A Method for Determining Optimal Residential Energy Efficiency Packages
Energy Technology Data Exchange (ETDEWEB)
Polly, B. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gestwick, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bianchi, M. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Anderson, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Horowitz, S. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Christensen, C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Judkoff, R. [National Renewable Energy Lab. (NREL), Golden, CO (United States)
2011-04-01
This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location.
An efficient multilevel optimization method for engineering design
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.
Method for Determining Optimal Residential Energy Efficiency Retrofit Packages
Energy Technology Data Exchange (ETDEWEB)
Polly, B.; Gestwick, M.; Bianchi, M.; Anderson, R.; Horowitz, S.; Christensen, C.; Judkoff, R.
2011-04-01
Businesses, government agencies, consumers, policy makers, and utilities currently have limited access to occupant-, building-, and location-specific recommendations for optimal energy retrofit packages, as defined by estimated costs and energy savings. This report describes an analysis method for determining optimal residential energy efficiency retrofit packages and, as an illustrative example, applies the analysis method to a 1960s-era home in eight U.S. cities covering a range of International Energy Conservation Code (IECC) climate regions. The method uses an optimization scheme that considers average energy use (determined from building energy simulations) and equivalent annual cost to recommend optimal retrofit packages specific to the building, occupants, and location. Energy savings and incremental costs are calculated relative to a minimum upgrade reference scenario, which accounts for efficiency upgrades that would occur in the absence of a retrofit because of equipment wear-out and replacement with current minimum standards.
Efficient solution method for optimal control of nuclear systems
International Nuclear Information System (INIS)
Naser, J.A.; Chambre, P.L.
1981-01-01
To improve the utilization of existing fuel sources, the use of optimization techniques is becoming more important. A technique for solving systems of coupled ordinary differential equations with initial, boundary, and/or intermediate conditions is given. This method has a number of inherent advantages over existing techniques as well as being efficient in terms of computer time and space requirements. An example of computing the optimal control for a spatially dependent reactor model with and without temperature feedback is given. 10 refs
DEFF Research Database (Denmark)
Le, T.H.A.; Pham, D. T.; Canh, Nam Nguyen
2010-01-01
Both the efficient and weakly efficient sets of an affine fractional vector optimization problem, in general, are neither convex nor given explicitly. Optimization problems over one of these sets are thus nonconvex. We propose two methods for optimizing a real-valued function over the efficient...... and weakly efficient sets of an affine fractional vector optimization problem. The first method is a local one. By using a regularization function, we reformulate the problem into a standard smooth mathematical programming problem that allows applying available methods for smooth programming. In case...... the objective function is linear, we have investigated a global algorithm based upon a branch-and-bound procedure. The algorithm uses Lagrangian bound coupling with a simplicial bisection in the criteria space. Preliminary computational results show that the global algorithm is promising....
An Efficient Optimization Method for Solving Unsupervised Data Classification Problems
Directory of Open Access Journals (Sweden)
Parvaneh Shabanzadeh
2015-01-01
Full Text Available Unsupervised data classification (or clustering analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.
Nonlinear Multidimensional Assignment Problems Efficient Conic Optimization Methods and Applications
2015-06-24
WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Arizona State University School of Mathematical & Statistical Sciences 901 S...SUPPLEMENTARY NOTES 14. ABSTRACT The major goals of this project were completed: the exact solution of previously unsolved challenging combinatorial optimization... combinatorial optimization problem, the Directional Sensor Problem, was solved in two ways. First, heuristically in an engineering fashion and second, exactly
Biological optimization systems for enhancing photosynthetic efficiency and methods of use
Hunt, Ryan W.; Chinnasamy, Senthil; Das, Keshav C.; de Mattos, Erico Rolim
2012-11-06
Biological optimization systems for enhancing photosynthetic efficiency and methods of use. Specifically, methods for enhancing photosynthetic efficiency including applying pulsed light to a photosynthetic organism, using a chlorophyll fluorescence feedback control system to determine one or more photosynthetic efficiency parameters, and adjusting one or more of the photosynthetic efficiency parameters to drive the photosynthesis by the delivery of an amount of light to optimize light absorption of the photosynthetic organism while providing enough dark time between light pulses to prevent oversaturation of the chlorophyll reaction centers are disclosed.
Efficiency Optimization Methods in Low-Power High-Frequency Digitally Controlled SMPS
Directory of Open Access Journals (Sweden)
Aleksandar Prodić
2010-06-01
Full Text Available This paper gives a review of several power efficiency optimization techniques that are utilizing advantages of emerging digital control in high frequency switch-mode power supplies (SMPS, processing power from a fraction of watt to several hundreds of watts. Loss mechanisms in semiconductor components are briefly reviewed and the related principles of online efficiency optimization through power stage segmentation and gate voltage variation presented. Practical implementations of such methods utilizing load prediction or data extraction from a digital control loop are shown. The benefits of the presented efficiency methods are verified through experimental results, showing efficiency improvements, ranging from 2% to 30%,depending on the load conditions.
An Efficient Approach for Solving Mesh Optimization Problems Using Newton’s Method
Directory of Open Access Journals (Sweden)
Jibum Kim
2014-01-01
Full Text Available We present an efficient approach for solving various mesh optimization problems. Our approach is based on Newton’s method, which uses both first-order (gradient and second-order (Hessian derivatives of the nonlinear objective function. The volume and surface mesh optimization algorithms are developed such that mesh validity and surface constraints are satisfied. We also propose several Hessian modification methods when the Hessian matrix is not positive definite. We demonstrate our approach by comparing our method with nonlinear conjugate gradient and steepest descent methods in terms of both efficiency and mesh quality.
Chen, Zhongxian; Yu, Haitao; Wen, Cheng
2014-01-01
The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability. PMID:25152913
Chen, Zhongxian; Yu, Haitao; Wen, Cheng
2014-01-01
The goal of direct drive ocean wave energy extraction system is to convert ocean wave energy into electricity. The problem explored in this paper is the design and optimal control for the direct drive ocean wave energy extraction system. An optimal control method based on internal model proportion integration differentiation (IM-PID) is proposed in this paper though most of ocean wave energy extraction systems are optimized by the structure, weight, and material. With this control method, the heavy speed of outer heavy buoy of the energy extraction system is in resonance with incident wave, and the system efficiency is largely improved. Validity of the proposed optimal control method is verified in both regular and irregular ocean waves, and it is shown that IM-PID control method is optimal in that it maximizes the energy conversion efficiency. In addition, the anti-interference ability of IM-PID control method has been assessed, and the results show that the IM-PID control method has good robustness, high precision, and strong anti-interference ability.
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
Directory of Open Access Journals (Sweden)
Lim, C. H.
2007-01-01
Full Text Available Production of Lactobacillus salivarius i 24, a probiotic strain for chicken, was studied in batch fermentation using 500 mL Erlenmeyer flask. Response surface method (RSM was used to optimize the medium for efficient cultivation of the bacterium. The factors investigated were yeast extract, glucose and initial culture pH. A polynomial regression model with cubic and quartic terms was used for the analysis of the experimental data. Estimated optimal conditions of the factors for growth of L. salivarius i 24 were; 3.32 % (w/v glucose, 4.31 % (w/v yeast extract and initial culture pH of 6.10.
A Building Energy Efficiency Optimization Method by Evaluating the Effective Thermal Zones Occupancy
Directory of Open Access Journals (Sweden)
Franco Cotana
2012-12-01
Full Text Available Building energy efficiency is strongly linked to the operations and control systems, together with the integrated performance of passive and active systems. In new high quality buildings in particular, where these two latter aspects have been already implemented at the design stage, users’ perspective, obtained through post-occupancy assessment, has to be considered to reduce whole energy requirement during service life. This research presents an innovative and low-cost methodology to reduce buildings’ energy requirements through post-occupancy assessment and optimization of energy operations using effective users’ attitudes and requirements as feedback. As a meaningful example, the proposed method is applied to a multipurpose building located in New York City, NY, USA, where real occupancy conditions are assessed. The effectiveness of the method is tested through dynamic simulations using a numerical model of the case study, calibrated through real monitoring data collected on the building. Results show that, for the chosen case study, the method provides optimized building energy operations which allow a reduction of primary energy requirements for HVAC, lighting, room-electricity, and auxiliary supply by about 21%. This paper shows that the proposed strategy represents an effective way to reduce buildings’ energy waste, in particular in those complex and high-efficiency buildings that are not performing as well as expected during the concept-design-commissioning stage, in particular due to the lack of feedback after the building handover.
