear phase quadrature mirror filter (QMF) bank design based on a hybrid of gradient based optimization and optimization of fractional derivative constraints is introduced. For the purpose of this work, recently proposed nature inspired optimization techniques such as cuckoo search (CS), modified cuckoo search (MCS) and wind driven optimization (WDO) are explored for the design of QMF bank. 2-Channel QMF is also designed with particle swarm optimization (PSO) and artificial bee colony (ABC) nature inspired optimization techniques. The design problem is formulated in frequency domain as sum of L2 norm of error in passband, stopband and transition band at quadrature frequency. The contribution of this work is the novel hybrid combination of gradient based optimization (Lagrange multiplier method) and nature inspired optimization (CS, MCS, WDO, PSO and ABC) and its usage for optimizing the design problem. Performance of the proposed method is evaluated by passband error (ϕp), stopband error (ϕs), transition band error (ϕt), peak reconstruction error (PRE), stopband attenuation (As) and computational time. The design examples illustrate the ingenuity of the proposed method. Results are also compared with the other existing algorithms, and it was found that the proposed method gives best result in terms of peak reconstruction error and transition band error while it is comparable in terms of passband and stopband error. Results show that the proposed method is successful for both lower and higher order 2-channel QMF bank design. A comparative study of various nature inspired optimization techniques is also presented, and the study singles out CS as a best QMF optimization technique. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

DETERMINATION OF BRAKING OPTIMAL MODE OF CONTROLLED CUT OF DESIGN GROUP

Directory of Open Access Journals (Sweden)

A. S. Dorosh

2015-06-01

Full Text Available Purpose. The application of automation systems of breaking up process on the gravity hump is the efficiency improvement of their operation, absolute provision of trains breaking up safety demands, as well as improvement of hump staff working conditions. One of the main tasks of the indicated systems is the assurance of cuts reliable separation at all elements of their rolling route to the classification track. This task is a sophisticated optimization problem and has not received a final decision. Therefore, the task of determining the cuts braking mode is quite relevant. The purpose of this research is to find the optimal braking mode of control cut of design group. Methodology. In order to achieve the purpose is offered to use the direct search methods in the work, namely the Box complex method. This method does not require smoothness of the objective function, takes into account its limitations and does not require calculation of the function derivatives, and uses only its value. Findings. Using the Box method was developed iterative procedure for determining the control cut optimal braking mode of design group. The procedure maximizes the smallest controlled time interval in the group. To evaluate the effectiveness of designed procedure the series of simulation experiments of determining the control cut braking mode of design group was performed. The results confirmed the efficiency of the developed optimization procedure. Originality. The author formalized the task of optimizing control cut braking mode of design group, taking into account the cuts separation of design group at all elements (switches, retarders during cuts rolling to the classification track. The problem of determining the optimal control cut braking mode of design group was solved. The developed braking mode ensures cuts reliable separation of the group not only at the switches but at the retarders of brake position. Practical value. The developed procedure can be

Computer Based Porosity Design by Multi Phase Topology Optimization

Science.gov (United States)

Burblies, Andreas; Busse, Matthias

2008-02-01

A numerical simulation technique called Multi Phase Topology Optimization (MPTO) based on finite element method has been developed and refined by Fraunhofer IFAM during the last five years. MPTO is able to determine the optimum distribution of two or more different materials in components under thermal and mechanical loads. The objective of optimization is to minimize the component's elastic energy. Conventional topology optimization methods which simulate adaptive bone mineralization have got the disadvantage that there is a continuous change of mass by growth processes. MPTO keeps all initial material concentrations and uses methods adapted from molecular dynamics to find energy minimum. Applying MPTO to mechanically loaded components with a high number of different material densities, the optimization results show graded and sometimes anisotropic porosity distributions which are very similar to natural bone structures. Now it is possible to design the macro- and microstructure of a mechanical component in one step. Computer based porosity design structures can be manufactured by new Rapid Prototyping technologies. Fraunhofer IFAM has applied successfully 3D-Printing and Selective Laser Sintering methods in order to produce very stiff light weight components with graded porosities calculated by MPTO.

Optimized emission in nanorod arrays through quasi-aperiodic inverse design.

Science.gov (United States)

Anderson, P Duke; Povinelli, Michelle L

2015-06-01

We investigate a new class of quasi-aperiodic nanorod structures for the enhancement of incoherent light emission. We identify one optimized structure using an inverse design algorithm and the finite-difference time-domain method. We carry out emission calculations on both the optimized structure as well as a simple periodic array. The optimized structure achieves nearly perfect light extraction while maintaining a high spontaneous emission rate. Overall, the optimized structure can achieve a 20%-42% increase in external quantum efficiency relative to a simple periodic design, depending on material quality.