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.
Efficient AUC optimization for classification
Calders, T.; Jaroszewicz, S.; Kok, J.N.; Koronacki, J.; Lopez de Mantaras, R.; Matwin, S.; Mladenic, D.; Skowron, A.
2007-01-01
In this paper we show an efficient method for inducing classifiers that directly optimize the area under the ROC curve. Recently, AUC gained importance in the classification community as a mean to compare the performance of classifiers. Because most classification methods do not optimize this
An efficient inverse radiotherapy planning method for VMAT using quadratic programming optimization.
Hoegele, W; Loeschel, R; Merkle, N; Zygmanski, P
2012-01-01
The purpose of this study is to investigate the feasibility of an inverse planning optimization approach for the Volumetric Modulated Arc Therapy (VMAT) based on quadratic programming and the projection method. The performance of this method is evaluated against a reference commercial planning system (eclipse(TM) for rapidarc(TM)) for clinically relevant cases. The inverse problem is posed in terms of a linear combination of basis functions representing arclet dose contributions and their respective linear coefficients as degrees of freedom. MLC motion is decomposed into basic motion patterns in an intuitive manner leading to a system of equations with a relatively small number of equations and unknowns. These equations are solved using quadratic programming under certain limiting physical conditions for the solution, such as the avoidance of negative dose during optimization and Monitor Unit reduction. The modeling by the projection method assures a unique treatment plan with beneficial properties, such as the explicit relation between organ weightings and the final dose distribution. Clinical cases studied include prostate and spine treatments. The optimized plans are evaluated by comparing isodose lines, DVH profiles for target and normal organs, and Monitor Units to those obtained by the clinical treatment planning system eclipse(TM). The resulting dose distributions for a prostate (with rectum and bladder as organs at risk), and for a spine case (with kidneys, liver, lung and heart as organs at risk) are presented. Overall, the results indicate that similar plan qualities for quadratic programming (QP) and rapidarc(TM) could be achieved at significantly more efficient computational and planning effort using QP. Additionally, results for the quasimodo phantom [Bohsung et al., "IMRT treatment planning: A comparative inter-system and inter-centre planning exercise of the estro quasimodo group," Radiother. Oncol. 76(3), 354-361 (2005)] are presented as an example
Efficiency of operation of wind turbine rotors optimized by the Glauert and Betz methods
DEFF Research Database (Denmark)
Okulov, Valery; Mikkelsen, Robert Flemming; Litvinov, I. V.
2015-01-01
The models of two types of rotors with blades constructed using different optimization methods are compared experimentally. In the first case, the Glauert optimization by the pulsed method is used, which is applied independently for each individual blade cross section. This method remains the main...... time as a result of direct experimental comparison that the rotor constructed using the Betz method makes it possible to extract more kinetic energy from the homogeneous incoming flow....
Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing
2017-07-19
Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.
Efficiency of operation of wind turbine rotors optimized by the Glauert and Betz methods
Okulov, V. L.; Mikkelsen, R.; Litvinov, I. V.; Naumov, I. V.
2015-11-01
The models of two types of rotors with blades constructed using different optimization methods are compared experimentally. In the first case, the Glauert optimization by the pulsed method is used, which is applied independently for each individual blade cross section. This method remains the main approach in designing rotors of various duties. The construction of the other rotor is based on the Betz idea about optimization of rotors by determining a special distribution of circulation over the blade, which ensures the helical structure of the wake behind the rotor. It is established for the first time as a result of direct experimental comparison that the rotor constructed using the Betz method makes it possible to extract more kinetic energy from the homogeneous incoming flow.
Directory of Open Access Journals (Sweden)
JongHyup Lee
2016-08-01
Full Text Available For practical deployment of wireless sensor networks (WSN, WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.
Lee, JongHyup; Pak, Dohyun
2016-01-01
For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743
Directory of Open Access Journals (Sweden)
Luman Zhao
2015-01-01
Full Text Available A thrust allocation method was proposed based on a hybrid optimization algorithm to efficiently and dynamically position a semisubmersible drilling rig. That is, the thrust allocation was optimized to produce the generalized forces and moment required while at the same time minimizing the total power consumption under the premise that forbidden zones should be taken into account. An optimization problem was mathematically formulated to provide the optimal thrust allocation by introducing the corresponding design variables, objective function, and constraints. A hybrid optimization algorithm consisting of a genetic algorithm and a sequential quadratic programming (SQP algorithm was selected and used to solve this problem. The proposed method was evaluated by applying it to a thrust allocation problem for a semisubmersible drilling rig. The results indicate that the proposed method can be used as part of a cost-effective strategy for thrust allocation of the rig.
Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz
2017-10-01
Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.
An efficient second-order SQP method for structural topology optimization
DEFF Research Database (Denmark)
Rojas Labanda, Susana; Stolpe, Mathias
2016-01-01
This article presents a Sequential Quadratic Programming (SQP) solver for structural topology optimization problems named TopSQP. The implementation is based on the general SQP method proposed in Morales et al. J Numer Anal 32(2):553–579 (2010) called SQP+. The topology optimization problem...... nonlinear solvers IPOPT and SNOPT. Numerical experiments on a large set of benchmark problems show good performance of TopSQP in terms of number of function evaluations. In addition, the use of second-order information helps to decrease the objective function value....
An optimization method of VON mapping for energy efficiency and routing in elastic optical networks
Liu, Huanlin; Xiong, Cuilian; Chen, Yong; Li, Changping; Chen, Derun
2018-03-01
To improve resources utilization efficiency, network virtualization in elastic optical networks has been developed by sharing the same physical network for difference users and applications. In the process of virtual nodes mapping, longer paths between physical nodes will consume more spectrum resources and energy. To address the problem, we propose a virtual optical network mapping algorithm called genetic multi-objective optimize virtual optical network mapping algorithm (GM-OVONM-AL), which jointly optimizes the energy consumption and spectrum resources consumption in the process of virtual optical network mapping. Firstly, a vector function is proposed to balance the energy consumption and spectrum resources by optimizing population classification and crowding distance sorting. Then, an adaptive crossover operator based on hierarchical comparison is proposed to improve search ability and convergence speed. In addition, the principle of the survival of the fittest is introduced to select better individual according to the relationship of domination rank. Compared with the spectrum consecutiveness-opaque virtual optical network mapping-algorithm and baseline-opaque virtual optical network mapping algorithm, simulation results show the proposed GM-OVONM-AL can achieve the lowest bandwidth blocking probability and save the energy consumption.
The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing
Directory of Open Access Journals (Sweden)
Sébastien Bissey
2017-10-01
Full Text Available Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours to prevent the need to extend the grid and thus save considerable costs. This article points out the relevance of a fuzzy logic algorithm to efficiently predict short term load consumption (STLC. This approach is the cornerstone of a new home energy management (HEM algorithm which is able to optimize the cost of electricity consumption, while smoothing the peak demand. The fuzzy logic modeling involves a strong reliance on a complete database of real consumption data from many instrumented show houses. The proposed HEM algorithm enables any end-user to manage his electricity consumption with a high degree of flexibility and transparency, and “reshape” the load profile. For example, this can be mainly achieved using smart control of a storage system coupled with remote management of the electric appliances. The simulation results demonstrate that an accurate prediction of STLC gives the possibility of achieving optimal planning and operation of the HEM system.
Optimization of an Efficient Non-Tissue Culture Transformation Method for Brassica Juncea
International Nuclear Information System (INIS)
Naeem, I.; Munir, I.; Iqbal, A.; Ullah, F.