Inverse design of dielectric materials by topology optimization

DEFF Research Database (Denmark)

Otomori, M.; Andkjær, Jacob Anders; Sigmund, Ole

2012-01-01

The capabilities and operation of electromagnetic devices can be dramatically enhanced if artificial materials that provide certain prescribed properties can be designed and fabricated. This paper presents a systematic methodology for the design of dielectric materials with prescribed electric...... permittivity. A gradient-based topology optimization method is used to find the distribution of dielectric material for the unit cell of a periodic microstructure composed of one or two dielectric materials. The optimization problem is formulated as a problem to minimize the square of the difference between...

Research on optimization design of conformal cooling channels in hot stamping tool based on response surface methodology and multi-objective optimization

Directory of Open Access Journals (Sweden)

He Bin

2016-01-01

Full Text Available In order to optimize the layout of the conformal cooling channels in hot stamping tools, a response surface methodology and multi-objective optimization technique are proposed. By means of an Optimal Latin Hypercube experimental design method, a design matrix with 17 factors and 50 levels is generated. Three kinds of design variables, the radius Rad of the cooling channel, the distance H from the channel center to tool work surface and the ratio rat of each channel center, are optimized to determine the layout of cooling channels. The average temperature and temperature deviation of work surface are used to evaluate the cooling performance of hot stamping tools. On the basis of the experimental design results, quadratic response surface models are established to describe the relationship between the design variables and the evaluation objectives. The error analysis is performed to ensure the accuracy of response surface models. Then the layout of the conformal cooling channels is optimized in accordance with a multi-objective optimization method to find the Pareto optimal frontier which consists of some optimal combinations of design variables that can lead to an acceptable cooling performance.

Simulated annealing method for electronic circuits design: adaptation and comparison with other optimization methods; La methode du recuit simule pour la conception des circuits electroniques: adaptation et comparaison avec d`autres methodes d`optimisation

Energy Technology Data Exchange (ETDEWEB)

Berthiau, G

1995-10-01

The circuit design problem consists in determining acceptable parameter values (resistors, capacitors, transistors geometries ...) which allow the circuit to meet various user given operational criteria (DC consumption, AC bandwidth, transient times ...). This task is equivalent to a multidimensional and/or multi objective optimization problem: n-variables functions have to be minimized in an hyper-rectangular domain ; equality constraints can be eventually specified. A similar problem consists in fitting component models. In this way, the optimization variables are the model parameters and one aims at minimizing a cost function built on the error between the model response and the data measured on the component. The chosen optimization method for this kind of problem is the simulated annealing method. This method, provided by the combinatorial optimization domain, has been adapted and compared with other global optimization methods for the continuous variables problems. An efficient strategy of variables discretization and a set of complementary stopping criteria have been proposed. The different parameters of the method have been adjusted with analytical functions of which minima are known, classically used in the literature. Our simulated annealing algorithm has been coupled with an open electrical simulator SPICE-PAC of which the modular structure allows the chaining of simulations required by the circuit optimization process. We proposed, for high-dimensional problems, a partitioning technique which ensures proportionality between CPU-time and variables number. To compare our method with others, we have adapted three other methods coming from combinatorial optimization domain - the threshold method, a genetic algorithm and the Tabu search method - The tests have been performed on the same set of test functions and the results allow a first comparison between these methods applied to continuous optimization variables. (Abstract Truncated)

Design optimization applied in structural dynamics

NARCIS (Netherlands)

Akcay-Perdahcioglu, Didem; de Boer, Andries; van der Hoogt, Peter; Tiskarna, T

2007-01-01

This paper introduces the design optimization strategies, especially for structures which have dynamic constraints. Design optimization involves first the modeling and then the optimization of the problem. Utilizing the Finite Element (FE) model of a structure directly in an optimization process

Optimal Design, Reliability And Sensitivity Analysis Of Foundation Plate

Directory of Open Access Journals (Sweden)

Tvrdá Katarína

2015-12-01

Full Text Available This paper deals with the optimal design of thickness of a plate rested on Winkler’s foundation. First order method was used for the optimization, while maintaining different restrictive conditions. The aim is to obtain a minimum volume of the foundation plate. At the end some probabilistic and safety analysis of the deflection of the foundation using LHS Monte Carlo method are presented.

Novel Verification Method for Timing Optimization Based on DPSO

Directory of Open Access Journals (Sweden)

Chuandong Chen

2018-01-01

Full Text Available Timing optimization for logic circuits is one of the key steps in logic synthesis. Extant research data are mainly proposed based on various intelligence algorithms. Hence, they are neither comparable with timing optimization data collected by the mainstream electronic design automation (EDA tool nor able to verify the superiority of intelligence algorithms to the EDA tool in terms of optimization ability. To address these shortcomings, a novel verification method is proposed in this study. First, a discrete particle swarm optimization (DPSO algorithm was applied to optimize the timing of the mixed polarity Reed-Muller (MPRM logic circuit. Second, the Design Compiler (DC algorithm was used to optimize the timing of the same MPRM logic circuit through special settings and constraints. Finally, the timing optimization results of the two algorithms were compared based on MCNC benchmark circuits. The timing optimization results obtained using DPSO are compared with those obtained from DC, and DPSO demonstrates an average reduction of 9.7% in the timing delays of critical paths for a number of MCNC benchmark circuits. The proposed verification method directly ascertains whether the intelligence algorithm has a better timing optimization ability than DC.

Optimal Design and Related Areas in Optimization and Statistics

CERN Document Server

Pronzato, Luc

2009-01-01

This edited volume, dedicated to Henry P. Wynn, reflects his broad range of research interests, focusing in particular on the applications of optimal design theory in optimization and statistics. It covers algorithms for constructing optimal experimental designs, general gradient-type algorithms for convex optimization, majorization and stochastic ordering, algebraic statistics, Bayesian networks and nonlinear regression. Written by leading specialists in the field, each chapter contains a survey of the existing literature along with substantial new material. This work will appeal to both the

Flat-plate photovoltaic array design optimization

Science.gov (United States)

Ross, R. G., Jr.

1980-01-01

An analysis is presented which integrates the results of specific studies in the areas of photovoltaic structural design optimization, optimization of array series/parallel circuit design, thermal design optimization, and optimization of environmental protection features. The analysis is based on minimizing the total photovoltaic system life-cycle energy cost including repair and replacement of failed cells and modules. This approach is shown to be a useful technique for array optimization, particularly when time-dependent parameters such as array degradation and maintenance are involved.

Design of AC-DC Grid Connected Converter using Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

Piasecki Szymon

2014-05-01

Full Text Available Power electronic circuits, in particular AC-DC converters are complex systems, many different parameters and objectives have to be taken into account during the design process. Implementation of Multi-Objective Optimization (MOO seems to be attractive idea, which used as designer supporting tool gives possibility for better analysis of the designed system. This paper presents a short introduction to the MOO applied in the field of power electronics. Short introduction to the subject is given in section I. Then, optimization process and its elements are briefly described in section II. Design procedure with proposed optimization parameters and performance indices for AC-DC Grid Connected Converter (GCC interfacing distributed systems is introduced in section III. Some preliminary optimization results, achieved on the basis of analytical and simulation study, are shown at each stage of designing process. Described optimization parameters and performance indices are part of developed global optimization method dedicated for ACDC GCC introduced in section IV. Described optimization method is under development and only short introduction and basic assumptions are presented. In section V laboratory prototype of high efficient and compact 14 kVA AC-DC converter is introduced. The converter is elaborated based on performed designing and optimization procedure with the use of silicon carbide (SiC power semiconductors. Finally, the paper is summarized and concluded in section VI. In presented work theoretical research are conducted in parallel with laboratory prototyping e.g. all theoretical ideas are verified in laboratory using modern DSP microcontrollers and prototypes of the ACDC GCC.

Integrated design optimization research and development in an industrial environment

Science.gov (United States)

Kumar, V.; German, Marjorie D.; Lee, S.-J.

1989-01-01

An overview is given of a design optimization project that is in progress at the GE Research and Development Center for the past few years. The objective of this project is to develop a methodology and a software system for design automation and optimization of structural/mechanical components and systems. The effort focuses on research and development issues and also on optimization applications that can be related to real-life industrial design problems. The overall technical approach is based on integration of numerical optimization techniques, finite element methods, CAE and software engineering, and artificial intelligence/expert systems (AI/ES) concepts. The role of each of these engineering technologies in the development of a unified design methodology is illustrated. A software system DESIGN-OPT has been developed for both size and shape optimization of structural components subjected to static as well as dynamic loadings. By integrating this software with an automatic mesh generator, a geometric modeler and an attribute specification computer code, a software module SHAPE-OPT has been developed for shape optimization. Details of these software packages together with their applications to some 2- and 3-dimensional design problems are described.

Techno-economic design optimization of solar thermal power plants

OpenAIRE

Morin, G.

2011-01-01

A holistic view is essential in the engineering of technical systems. This thesis presents an integrative approach for designing solar thermal power plants. The methodology is based on a techno-economic plant model and a powerful optimization algorithm. Typically, contemporary design methods treat technical and economic parameters and sub-systems separately, making it difficult or even impossible to realize the full optimization potential of power plant systems. The approach presented here ov...