2016-01-01
The major hurdles in successful in vitro transformation of Brassica juncea through standard tissue culture (STC) method are: culture contamination, somaclonal variations, and lack of expertise. Moreover, the current STC method is time consuming and needs continuous electricity. In the present study, the in planta transformation method through floral dip with or without vacuum infiltration was optimized for successful transformation of B. juncea. The B. juncea CV RAYA Anmol was used for transformation through Agrobacterium tumefaciens strain GV3101 harboring the binary vector plasmid pBinGlyBar4-EADcT. Based on the resistance reaction to the herbicide Basta, 20 and 40 resistant seedlings were obtained from 2000 seed germinated from the plants transformed through floral dip and vacuum infiltration methods, respectively. The PCR analyses further confirmed the presence of transgene in 3 floral dipped plants without vacuum infiltration and 17 floral dipped plants with vacuum infiltration, giving the transformation frequencies of 1.5*10/sup -3/ and 8.5*10/sup -3/, respectively. This method, which avoids tissue culture, will reduce the somaclonal variation accompanying prolonged culture of cells in a dedifferentiated state, will facilitate functional genomics and improvement of Brassica juncea with novel desirable traits while reducing time and expense. (author)
Optimization analysis of propulsion motor control efficiency
Directory of Open Access Journals (Sweden)
CAI Qingnan
2017-12-01
Full Text Available [Objectives] This paper aims to strengthen the control effect of propulsion motors and decrease the energy used during actual control procedures.[Methods] Based on the traditional propulsion motor equivalence circuit, we increase the iron loss current component, introduce the definition of power matching ratio, calculate the highest efficiency of a motor at a given speed and discuss the flux corresponding to the power matching ratio with the highest efficiency. In the original motor vector efficiency optimization control module, an efficiency optimization control module is added so as to achieve motor efficiency optimization and energy conservation.[Results] MATLAB/Simulink simulation data shows that the efficiency optimization control method is suitable for most conditions. The operation efficiency of the improved motor model is significantly higher than that of the original motor model, and its dynamic performance is good.[Conclusions] Our motor efficiency optimization control method can be applied in engineering to achieve energy conservation.
Directory of Open Access Journals (Sweden)
J.-M. Beckers
2014-10-01
Full Text Available We present a method in which the optimal interpolation of multi-scale processes can be expanded into a succession of simpler interpolations. First, we prove how the optimal analysis of a superposition of two processes can be obtained by different mathematical formulations involving iterations and analysis focusing on a single process. From the different mathematical equivalent formulations, we then select the most efficient ones by analyzing the behavior of the different possibilities in a simple and well-controlled test case. The clear guidelines deduced from this experiment are then applied to a real situation in which we combine large-scale analysis of hourly Spinning Enhanced Visible and Infrared Imager (SEVIRI satellite images using data interpolating empirical orthogonal functions (DINEOF with a local optimal interpolation using a Gaussian covariance. It is shown that the optimal combination indeed provides the best reconstruction and can therefore be exploited to extract the maximum amount of useful information from the original data.
International Nuclear Information System (INIS)
Guardiola, Carlos; Climent, Héctor; Pla, Benjamín; Reig, Alberto
2017-01-01
Highlights: • Optimal Control is applied for heat release shaping in internal combustion engines. • Optimal Control allows to assess the engine performance with a realistic reference. • The proposed method gives a target heat release law to define control strategies. - Abstract: The present paper studies the optimal heat release law in a Diesel engine to maximise the indicated efficiency subject to different constraints, namely: maximum cylinder pressure, maximum cylinder pressure derivative, and NO_x emission restrictions. With this objective, a simple but also representative model of the combustion process has been implemented. The model consists of a 0D energy balance model aimed to provide the pressure and temperature evolutions in the high pressure loop of the engine thermodynamic cycle from the gas conditions at the intake valve closing and the heat release law. The gas pressure and temperature evolutions allow to compute the engine efficiency and NO_x emissions. The comparison between model and experimental results shows that despite the model simplicity, it is able to reproduce the engine efficiency and NO_x emissions. After the model identification and validation, the optimal control problem is posed and solved by means of Dynamic Programming (DP). Also, if only pressure constraints are considered, the paper proposes a solution that reduces the computation cost of the DP strategy in two orders of magnitude for the case being analysed. The solution provides a target heat release law to define injection strategies but also a more realistic maximum efficiency boundary than the ideal thermodynamic cycles usually employed to estimate the maximum engine efficiency.
Stochastic optimization methods
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.
A cost-efficient method to optimize package size in emerging markets
Gamez-Alban, H.M.; Soto-Cardona, O.C.; Mejia Argueta, C.; Sarmiento, A.T.
2015-01-01
Packaging links the entire supply chain and coordinates all participants in the process to give a flexible and effective response to customer needs in order to maximize satisfaction at optimal cost. This research proposes an optimization model to define the minimum total cost combination of outer
Li, Gang; Yu, Yue; Zhang, Cui; Lin, Ling
2017-09-01
The oxygen saturation is one of the important parameters to evaluate human health. This paper presents an efficient optimization method that can improve the accuracy of oxygen saturation measurement, which employs an optical frequency division triangular wave signal as the excitation signal to obtain dynamic spectrum and calculate oxygen saturation. In comparison to the traditional method measured RMSE (root mean square error) of SpO2 which is 0.1705, this proposed method significantly reduced the measured RMSE which is 0.0965. It is notable that the accuracy of oxygen saturation measurement has been improved significantly. The method can simplify the circuit and bring down the demand of elements. Furthermore, it has a great reference value on improving the signal to noise ratio of other physiological signals.
Practical methods of optimization
Fletcher, R
2013-01-01
Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practical aspects in conjunction with the heuristics useful in making them perform more reliably and efficiently. To this end, it presents comparative numerical studies to give readers a feel for possibile applications and to illustrate the problems in assessing evidence. Also provides theoretical background which provides insights into how methods are derived. This edition offers rev
Nzisabira, Jonathan; Louvigny, Yannick; Duysinx, Pierre
2008-01-01
The electric vehicles (EV) and sometimes the hybrid electric vehicle (HEV) technologies are environmentally very efficient but can not succeed on the market because of a smaller ability to satisfy customer’s requirements. Comparison of clean technologies in automotive and transportation systems has been measured using different analysis tools such as LCA (life cycle analysis). However, these instruments never account for the user’s satisfaction which partly explains the market acceptance prob...
Energy Technology Data Exchange (ETDEWEB)
Shen, Yanting, E-mail: shenyanting798@126.com [Research Center for Learning Science, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); State Key Laboratory of Bioelectronics, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); Tian, Fei, E-mail: 642807827@qq.com [Research Center for Learning Science, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); Tu, Jing, E-mail: jtu@seu.edu.cn [State Key Laboratory of Bioelectronics, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); Li, Rui, E-mail: lirui901113@163.com [Research Center for Learning Science, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); Chen, Zhenzhu, E-mail: zzchen_seu@163.com [Research Center for Learning Science, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); Bai, Yunfei, E-mail: whitecf@seu.edu.cn [State Key Laboratory of Bioelectronics, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); Ge, Qinyu, E-mail: geqinyu@seu.edu.cn [State Key Laboratory of Bioelectronics, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China); Lu, Zuhong, E-mail: zhlu@seu.edu.cn [State Key Laboratory of Bioelectronics, Southeast University, Sipailou Road no. 2, Nanjing, Jiangsu Province 210096 (China)
2017-06-22
The reaction temperature is one of the main factors that affect the stability of emulsion PCR (emPCR). Focusing on this point, we applied the “DNA breathing” mechanism in BEAMing (Bead, Emulsion, Amplification, and Magnetic) and proposed a more stable emulsion amplification method. Compared to the conventional emPCR, this method provided excellent results. Firstly, more stable emulsion system resulted in higher percentage of single-molecular amplifications (73.17%). Secondly, an ordinary temperature-controlling device was enough. Our outcome showed that the reaction temperature of this method was not strict so that the ordinary temperature-controlling device was enough for it (the heat block sets vs. the PCR instrument: 13.140 ± 0.110 vs. 13.008 ± 0.039, P = 0.120). Thirdly, the single-biotinylated emP{sub 1} coated streptavidin beads were stable enough to be used for this method (the control temperature vs. the reaction temperature: 2967.91 ± 409.045 vs. 3026.22 ± 442.129, P = 0.334), which could replace the double-biotinylated emP{sub 1} coated beads and was benefit for saving cost. In conclusion, the method presented here with stable emulsion system, simplified temperature-controlling device, and decreased investment would be a highly streamlined and inexpensive option for future single-molecular amplification based researches. - Highlights: • A breathing-based isothermal emulsion amplification (BIEA) method was developed. • BIEA showed excellent properties compared with conventional amplification method. • Terminal breathing of DNA duplex was firstly used in emulsion amplification.