Development of Combinatorial Methods for Alloy Design and Optimization

International Nuclear Information System (INIS)

Pharr, George M.; George, Easo P.; Santella, Michael L

2005-01-01

The primary goal of this research was to develop a comprehensive methodology for designing and optimizing metallic alloys by combinatorial principles. Because conventional techniques for alloy preparation are unavoidably restrictive in the range of alloy composition that can be examined, combinatorial methods promise to significantly reduce the time, energy, and expense needed for alloy design. Combinatorial methods can be developed not only to optimize existing alloys, but to explore and develop new ones as well. The scientific approach involved fabricating an alloy specimen with a continuous distribution of binary and ternary alloy compositions across its surface--an ''alloy library''--and then using spatially resolved probing techniques to characterize its structure, composition, and relevant properties. The three specific objectives of the project were: (1) to devise means by which simple test specimens with a library of alloy compositions spanning the range interest can be produced; (2) to assess how well the properties of the combinatorial specimen reproduce those of the conventionally processed alloys; and (3) to devise screening tools which can be used to rapidly assess the important properties of the alloys. As proof of principle, the methodology was applied to the Fe-Ni-Cr ternary alloy system that constitutes many commercially important materials such as stainless steels and the H-series and C-series heat and corrosion resistant casting alloys. Three different techniques were developed for making alloy libraries: (1) vapor deposition of discrete thin films on an appropriate substrate and then alloying them together by solid-state diffusion; (2) co-deposition of the alloying elements from three separate magnetron sputtering sources onto an inert substrate; and (3) localized melting of thin films with a focused electron-beam welding system. Each of the techniques was found to have its own advantages and disadvantages. A new and very powerful technique for

Inverse design of dispersion compensating optical fiber using topology optimization

DEFF Research Database (Denmark)

Riishede, Jesper; Sigmund, Ole

2008-01-01

We present a new numerical method for designing dispersion compensating optical fibers. The method is based on the solving of the Helmholtz wave equation with a finite-difference modesolver and uses topology optimization combined with a regularization filter for the design of the refractive index...

A method optimization study for atomic absorption ...

African Journals Online (AJOL)

A sensitive, reliable and relative fast method has been developed for the determination of total zinc in insulin by atomic absorption spectrophotometer. This designed study was used to optimize the procedures for the existing methods. Spectrograms of both standard and sample solutions of zinc were recorded by measuring ...

Analytical Model-Based Design Optimization of a Transverse Flux Machine

Energy Technology Data Exchange (ETDEWEB)

Hasan, Iftekhar; Husain, Tausif; Sozer, Yilmaz; Husain, Iqbal; Muljadi, Eduard

2017-02-16

This paper proposes an analytical machine design tool using magnetic equivalent circuit (MEC)-based particle swarm optimization (PSO) for a double-sided, flux-concentrating transverse flux machine (TFM). The magnetic equivalent circuit method is applied to analytically establish the relationship between the design objective and the input variables of prospective TFM designs. This is computationally less intensive and more time efficient than finite element solvers. A PSO algorithm is then used to design a machine with the highest torque density within the specified power range along with some geometric design constraints. The stator pole length, magnet length, and rotor thickness are the variables that define the optimization search space. Finite element analysis (FEA) was carried out to verify the performance of the MEC-PSO optimized machine. The proposed analytical design tool helps save computation time by at least 50% when compared to commercial FEA-based optimization programs, with results found to be in agreement with less than 5% error.

A surrogate based multistage-multilevel optimization procedure for multidisciplinary design optimization

OpenAIRE

Yao, W.; Chen, X.; Ouyang, Q.; Van Tooren, M.

2011-01-01

Optimization procedure is one of the key techniques to address the computational and organizational complexities of multidisciplinary design optimization (MDO). Motivated by the idea of synthetically exploiting the advantage of multiple existing optimization procedures and meanwhile complying with the general process of satellite system design optimization in conceptual design phase, a multistage-multilevel MDO procedure is proposed in this paper by integrating multiple-discipline-feasible (M...

Comprehensive evaluation method in application of nuclear DCS product design

International Nuclear Information System (INIS)

Wang Weixin; Zhao Zhemin; Shi Yingbin

2014-01-01

In order to select the best design proposal in short time, the TOPSIS comprehensive evaluation method in the nuclear power plant DCS product design was introduced. It can intuitively show the different design proposals good or not good by data and shorten the time of the design proposal optimization. The design proposal selected by this method will be more reasonable and has good comprehensive performance indexes. The TOPSIS comprehensive evaluation method achieves good result in one of the nuclear power plant DCS cabinet design proposal optimization. (authors)

A new decomposition method for parallel processing multi-level optimization

International Nuclear Information System (INIS)

Park, Hyung Wook; Kim, Min Soo; Choi, Dong Hoon

2002-01-01

In practical designs, most of the multidisciplinary problems have a large-size and complicate design system. Since multidisciplinary problems have hundreds of analyses and thousands of variables, the grouping of analyses and the order of the analyses in the group affect the speed of the total design cycle. Therefore, it is very important to reorder and regroup the original design processes in order to minimize the total computational cost by decomposing large multidisciplinary problems into several MultiDisciplinary Analysis SubSystems (MDASS) and by processing them in parallel. In this study, a new decomposition method is proposed for parallel processing of multidisciplinary design optimization, such as Collaborative Optimization (CO) and Individual Discipline Feasible (IDF) method. Numerical results for two example problems are presented to show the feasibility of the proposed method

Design optimization for cost and quality: The robust design approach

Science.gov (United States)

Unal, Resit

1990-01-01

Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.

Integrated Design Optimization of a 5-DOF Assistive Light-weight Anthropomorphic Arm

DEFF Research Database (Denmark)

Zhou, Lelai; Bai, Shaoping; Hansen, Michael Rygaard

2011-01-01

An integrated dimensional and drive train optimization method was developed for light-weight robotic arm design. The method deals with the determination of optimal link lengths and the optimal selection of motors and gearboxes from commercially available components. Constraints are formulated...... on the basis of kinematic performance and dynamic requirements, whereas the main objective is to minimize the weight. The design of a human-like arm, which is 10 kg in weight with a load capacity of 5 kg, is described....

Slot Optimization Design of Induction Motor for Electric Vehicle

Science.gov (United States)

Shen, Yiming; Zhu, Changqing; Wang, Xiuhe

2018-01-01

Slot design of induction motor has a great influence on its performance. The RMxprt module based on magnetic circuit method can be used to analyze the influence of rotor slot type on motor characteristics and optimize slot parameters. In this paper, the authors take an induction motor of electric vehicle for a typical example. The first step of the design is to optimize the rotor slot by RMxprt, and then compare the main performance of the motor before and after the optimization through Ansoft Maxwell 2D. After that, the combination of optimum slot type and the optimum parameters are obtained. The results show that the power factor and the starting torque of the optimized motor have been improved significantly. Furthermore, the electric vehicle works at a better running status after the optimization.

Optimization of 3D Field Design

Science.gov (United States)

Logan, Nikolas; Zhu, Caoxiang

2017-10-01

Recent progress in 3D tokamak modeling is now leveraged to create a conceptual design of new external 3D field coils for the DIII-D tokamak. Using the IPEC dominant mode as a target spectrum, the Finding Optimized Coils Using Space-curves (FOCUS) code optimizes the currents and 3D geometry of multiple coils to maximize the total set's resonant coupling. The optimized coils are individually distorted in space, creating toroidal ``arrays'' containing a variety of shapes that often wrap around a significant poloidal extent of the machine. The generalized perturbed equilibrium code (GPEC) is used to determine optimally efficient spectra for driving total, core, and edge neoclassical toroidal viscosity (NTV) torque and these too provide targets for the optimization of 3D coil designs. These conceptual designs represent a fundamentally new approach to 3D coil design for tokamaks targeting desired plasma physics phenomena. Optimized coil sets based on plasma response theory will be relevant to designs for future reactors or on any active machine. External coils, in particular, must be optimized for reliable and efficient fusion reactor designs. Work supported by the US Department of Energy under DE-AC02-09CH11466.

Optimal Market Design

NARCIS (Netherlands)

Boone, J.; Goeree, J.K.

2010-01-01

This paper introduces three methodological advances to study the optimal design of static and dynamic markets. First, we apply a mechanism design approach to characterize all incentive-compatible market equilibria. Second, we conduct a normative analysis, i.e. we evaluate alternative competition and

Topology optimization of hyperelastic structures using a level set method

Science.gov (United States)

Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.

2017-12-01

Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.

A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites

Directory of Open Access Journals (Sweden)

Yunfeng Dong

2017-01-01

Full Text Available The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM, which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components. Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM. In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence. The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM. And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM.

Instrument design optimization with computational methods

Energy Technology Data Exchange (ETDEWEB)

Moore, Michael H. [Old Dominion Univ., Norfolk, VA (United States)

2017-08-01

Using Finite Element Analysis to approximate the solution of differential equations, two different instruments in experimental Hall C at the Thomas Jefferson National Accelerator Facility are analyzed. The time dependence of density uctuations from the liquid hydrogen (LH2) target used in the Q_weak experiment (2011-2012) are studied with Computational Fluid Dynamics (CFD) and the simulation results compared to data from the experiment. The 2.5 kW liquid hydrogen target was the highest power LH2 target in the world and the first to be designed with CFD at Jefferson Lab. The first complete magnetic field simulation of the Super High Momentum Spectrometer (SHMS) is presented with a focus on primary electron beam deflection downstream of the target. The SHMS consists of a superconducting horizontal bending magnet (HB) and three superconducting quadrupole magnets. The HB allows particles scattered at an angle of 5:5 deg to the beam line to be steered into the quadrupole magnets which make up the optics of the spectrometer. Without mitigation, remnant fields from the SHMS may steer the unscattered beam outside of the acceptable envelope on the beam dump and limit beam operations at small scattering angles. A solution is proposed using optimal placement of a minimal amount of shielding iron around the beam line.