An efficient fringe integral equation method for optimizing the antenna location on complex bodies
DEFF Research Database (Denmark)
Jørgensen, Erik; Meincke, Peter; Breinbjerg, Olav
2001-01-01
The radiation pattern of an antenna mounted nearby, or directly on, a complex three-dimensional (3D) structure can be significantly influenced by this structure. Integral equations combined with the method of moments (MoM) provide an accurate means for calculating the scattering from the structures...... in such applications. The structure is then modelled by triangular or rectangular surface patches with corresponding surface current expansion functions. A MoM matrix which is independent of the antenna location can be obtained by modelling the antenna as an impressed electric or magnetic source, e.g., a slot antenna...... can be modelled by a magnetic Hertzian dipole. For flush-mounted antennas, or antennas mounted in close vicinity of the scattering structure, the nearby impressed source induces a highly peaked surface current on the scattering structure. For the low-order basis functions usually applied...
On the efficiency of chaos optimization algorithms for global optimization
International Nuclear Information System (INIS)
Yang Dixiong; Li Gang; Cheng Gengdong
2007-01-01
Chaos optimization algorithms as a novel method of global optimization have attracted much attention, which were all based on Logistic map. However, we have noticed that the probability density function of the chaotic sequences derived from Logistic map is a Chebyshev-type one, which may affect the global searching capacity and computational efficiency of chaos optimization algorithms considerably. Considering the statistical property of the chaotic sequences of Logistic map and Kent map, the improved hybrid chaos-BFGS optimization algorithm and the Kent map based hybrid chaos-BFGS algorithm are proposed. Five typical nonlinear functions with multimodal characteristic are tested to compare the performance of five hybrid optimization algorithms, which are the conventional Logistic map based chaos-BFGS algorithm, improved Logistic map based chaos-BFGS algorithm, Kent map based chaos-BFGS algorithm, Monte Carlo-BFGS algorithm, mesh-BFGS algorithm. The computational performance of the five algorithms is compared, and the numerical results make us question the high efficiency of the chaos optimization algorithms claimed in some references. It is concluded that the efficiency of the hybrid optimization algorithms is influenced by the statistical property of chaotic/stochastic sequences generated from chaotic/stochastic algorithms, and the location of the global optimum of nonlinear functions. In addition, it is inappropriate to advocate the high efficiency of the global optimization algorithms only depending on several numerical examples of low-dimensional functions
Inoue, Kaoru; Ogata, Kenji; Kato, Toshiji
When the motor speed is reduced by using a regenerative brake, the mechanical energy of rotation is converted to the electrical energy. When the regenerative torque is large, the corresponding current increases so that the copper loss also becomes large. On the other hand, the damping effect of rotation increases according to the time elapse when the regenerative torque is small. In order to use the limited energy effectively, an optimal regenerative torque should be discussed in order to regenerate electrical energy as much as possible. This paper proposes a design methodology of a regenerative torque for an induction motor to maximize the regenerative electric energy by means of the variational method. Similarly, an optimal torque for acceleration is derived in order to minimize the energy to drive. Finally, an efficient motor drive system with the proposed optimal torque and the power storage system stabilizing the DC link voltage will be proposed. The effectiveness of the proposed methods are illustrated by both simulations and experiments.
Directory of Open Access Journals (Sweden)
H Javadikia
2017-05-01
reaction. Response surface methodology: Three important settings of reactor were considered to optimize reactor performance, which include: inlet flow to reactor, reactor rotational speed and the fluid cycle time in the system. Each set was considered at three levels. The factorial design was used to the analysis without any repeat, there will be 27 situations that because of the cost of analysis per sample by GC, practically not possible to do it. Therefore, response surface methodology was used by Design Expert software. In the other words, after defining the number of variables and their boundaries, software determined the number of necessary tests and the value of the relevant variables. Results and Discussion Three parameters include the inlet flow to reactor, reactor rotational speed and the fluid cycle time in the system were considered as input variables and performance of reactor as outcome in analyzing of extracted data from the reactor and GC by Design Expert software. The results of tests and optimization by software indicated that in 3.51 minutes as retention time of the raw material of biodiesel fuel in the system, the method of transesterification reaction had more than 88% Methyl ester and this represents an improvement in reaction time of biodiesel production. This method has very low retention time rather than biodiesel fuel production in conventional batch reactors that it takes 20 minutes to more than one hour. Conclusions According to the researches, efficiency of biodiesel fuel production in hydrodynamic cavitation reactors is higher than ultrasonic reactors so in this study, the settings of hydrodynamic reactor were investigated so that the settings were optimized in production of biodiesel fuel. Sunflower oil was used in this research. The molar ratio of Methanol to oil was 6 to 1 and sodium hydroxide as a catalyst was used. Three important settings of reactor were considered which include: inlet flow to reactor, reactor rotational speed and the
Directory of Open Access Journals (Sweden)
Szwed Łukasz P.
2014-09-01
Full Text Available Malt extracts and malt concentrates have a broad range of application in food industry. Those products are obtained by methods similar to brewing worts. The possible reduction of cost can be achieved by application of malt substitutes likewise in brewing industry. As the malt concentrates for food industry do not have to fulfill strict norms for beer production it is possible to produce much cheaper products. It was proved that by means of mathematic optimization it is possible to determine the optimal share of unmalted material for cheap yet effective production of wort.
Methods of mathematical optimization
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.
Efficient optimization of electrostatic interactions between biomolecules.
Energy Technology Data Exchange (ETDEWEB)
Bardhan, J. P.; Altman, M. D.; White, J. K.; Tidor, B.; Mathematics and Computer Science; MIT
2007-01-01
We present a PDE-constrained approach to optimizing the electrostatic interactions between two biomolecules. These interactions play important roles in the determination of binding affinity and specificity, and are therefore of significant interest when designing a ligand molecule to bind tightly to a receptor. Using a popular continuum model and physically reasonable assumptions, the electrostatic component of the binding free energy is a convex, quadratic function of the ligand charge distribution. Traditional optimization methods require exhaustive pre-computation, and the expense has precluded a full exploration of the promise of electrostatic optimization in biomolecule analysis and design. In this paper we describe an approach in which the electrostatic simulations and optimization problem are solved simultaneously; unlike many PDE- constrained optimization frameworks, the proposed method does not incorporate the PDE as a set of equality constraints. This co-optimization approach can be used by itself to solve unconstrained problems or those with linear equality constraints, or in conjunction with primal-dual interior point methods to solve problems with inequality constraints. Model problems demonstrate that the co-optimization method is computationally efficient and can be used to solve realistic problems.
Improving the efficiency of aerodynamic shape optimization
Burgreen, Greg W.; Baysal, Oktay; Eleshaky, Mohamed E.
1994-01-01
The computational efficiency of an aerodynamic shape optimization procedure that is based on discrete sensitivity analysis is increased through the implementation of two improvements. The first improvement involves replacing a grid-point-based approach for surface representation with a Bezier-Bernstein polynomial parameterization of the surface. Explicit analytical expressions for the grid sensitivity terms are developed for both approaches. The second improvement proposes the use of Newton's method in lieu of an alternating direction implicit methodology to calculate the highly converged flow solutions that are required to compute the sensitivity coefficients. The modified design procedure is demonstrated by optimizing the shape of an internal-external nozzle configuration. Practically identical optimization results are obtained that are independent of the method used to represent the surface. A substantial factor of 8 decrease in computational time for the optimization process is achieved by implementing both of the design procedure improvements.