Lightweight design of a vertical articulated robot using topology optimization

Energy Technology Data Exchange (ETDEWEB)

Hong, Seong Ki; Hong, Jung Ki; Jang, Gang Won [Sejong Univ., Seoul (Korea, Republic of); Kim, Tae Hyun; Park, Jin Kyun; Kim, Sang Hyun [Hyundai Heavy Industries Co., Ltd., Daejeon (Korea, Republic of)

2012-12-15

Topology optimization is applied for the lightweight design of three main parts of a vertical articulated robot: a base frame, a lower and a upper frame. Design domains for optimization are set as large solid regions that completely embrace the original parts, which are discretized by using three dimensional solid elements. Design variables are parameterized one to one to the material properties of each element by using the SIMP method. The objective of optimization is set as the multi objective form combining the natural frequencies and mean compliances of a structure for which load steps of interest are selected from the multibody dynamics analysis of a robot. The obtained results of topology optimization are post processed to designs favorable to manufacturability for casting process. The final optimized results are 11.0% (base frame), 12.0% (lower frame) and 10.0% (upper frame) lighter with similar or even higher static and dynamic stiffnesses than the original models.

Topology optimization based on the harmony search method

International Nuclear Information System (INIS)

Lee, Seung-Min; Han, Seog-Young

2017-01-01

A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

Topology optimization based on the harmony search method

Energy Technology Data Exchange (ETDEWEB)

Lee, Seung-Min; Han, Seog-Young [Hanyang University, Seoul (Korea, Republic of)

2017-06-15

A new topology optimization scheme based on a Harmony search (HS) as a metaheuristic method was proposed and applied to static stiffness topology optimization problems. To apply the HS to topology optimization, the variables in HS were transformed to those in topology optimization. Compliance was used as an objective function, and harmony memory was defined as the set of the optimized topology. Also, a parametric study for Harmony memory considering rate (HMCR), Pitch adjusting rate (PAR), and Bandwidth (BW) was performed to find the appropriate range for topology optimization. Various techniques were employed such as a filtering scheme, simple average scheme and harmony rate. To provide a robust optimized topology, the concept of the harmony rate update rule was also implemented. Numerical examples are provided to verify the effectiveness of the HS by comparing the optimal layouts of the HS with those of Bidirectional evolutionary structural optimization (BESO) and Artificial bee colony algorithm (ABCA). The following conclu- sions could be made: (1) The proposed topology scheme is very effective for static stiffness topology optimization problems in terms of stability, robustness and convergence rate. (2) The suggested method provides a symmetric optimized topology despite the fact that the HS is a stochastic method like the ABCA. (3) The proposed scheme is applicable and practical in manufacturing since it produces a solid-void design of the optimized topology. (4) The suggested method appears to be very effective for large scale problems like topology optimization.

Load Sharing Multiobjective Optimization Design of a Split Torque Helicopter Transmission

Directory of Open Access Journals (Sweden)

Chenxi Fu

2015-01-01

Full Text Available Split torque designs can offer significant advantages over the traditional planetary designs for helicopter transmissions. However, it has two unique properties, gap and phase differences, which result in the risk of unequal load sharing. Various methods have been proposed to eliminate the effect of gap and promote load sharing to a certain extent. In this paper, system design parameters will be optimized to change the phase difference, thereby further improving load sharing. A nonlinear dynamic model is established to measure the load sharing with dynamic mesh forces quantitatively. Afterwards, a multiobjective optimization of a reference split torque design is conducted with the promoting of load sharing property, lightweight, and safety considered as the objectives. The load sharing property, which is measured by load sharing coefficient, is evaluated under multiple operating conditions with dynamic analysis method. To solve the multiobjective model with NSGA-II, an improvement is done to overcome the problem of time consuming. Finally, a satisfied optimal solution is picked up as the final design from the Pareto optimal front, which achieves improvements in all the three objectives compared with the reference design.

Stochastic optimization methods

CERN Document Server

Marti, Kurt

2005-01-01

Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.

ATHENA optimized coating design

DEFF Research Database (Denmark)

Ferreira, Desiree Della Monica; Christensen, Finn Erland; Jakobsen, Anders Clemen

2012-01-01

The optimization of coating design for the ATHENA mission si described and the possibility of increasing the telescope effective area in the range between 0.1 and 10 keV is investigated. An independent computation of the on-axis effective area based on the mirror design of ATHENA is performed...... in order to review the current coating baseline. The performance of several material combinations, considering a simple bi-layer, simple multilayer and linear graded multilayer coatings are tested and simulation of the mirror performance considering both the optimized coating design and the coating...