An analysis of pavement heat flux to optimize the water efficiency of a pavement-watering method
International Nuclear Information System (INIS)
Hendel, Martin; Colombert, Morgane; Diab, Youssef; Royon, Laurent
2015-01-01
Pavement-watering as a technique of cooling dense urban areas and reducing the urban heat island effect has been studied since the 1990's. The method is currently considered as a potential tool for and climate change adaptation against increasing heat wave intensity and frequency. However, although water consumption necessary to implement this technique is an important aspect for decision makers, optimization of possible watering methods has only rarely been conducted. An analysis of pavement heat flux at a depth of 5 cm and solar irradiance measurements is proposed to attempt to optimize the watering period, cycle frequency and water consumption rate of a pavement-watering method applied in Paris over the summer of 2013. While fine-tuning of the frequency can be conducted on the basis of pavement heat flux observations, the watering rate requires a heat transfer analysis based on a relation established between pavement heat flux and solar irradiance during pavement insolation. From this, it was found that watering conducted during pavement insolation could be optimized to 30-min cycles and water consumption could be reduced by more than 80% while reducing the cooling effect by less than 13%. - Highlights: • The thermal effects of pavement-watering were investigated in Paris, France. • Pavement-watering was found to significantly affect pavement heat flux 5 cm deep. • When insolated, a linear relation was found between heat flux and solar radiation. • Pavement-watering did not alter its slope, but introduced a negative intercept. • Subsequent improvements of the watering period, frequency and rate are proposed
Efficient Iris Localization via Optimization Model
Directory of Open Access Journals (Sweden)
Qi Wang
2017-01-01
Full Text Available Iris localization is one of the most important processes in iris recognition. Because of different kinds of noises in iris image, the localization result may be wrong. Besides this, localization process is time-consuming. To solve these problems, this paper develops an efficient iris localization algorithm via optimization model. Firstly, the localization problem is modeled by an optimization model. Then SIFT feature is selected to represent the characteristic information of iris outer boundary and eyelid for localization. And SDM (Supervised Descent Method algorithm is employed to solve the final points of outer boundary and eyelids. Finally, IRLS (Iterative Reweighted Least-Square is used to obtain the parameters of outer boundary and upper and lower eyelids. Experimental result indicates that the proposed algorithm is efficient and effective.
International Nuclear Information System (INIS)
Jin, S.W.; Li, Y.P.; Huang, G.H.; Hao, Q.; Nie, S.
2015-01-01
Highlights: • Superiority–inferiority full-infinite mixed-integer method is developed. • The method can tackle uncertainties of fuzzy sets, crisp and functional intervals. • The method is applied to a real case of planning energy system. • Effects of energy-conversion efficiency on energy systems are analyzed. • Results can support policy enactment of conversion efficiency improvement. - Abstract: In this study, a superiority–inferiority full-infinite mixed-integer programming (SFMP) method is developed for analyzing the effect of energy conversion efficiency under uncertainty. SFMP can effectively tackle uncertainties expressed as fuzzy sets, crisp intervals and functional intervals, it also can directly reflect relationships among multiple fuzzy sets through varying superiority and inferiority degrees with a high computational efficiency. Then the developed SFMP is applied to a real case of planning energy system for Bayingolin Mongol Autonomous Prefecture, where multiple scenarios related to different energy-conversion efficiency are concerned. Results for energy processing, energy conversion, capacity expansion, pollutant emission and system cost have been generated. It is proved that SFMP is an effective approach to deal with the uncertainties in energy systems with interactive and uncertain characteristics. A variety of uncertainties existed in energy conversion processes and impact factors could affect the modeling result. Results show that improvement of energy-conversion efficiency can effectively facilitate reducing energy resources consumption, optimizing energy generation pattern, decreasing capacity expansion, as well as mitigating pollutant emissions. Results also reveal that, for the study area, electric power has a highest energy saving potential among heating, oil processing, coal washing and refining. Results can help decision makers to generate desired alternatives that can facilitate policy enactment of conversion efficiency
Efficient Reanalysis Procedures in Structural Topology Optimization
DEFF Research Database (Denmark)
Amir, Oded
This thesis examines efficient solution procedures for the structural analysis problem within topology optimization. The research is motivated by the observation that when the nested approach to structural optimization is applied, most of the computational effort is invested in repeated solutions...... on approximate reanalysis. For cases where memory limitations require the utilization of iterative equation solvers, we suggest efficient procedures based on alternative termination criteria for such solvers. These approaches are tested on two- and three-dimensional topology optimization problems including...
2006-05-15
of different evolutionary approaches to multiobjective optimal design are given by Van Veldhuizen ,7 Van Veldhuizen and Lamont,8 and Zitzler and Thiele...and Machine Learning, Addison-Wesley, Boston, 1989. 7. D. A. Van Veldhuizen , "Multiobjective Evolutionary Algorithms: Classifications, Analyses, and...New Innovations," Ph.D. Dissertation, Air Force Institute of Technology, 1999. 39 8. D. A. Van Veldhuizen and G. B. Lamont, "Multiobjective
Energy Technology Data Exchange (ETDEWEB)
Dahlmann, Katrin
2012-11-01
For calculating the climate impact of aviation it is important to consider the effect of so-called non-CO{sub 2} emissions beside the climate effect of carbon dioxide emissions. As the impact of these non-CO{sub 2} emissions strongly depends on the location of the emission, the climate impact is no longer proportional to the total amount of emissions. Therefore it is necessary to use an efficient model which considers the impact of different climate agents as well as their geographically variable impact for calculating the climate impact of aviation emissions. Such a model (AirClim) was expanded to consider primary mode ozone and contrail-cirrus as well as uncertainties in the evaluation of different measures by using a Monte-Carlo simulation. Afterward the mitigation gain of changing flight altitude and speed of nowadays aircrafts was evaluated. This shows that it would be possible to reduce the climate impact by more than 60% by optimizing the flight altitude and speed, leading to an increase in direct operating costs by 32%. A one percentage increase in direct operating cost can results in a 12% reduction in climate impact. (orig.)
Saito, Masatoshi
2010-08-01
This article describes the spectral optimization of dual-energy computed tomography using balanced filters (bf-DECT) to reduce the tube loadings and dose by dedicating to the acquisition of electron density information, which is essential for treatment planning in radiotherapy. For the spectral optimization of bf-DECT, the author calculated the beam-hardening error and air kerma required to achieve a desired noise level in an electron density image of a 50-cm-diameter cylindrical water phantom. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimal combination of tube voltages was 80 kV/140 kV in conjunction with Tb/Hf and Bi/Mo filter pairs; this combination agrees with that obtained in a previous study [M. Saito, "Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method," Med. Phys. 36, 3631-3642 (2009)], although the thicknesses of the filters that yielded a minimum tube output were slightly different from those obtained in the previous study. The resultant tube loading of a low-energy scan of the present bf-DECT significantly decreased from 57.5 to 4.5 times that of a high-energy scan for conventional DECT. Furthermore, the air kerma of bf-DECT could be reduced to less than that of conventional DECT, while obtaining the same figure of merit for the measurement of electron density and effective atomic number. The tube-loading and dose efficiencies of bf-DECT were considerably improved by sacrificing the quality of the noise level in the images of effective atomic number.
Stochastic optimization methods
Marti, Kurt
2008-01-01
Optimization problems arising in practice involve random model parameters. This book features many illustrations, several examples, and applications to concrete problems from engineering and operations research.
An Efficient Algorithm for Unconstrained Optimization
Directory of Open Access Journals (Sweden)
Sergio Gerardo de-los-Cobos-Silva
2015-01-01
Full Text Available This paper presents an original and efficient PSO algorithm, which is divided into three phases: (1 stabilization, (2 breadth-first search, and (3 depth-first search. The proposed algorithm, called PSO-3P, was tested with 47 benchmark continuous unconstrained optimization problems, on a total of 82 instances. The numerical results show that the proposed algorithm is able to reach the global optimum. This work mainly focuses on unconstrained optimization problems from 2 to 1,000 variables.
Analytical methods of optimization
Lawden, D F
2006-01-01
Suitable for advanced undergraduates and graduate students, this text surveys the classical theory of the calculus of variations. It takes the approach most appropriate for applications to problems of optimizing the behavior of engineering systems. Two of these problem areas have strongly influenced this presentation: the design of the control systems and the choice of rocket trajectories to be followed by terrestrial and extraterrestrial vehicles.Topics include static systems, control systems, additional constraints, the Hamilton-Jacobi equation, and the accessory optimization problem. Prereq
Efficient reanalysis techniques for robust topology optimization
DEFF Research Database (Denmark)
Amir, Oded; Sigmund, Ole; Lazarov, Boyan Stefanov
2012-01-01
efficient robust topology optimization procedures based on reanalysis techniques. The approach is demonstrated on two compliant mechanism design problems where robust design is achieved by employing either a worst case formulation or a stochastic formulation. It is shown that the time spent on finite...
Directory of Open Access Journals (Sweden)
maria Beihaghi
2018-03-01
Full Text Available Introduction: Plant tissue culture is a collection of techniques used to maintain or grow plant cells, tissues or organs under sterile conditions on a nutrient culture medium of known composition and widely used to produce clones of a plant in a method known as micropropagation. Plant research often involves growing new plants in a controlled environment. These may be plants that we have genetically altered in some way or may be plants of which we need many copies all exactly alike. These things can be accomplished through tissue culture of small tissue pieces from the plant of interest. These small pieces may come from a single mother plant or they may be the result of genetic transformation of single plant cells which are then encouraged to grow and to ultimately develop into a whole plant. Tissue culture techniques are often used for commercial production of plants as well as for plant research. Tobacco (Nicotiana tabacum L. is one of the most important model plants used in the physiologic, genetic and tissue culture studies. The manipulation of tobacco genetic structure requires an efficient technique of gene transferring and regeneration. Whereas, the tobacco plant is a very effective bioreactor in the production of recombinant proteins, in this research we optimized the best tissue culture system and also, genetic transformation process of this plant. Materials and Methods: Our plant tissue culture protocols, Include helpful information for Murashige and Skoog media, plant growth regulators, plant growth hormones, plant transformation systems, and other products for plant tissue culture. For this purpose, different concentrations of sucrose and 4 combinations of growth regulators (BAP and NAA on callus induction, direct shoot regeneration and rooting were examined in a factorial experiment based on completely randomized design with 3 replications. The sensitivity of tobacco explants to kanamycin was examined through the cultivation of them
Interactive Nonlinear Multiobjective Optimization Methods
Miettinen, Kaisa; Hakanen, Jussi; Podkopaev, Dmitry
2016-01-01
An overview of interactive methods for solving nonlinear multiobjective optimization problems is given. In interactive methods, the decision maker progressively provides preference information so that the most satisfactory Pareto optimal solution can be found for her or his. The basic features of several methods are introduced and some theoretical results are provided. In addition, references to modifications and applications as well as to other methods are indicated. As the...
Efficiency Optimization in Class-D Audio Amplifiers
DEFF Research Database (Denmark)
Yamauchi, Akira; Knott, Arnold; Jørgensen, Ivan Harald Holger
2015-01-01
This paper presents a new power efficiency optimization routine for designing Class-D audio amplifiers. The proposed optimization procedure finds design parameters for the power stage and the output filter, and the optimum switching frequency such that the weighted power losses are minimized under...... the given constraints. The optimization routine is applied to minimize the power losses in a 130 W class-D audio amplifier based on consumer behavior investigations, where the amplifier operates at idle and low power levels most of the time. Experimental results demonstrate that the optimization method can...... lead to around 30 % of efficiency improvement at 1.3 W output power without significant effects on both audio performance and the efficiency at high power levels....
Optimization methods for logical inference
Chandru, Vijay
2011-01-01
Merging logic and mathematics in deductive inference-an innovative, cutting-edge approach. Optimization methods for logical inference? Absolutely, say Vijay Chandru and John Hooker, two major contributors to this rapidly expanding field. And even though ""solving logical inference problems with optimization methods may seem a bit like eating sauerkraut with chopsticks. . . it is the mathematical structure of a problem that determines whether an optimization model can help solve it, not the context in which the problem occurs."" Presenting powerful, proven optimization techniques for logic in
Efficient evolutionary algorithms for optimal control
López Cruz, I.L.
2002-01-01
If optimal control problems are solved by means of gradient based local search methods, convergence to local solutions is likely. Recently, there has been an increasing interest in the use
Efficient search by optimized intermittent random walks
International Nuclear Information System (INIS)
Oshanin, Gleb; Lindenberg, Katja; Wio, Horacio S; Burlatsky, Sergei
2009-01-01
We study the kinetics for the search of an immobile target by randomly moving searchers that detect it only upon encounter. The searchers perform intermittent random walks on a one-dimensional lattice. Each searcher can step on a nearest neighbor site with probability α or go off lattice with probability 1 - α to move in a random direction until it lands back on the lattice at a fixed distance L away from the departure point. Considering α and L as optimization parameters, we seek to enhance the chances of successful detection by minimizing the probability P N that the target remains undetected up to the maximal search time N. We show that even in this simple model, a number of very efficient search strategies can lead to a decrease of P N by orders of magnitude upon appropriate choices of α and L. We demonstrate that, in general, such optimal intermittent strategies are much more efficient than Brownian searches and are as efficient as search algorithms based on random walks with heavy-tailed Cauchy jump-length distributions. In addition, such intermittent strategies appear to be more advantageous than Levy-based ones in that they lead to more thorough exploration of visited regions in space and thus lend themselves to parallelization of the search processes.
Optimization methods in structural design
Rothwell, Alan
2017-01-01
This book offers an introduction to numerical optimization methods in structural design. Employing a readily accessible and compact format, the book presents an overview of optimization methods, and equips readers to properly set up optimization problems and interpret the results. A ‘how-to-do-it’ approach is followed throughout, with less emphasis at this stage on mathematical derivations. The book features spreadsheet programs provided in Microsoft Excel, which allow readers to experience optimization ‘hands-on.’ Examples covered include truss structures, columns, beams, reinforced shell structures, stiffened panels and composite laminates. For the last three, a review of relevant analysis methods is included. Exercises, with solutions where appropriate, are also included with each chapter. The book offers a valuable resource for engineering students at the upper undergraduate and postgraduate level, as well as others in the industry and elsewhere who are new to these highly practical techniques.Whi...
Optimizing Temporal Queries: Efficient Handling of Duplicates
DEFF Research Database (Denmark)
Toman, David; Bowman, Ivan Thomas
2001-01-01
, these query languages are implemented by translating temporal queries into standard relational queries. However, the compiled queries are often quite cumbersome and expensive to execute even using state-of-the- art relational products. This paper presents an optimization technique that produces more efficient...... translated SQL queries by taking into account the properties of the encoding used for temporal attributes. For concreteness, this translation technique is presented in the context of SQL/TP; however, these techniques are also applicable to other temporal query languages....
Chen, Hai-Bin; Ding, Xi-Hong; Pan, Xu; Hayat, Tasawar; Alsaedi, Ahmed; Ding, Yong; Dai, Song-Yuan
2018-01-24
To achieve high-quality perovskite solar cells (PSCs), the morphology and carrier transportation of perovskite films need to be optimized. Herein, C 60 is employed as nucleation sites in PbI 2 precursor solution to optimize the morphology of perovskite films via vapor-assisted deposition process. Accompanying the homogeneous nucleation of PbI 2 , the incorporation of C 60 as heterogeneous nucleation sites can lower the nucleation free energy of PbI 2 , which facilitates the diffusion and reaction between PbI 2 and organic source. Meanwhile, C 60 could enhance carrier transportation and reduce charge recombination in the perovskite layer due to its high electron mobility and conductivity. In addition, the grain sizes of perovskite get larger with C 60 optimizing, which can reduce the grain boundaries and voids in perovskite and prevent the corrosion because of moisture. As a result, we obtain PSCs with a power conversion efficiency (PCE) of 18.33% and excellent stability. The PCEs of unsealed devices drop less than 10% in a dehumidification cabinet after 100 days and remain at 75% of the initial PCE during exposure to ambient air (humidity > 60% RH, temperature > 30 °C) for 30 days.
Dahm, T.; Heimann, S.; Isken, M.; Vasyura-Bathke, H.; Kühn, D.; Sudhaus, H.; Kriegerowski, M.; Daout, S.; Steinberg, A.; Cesca, S.