A primal-dual interior point method for large-scale free material optimization

DEFF Research Database (Denmark)

Weldeyesus, Alemseged Gebrehiwot; Stolpe, Mathias

2015-01-01

Free Material Optimization (FMO) is a branch of structural optimization in which the design variable is the elastic material tensor that is allowed to vary over the design domain. The requirements are that the material tensor is symmetric positive semidefinite with bounded trace. The resulting...... optimization problem is a nonlinear semidefinite program with many small matrix inequalities for which a special-purpose optimization method should be developed. The objective of this article is to propose an efficient primal-dual interior point method for FMO that can robustly and accurately solve large...... of iterations the interior point method requires is modest and increases only marginally with problem size. The computed optimal solutions obtain a higher precision than other available special-purpose methods for FMO. The efficiency and robustness of the method is demonstrated by numerical experiments on a set...

Optimizing design parameter for light isotopes separation by distillation method

International Nuclear Information System (INIS)

Ahmadi, M.

1999-01-01

More than methods are suggested in the world for producing heavy water, where between them chemical isotopic methods, distillation and electro lys are used widely in industrial scale. To select suitable method for heavy water production in Iran, taking into consideration, domestic technology an facilities, combination of hydrogen sulphide-water dual temperature process (Gs) and distillation (D W) may be proposed. Natural water, is firstly enriched up to 15 a% by G S process and then by distillation unit is enriched up to the grade necessary for Candu type reactors (99.8 a%). The aim of present thesis, is to achieve know-how, optimization of design parameters, and executing basic design for water isotopes separation using distillation process in a plant having minimum scale possible. In distillation, vapour phase resulted from liquid phase heating, is evidently composed of the same constituents as liquid phase. In isotopic distillation, the difference in composition of constituents is not considerable. In fact alteration of constituents composition is so small that makes the separation process impossible, however, direct separation and production of pure products without further processing which becomes possible by distillation, makes this process as one of the most important separation processes. Profiting distillation process to produce heavy water is based on difference existing between boiling point of heavy and light water. The trends of boiling points differences (heavy and light water) is adversely dependant with pressure. As the whole system pressure decreases, difference in boiling points increases. On the other hand according to the definition, separation factor is equal to the ratio of pure light water vapour pressure to that of heavy water, or we can say that the trend of whole system pressure decrease results in separation factor increase, which accordingly separation factor equation to pressure variable should be computed firstly. According to the

Research on Multidisciplinary Optimization Design of Bridge Crane

Directory of Open Access Journals (Sweden)

Tong Yifei

2013-01-01

Full Text Available Bridge crane is one of the most widely used cranes in our country, which is indispensable equipment for material conveying in the modern production. In this paper, the framework of multidisciplinary optimization for bridge crane is proposed. The presented research on crane multidisciplinary design technology for energy saving includes three levels, respectively: metal structures level, transmission design level, and electrical system design level. The shape optimal mathematical model of the crane is established for shape optimization design of metal structure level as well as size optimal mathematical model and topology optimal mathematical model of crane for topology optimization design of metal structure level is established. Finally, system-level multidisciplinary energy-saving optimization design of bridge crane is further carried out with energy-saving transmission design results feedback to energy-saving optimization design of metal structure. The optimization results show that structural optimization design can reduce total mass of crane greatly by using the finite element analysis and multidisciplinary optimization technology premised on the design requirements of cranes such as stiffness and strength; thus, energy-saving design can be achieved.

Shape optimization as a tool to design biocatalytic microreactors

DEFF Research Database (Denmark)

Pereira Rosinha Grundtvig, Ines; Daugaard, Anders Egede; Woodley, John

2017-01-01

in this paper has as its main goal the design of a reactor by compensating for the limitations of the reaction system by modifying the reactor configuration. Random search was the optimization method chosen for transforming the initial reactor configuration to a more optimal one. The case study presented here...

A Bayesian Optimal Design for Sequential Accelerated Degradation Testing

Directory of Open Access Journals (Sweden)

Xiaoyang Li

2017-07-01

Full Text Available When optimizing an accelerated degradation testing (ADT plan, the initial values of unknown model parameters must be pre-specified. However, it is usually difficult to obtain the exact values, since many uncertainties are embedded in these parameters. Bayesian ADT optimal design was presented to address this problem by using prior distributions to capture these uncertainties. Nevertheless, when the difference between a prior distribution and actual situation is large, the existing Bayesian optimal design might cause some over-testing or under-testing issues. For example, the implemented ADT following the optimal ADT plan consumes too much testing resources or few accelerated degradation data are obtained during the ADT. To overcome these obstacles, a Bayesian sequential step-down-stress ADT design is proposed in this article. During the sequential ADT, the test under the highest stress level is firstly conducted based on the initial prior information to quickly generate degradation data. Then, the data collected under higher stress levels are employed to construct the prior distributions for the test design under lower stress levels by using the Bayesian inference. In the process of optimization, the inverse Gaussian (IG process is assumed to describe the degradation paths, and the Bayesian D-optimality is selected as the optimal objective. A case study on an electrical connector’s ADT plan is provided to illustrate the application of the proposed Bayesian sequential ADT design method. Compared with the results from a typical static Bayesian ADT plan, the proposed design could guarantee more stable and precise estimations of different reliability measures.