2017-12-01
Seismic source and moment tensor waveform inversion is often ill-posed or non-unique if station coverage is poor or signals are weak. Therefore, the interpretation of moment tensors can become difficult, if not the full model space is explored, including all its trade-offs and uncertainties. This is especially true for non-double couple components of weak or shallow earthquakes, as for instance found in volcanic, geothermal or mining environments.We developed a bootstrap-based probabilistic optimization scheme (Grond), which is based on pre-calculated Greens function full waveform databases (e.g. fomosto tool, doi.org/10.5880/GFZ.2.1.2017.001). Grond is able to efficiently explore the full model space, the trade-offs and the uncertainties of source parameters. The program is highly flexible with respect to the adaption to specific problems, the design of objective functions, and the diversity of empirical datasets.It uses an integrated, robust waveform data processing based on a newly developed Python toolbox for seismology (Pyrocko, see Heimann et al., 2017, http://doi.org/10.5880/GFZ.2.1.2017.001), and allows for visual inspection of many aspects of the optimization problem. Grond has been applied to the CMT moment tensor inversion using W-phases, to nuclear explosions in Korea, to meteorite atmospheric explosions, to volcano-tectonic events during caldera collapse and to intra-plate volcanic and tectonic crustal events.Grond can be used to optimize simultaneously seismological waveforms, amplitude spectra and static displacements of geodetic data as InSAR and GPS (e.g. KITE, Isken et al., 2017, http://doi.org/10.5880/GFZ.2.1.2017.002). We present examples of Grond optimizations to demonstrate the advantage of a full exploration of source parameter uncertainties for interpretation.
Energy efficiency improvement by gear shifting optimization
Directory of Open Access Journals (Sweden)
Blagojevic Ivan A.
2013-01-01
Full Text Available Many studies have proved that elements of driver’s behavior related to gear selection have considerable influence on the fuel consumption. Optimal gear shifting is a complex task, especially for inexperienced drivers. This paper presents an implemented idea for gear shifting optimization with the aim of fuel consumption minimization with more efficient engine working regimes. Optimized gear shifting enables the best possible relation between vehicle motion regimes and engine working regimes. New theoretical-experimental approach has been developed using On-Board Diagnostic technology which so far has not been used for this purpose. The matrix of driving modes according to which tests were performed is obtained and special data acquisition system and analysis process have been developed. Functional relations between experimental test modes and adequate engine working parameters have been obtained and all necessary operations have been conducted to enable their use as inputs for the designed algorithm. The created Model has been tested in real exploitation conditions on passenger car with Otto fuel injection engine and On-Board Diagnostic connection without any changes on it. The conducted tests have shown that the presented Model has significantly positive effects on fuel consumption which is an important ecological aspect. Further development and testing of the Model allows implementation in wide range of motor vehicles with various types of internal combustion engines.
Optimized systems for energy efficient optical tweezing
Kampmann, R.; Kleindienst, R.; Grewe, A.; Bürger, Elisabeth; Oeder, A.; Sinzinger, S.
2013-03-01
Compared to conventional optics like singlet lenses or even microscope objectives advanced optical designs help to develop properties specifically useful for efficient optical tweezers. We present an optical setup providing a customized intensity distribution optimized with respect to large trapping forces. The optical design concept combines a refractive double axicon with a reflective parabolic focusing mirror. The axicon arrangement creates an annular field distribution and thus clears space for additional integrated observation optics in the center of the system. Finally the beam is focused to the desired intensity distribution by a parabolic ring mirror. The compact realization of the system potentially opens new fields of applications for optical tweezers such as in production industries and micro-nano assembly.
Evolutionary optimization methods for accelerator design
Poklonskiy, Alexey A.
Many problems from the fields of accelerator physics and beam theory can be formulated as optimization problems and, as such, solved using optimization methods. Despite growing efficiency of the optimization methods, the adoption of modern optimization techniques in these fields is rather limited. Evolutionary Algorithms (EAs) form a relatively new and actively developed optimization methods family. They possess many attractive features such as: ease of the implementation, modest requirements on the objective function, a good tolerance to noise, robustness, and the ability to perform a global search efficiently. In this work we study the application of EAs to problems from accelerator physics and beam theory. We review the most commonly used methods of unconstrained optimization and describe the GATool, evolutionary algorithm and the software package, used in this work, in detail. Then we use a set of test problems to assess its performance in terms of computational resources, quality of the obtained result, and the tradeoff between them. We justify the choice of GATool as a heuristic method to generate cutoff values for the COSY-GO rigorous global optimization package for the COSY Infinity scientific computing package. We design the model of their mutual interaction and demonstrate that the quality of the result obtained by GATool increases as the information about the search domain is refined, which supports the usefulness of this model. We Giscuss GATool's performance on the problems suffering from static and dynamic noise and study useful strategies of GATool parameter tuning for these and other difficult problems. We review the challenges of constrained optimization with EAs and methods commonly used to overcome them. We describe REPA, a new constrained optimization method based on repairing, in exquisite detail, including the properties of its two repairing techniques: REFIND and REPROPT. We assess REPROPT's performance on the standard constrained
Efficiency optimized control of medium-size induction motor drives
DEFF Research Database (Denmark)
Abrahamsen, F.; Blaabjerg, Frede; Pedersen, John Kim
2000-01-01
The efficiency of a variable speed induction motor drive can be optimized by adaption of the motor flux level to the load torque. In small drives (<10 kW) this can be done without considering the relatively small converter losses, but for medium-size drives (10-1000 kW) the losses can not be disr......The efficiency of a variable speed induction motor drive can be optimized by adaption of the motor flux level to the load torque. In small drives (... not be disregarded without further analysis. The importance of the converter losses on efficiency optimization in medium-size drives is analyzed in this paper. Based on the experiments with a 90 kW drive it is found that it is not critical if the converter losses are neglected in the control, except...... that the robustness towards load disturbances may unnecessarily be reduced. Both displacement power factor and model-based efficiency optimizing control methods perform well in medium-size drives. The last strategy is also tested on a 22 kW drive with good results....
Energy Technology Data Exchange (ETDEWEB)
Boer, Jan de [Fraunhofer-Institut fuer Bauphysik, Stuttgart (Germany); Aydinli, Sirri [Technische Universitaet Berlin (Germany); Cornelius, Wolfgang [Fachverband Tageslicht und Rauchschutz e.V. (FVLR), Detmold (Germany); Minnerup, Joerg [TRILUX GmbH + Co KG, Arnsberg (Germany); Schornick, Dieter [ZVEI - Zentralverband Elektrotechnik-und Elektronikindustrie e.V., Frankfurt (Germany); Wershoven, Ralf [ERCO Leuchten GmbH, Luedenscheid (Germany); Jakobiak, Roman
2011-08-15
Over the last years - on national as well as on international level - integrated rating methods (daylighting as well as artificial lighting) have been developed and transferred into practice, the later was fostered by integration into the corresponding standards (DIN V 18599-4, EN 15193-1) and the methods being referenced by national regulations like the German Building Energy Conservation Ordinance (EnEV). Emerging new lighting technologies und requirements to further improve the rating procedure pushed the development of additional new efficiency figures. The concept of expense factors has long been available and applied e.g. in the domain of heating systems. Now, as derived in this publication, it is as well assigned to indoor lighting systems. Therefore, from now on, it will be possible to differentiate lighting installations by their net energy and by their final energy demand. The efficiency of the lighting system itself can be described as function of the expense factor. Currently several new LED-products (lamps and luminaires) are introduced to the market of general lighting. In order to enable practitioners to energetically rate these products, the diversity of products has been structured into classes with assigned efficiency figures. Lighting appliances strongly depend on how the considered zone is used. To provide practioners with exemplary solutions (type of lighting system, facade composition, lighting control) a collection of typical appliances as function of zone usage has been established. This collection has been matched to the structure of the German DIN V 18599 standards.
Optimization of aerodynamic efficiency for twist morphing MAV wing
Directory of Open Access Journals (Sweden)
N.I. Ismail
2014-06-01
Full Text Available Twist morphing (TM is a practical control technique in micro air vehicle (MAV flight. However, TM wing has a lower aerodynamic efficiency (CL/CD compared to membrane and rigid wing. This is due to massive drag penalty created on TM wing, which had overwhelmed the successive increase in its lift generation. Therefore, further CL/CDmax optimization on TM wing is needed to obtain the optimal condition for the morphing wing configuration. In this paper, two-way fluid–structure interaction (FSI simulation and wind tunnel testing method are used to solve and study the basic wing aerodynamic performance over (non-optimal TM, membrane and rigid wings. Then, a multifidelity data metamodel based design optimization (MBDO process is adopted based on the Ansys-DesignXplorer frameworks. In the adaptive MBDO process, Kriging metamodel is used to construct the final multifidelity CL/CD responses by utilizing 23 multi-fidelity sample points from the FSI simulation and experimental data. The optimization results show that the optimal TM wing configuration is able to produce better CL/CDmax magnitude by at least 2% than the non-optimal TM wings. The flow structure formation reveals that low TV strength on the optimal TM wing induces low CD generation which in turn improves its overall CL/CDmax performance.