Deterministic operations research models and methods in linear optimization

CERN Document Server

Rader, David J

2013-01-01

Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear

Multi-objective optimization of generalized reliability design problems using feature models-A concept for early design stages

International Nuclear Information System (INIS)

Limbourg, Philipp; Kochs, Hans-Dieter

2008-01-01

Reliability optimization problems such as the redundancy allocation problem (RAP) have been of considerable interest in the past. However, due to the restrictions of the design space formulation, they may not be applicable in all practical design problems. A method with high modelling freedom for rapid design screening is desirable, especially in early design stages. This work presents a novel approach to reliability optimization. Feature modelling, a specification method originating from software engineering, is applied for the fast specification and enumeration of complex design spaces. It is shown how feature models can not only describe arbitrary RAPs but also much more complex design problems. The design screening is accomplished by a multi-objective evolutionary algorithm for probabilistic objectives. Comparing averages or medians may hide the true characteristics of this distributions. Therefore the algorithm uses solely the probability of a system dominating another to achieve the Pareto optimal set. We illustrate the approach by specifying a RAP and a more complex design space and screening them with the evolutionary algorithm

Optimized universal color palette design for error diffusion

Science.gov (United States)

Kolpatzik, Bernd W.; Bouman, Charles A.

1995-04-01

Currently, many low-cost computers can only simultaneously display a palette of 256 color. However, this palette is usually selectable from a very large gamut of available colors. For many applications, this limited palette size imposes a significant constraint on the achievable image quality. We propose a method for designing an optimized universal color palette for use with halftoning methods such as error diffusion. The advantage of a universal color palette is that it is fixed and therefore allows multiple images to be displayed simultaneously. To design the palette, we employ a new vector quantization method known as sequential scalar quantization (SSQ) to allocate the colors in a visually uniform color space. The SSQ method achieves near-optimal allocation, but may be efficiently implemented using a series of lookup tables. When used with error diffusion, SSQ adds little computational overhead and may be used to minimize the visual error in an opponent color coordinate system. We compare the performance of the optimized algorithm to standard error diffusion by evaluating a visually weighted mean-squared-error measure. Our metric is based on the color difference in CIE L*AL*B*, but also accounts for the lowpass characteristic of human contrast sensitivity.

A topological derivative method for topology optimization

DEFF Research Database (Denmark)

Norato, J.; Bendsøe, Martin P.; Haber, RB

2007-01-01

resource constraint. A smooth and consistent projection of the region bounded by the level set onto the fictitious analysis domain simplifies the response analysis and enhances the convergence of the optimization algorithm. Moreover, the projection supports the reintroduction of solid material in void......We propose a fictitious domain method for topology optimization in which a level set of the topological derivative field for the cost function identifies the boundary of the optimal design. We describe a fixed-point iteration scheme that implements this optimality criterion subject to a volumetric...... regions, a critical requirement for robust topology optimization. We present several numerical examples that demonstrate compliance minimization of fixed-volume, linearly elastic structures....

Lifecycle-Based Swarm Optimization Method for Numerical Optimization

Directory of Open Access Journals (Sweden)

Hai Shen

2014-01-01

Full Text Available Bioinspired optimization algorithms have been widely used to solve various scientific and engineering problems. Inspired by biological lifecycle, this paper presents a novel optimization algorithm called lifecycle-based swarm optimization (LSO. Biological lifecycle includes four stages: birth, growth, reproduction, and death. With this process, even though individual organism died, the species will not perish. Furthermore, species will have stronger ability of adaptation to the environment and achieve perfect evolution. LSO simulates Biological lifecycle process through six optimization operators: chemotactic, assimilation, transposition, crossover, selection, and mutation. In addition, the spatial distribution of initialization population meets clumped distribution. Experiments were conducted on unconstrained benchmark optimization problems and mechanical design optimization problems. Unconstrained benchmark problems include both unimodal and multimodal cases the demonstration of the optimal performance and stability, and the mechanical design problem was tested for algorithm practicability. The results demonstrate remarkable performance of the LSO algorithm on all chosen benchmark functions when compared to several successful optimization techniques.