Optimal database locks for efficient integrity checking
DEFF Research Database (Denmark)
Martinenghi, Davide
2004-01-01
In concurrent database systems, correctness of update transactions refers to the equivalent effects of the execution schedule and some serial schedule over the same set of transactions. Integrity constraints add further semantic requirements to the correctness of the database states reached upon...... the execution of update transactions. Several methods for efficient integrity checking and enforcing exist. We show in this paper how to apply one such method to automatically extend update transactions with locks and simplified consistency tests on the locked entities. All schedules produced in this way...
Optimization of Medical Teaching Methods
Directory of Open Access Journals (Sweden)
Wang Fei
2015-12-01
Full Text Available In order to achieve the goal of medical education, medicine and adapt to changes in the way doctors work, with the rapid medical teaching methods of modern science and technology must be reformed. Based on the current status of teaching in medical colleges method to analyze the formation and development of medical teaching methods, characteristics, about how to achieve optimal medical teaching methods for medical education teachers and management workers comprehensive and thorough change teaching ideas and teaching concepts provide a theoretical basis.
Directory of Open Access Journals (Sweden)
Fabiano A. S. Oliveira
2014-01-01
Full Text Available This paper describes the optimization of a multiresidue chromatographic analysis for the identification and quantification of 20 pesticides in bovine milk, including three carbamates, a carbamate oxime, six organophosphates, two strobilurins, a pyrethroid, an oxazolidinedione, an aryloxyphenoxypropionate acid/ester, a neonicotinoid, a dicarboximide, and three triazoles. The influences of different chromatographic columns and gradients were evaluated. Furthermore, four different extraction methods were evaluated; each utilized both different solvents, including ethyl acetate, methanol, and acetonitrile, and different workup steps. The best results were obtained by a modified QuEChERS method that lacked a workup step, and that included freezing the sample for 2 hours at -20 ºC. The results were satisfactory, yielding coefficients of variation of less than 20%, with the exception of the 50 µg L-1 sample of famoxadone, and recoveries between 70 and 120%, with the exception of acephate and bifenthrin; however, both analytes exhibited coefficients of variation of less than 20%.
Distributed optimization system and method
Hurtado, John E.; Dohrmann, Clark R.; Robinett, III, Rush D.
2003-06-10
A search system and method for controlling multiple agents to optimize an objective using distributed sensing and cooperative control. The search agent can be one or more physical agents, such as a robot, and can be software agents for searching cyberspace. The objective can be: chemical sources, temperature sources, radiation sources, light sources, evaders, trespassers, explosive sources, time dependent sources, time independent sources, function surfaces, maximization points, minimization points, and optimal control of a system such as a communication system, an economy, a crane, and a multi-processor computer.
Optimal control linear quadratic methods
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
Efficient topology optimization in MATLAB using 88 lines of code
DEFF Research Database (Denmark)
Andreassen, Erik; Clausen, Anders; Schevenels, Mattias
2011-01-01
The paper presents an efficient 88 line MATLAB code for topology optimization. It has been developed using the 99 line code presented by Sigmund (Struct Multidisc Optim 21(2):120–127, 2001) as a starting point. The original code has been extended by a density filter, and a considerable improvemen...... of the basic code to include recent PDE-based and black-and-white projection filtering methods. The complete 88 line code is included as an appendix and can be downloaded from the web site www.topopt.dtu.dk....
Mathematical efficiency calibration with uncertain source geometries using smart optimization
International Nuclear Information System (INIS)
Menaa, N.; Bosko, A.; Bronson, F.; Venkataraman, R.; Russ, W. R.; Mueller, W.; Nizhnik, V.; Mirolo, L.
2011-01-01
The In Situ Object Counting Software (ISOCS), a mathematical method developed by CANBERRA, is a well established technique for computing High Purity Germanium (HPGe) detector efficiencies for a wide variety of source shapes and sizes. In the ISOCS method, the user needs to input the geometry related parameters such as: the source dimensions, matrix composition and density, along with the source-to-detector distance. In many applications, the source dimensions, the matrix material and density may not be well known. Under such circumstances, the efficiencies may not be very accurate since the modeled source geometry may not be very representative of the measured geometry. CANBERRA developed an efficiency optimization software known as 'Advanced ISOCS' that varies the not well known parameters within user specified intervals and determines the optimal efficiency shape and magnitude based on available benchmarks in the measured spectra. The benchmarks could be results from isotopic codes such as MGAU, MGA, IGA, or FRAM, activities from multi-line nuclides, and multiple counts of the same item taken in different geometries (from the side, bottom, top etc). The efficiency optimization is carried out using either a random search based on standard probability distributions, or using numerical techniques that carry out a more directed (referred to as 'smart' in this paper) search. Measurements were carried out using representative source geometries and radionuclide distributions. The radionuclide activities were determined using the optimum efficiency and compared against the true activities. The 'Advanced ISOCS' method has many applications among which are: Safeguards, Decommissioning and Decontamination, Non-Destructive Assay systems and Nuclear reactor outages maintenance. (authors)
Shape optimization for aerodynamic efficiency and low observability
Vinh, Hoang; Van Dam, C. P.; Dwyer, Harry A.
1993-01-01
Field methods based on the finite-difference approximations of the time-domain Maxwell's equations and the potential-flow equation have been developed to solve the multidisciplinary problem of airfoil shaping for aerodynamic efficiency and low radar cross section (RCS). A parametric study and an optimization study employing the two analysis methods are presented to illustrate their combined capabilities. The parametric study shows that for frontal radar illumination, the RCS of an airfoil is independent of the chordwise location of maximum thickness but depends strongly on the maximum thickness, leading-edge radius, and leadingedge shape. In addition, this study shows that the RCS of an airfoil can be reduced without significant effects on its transonic aerodynamic efficiency by reducing the leading-edge radius and/or modifying the shape of the leading edge. The optimization study involves the minimization of wave drag for a non-lifting, symmetrical airfoil with constraints on the airfoil maximum thickness and monostatic RCS. This optimization study shows that the two analysis methods can be used effectively to design aerodynamically efficient airfoils with certain desired RCS characteristics.
Air conditioning with methane: Efficiency and economics optimization parameters
International Nuclear Information System (INIS)
Mastrullo, R.; Sasso, M.; Sibilio, S.; Vanoli, R.
1992-01-01
This paper presents an efficiency and economics evaluation method for methane fired cooling systems. Focus is on direct flame two staged absorption systems and alternative engine driven compressor sets. Comparisons are made with conventional vapour compression plants powered by electricity supplied by the national grid. A first and second law based thermodynamics analysis is made in which fuel use coefficients and exergy yields are determined. The economics analysis establishes annual energy savings, unit cooling energy production costs, payback periods and economics/efficiency optimization curves useful for preliminary feasibility studies
Energy-efficient cooking methods
Energy Technology Data Exchange (ETDEWEB)
De, Dilip K. [Department of Physics, University of Jos, P.M.B. 2084, Jos, Plateau State (Nigeria); Muwa Shawhatsu, N. [Department of Physics, Federal University of Technology, Yola, P.M.B. 2076, Yola, Adamawa State (Nigeria); De, N.N. [Department of Mechanical and Aerospace Engineering, The University of Texas at Arlington, Arlington, TX 76019 (United States); Ikechukwu Ajaeroh, M. [Department of Physics, University of Abuja, Abuja (Nigeria)
2013-02-15
Energy-efficient new cooking techniques have been developed in this research. Using a stove with 649{+-}20 W of power, the minimum heat, specific heat of transformation, and on-stove time required to completely cook 1 kg of dry beans (with water and other ingredients) and 1 kg of raw potato are found to be: 710 {+-}kJ, 613 {+-}kJ, and 1,144{+-}10 s, respectively, for beans and 287{+-}12 kJ, 200{+-}9 kJ, and 466{+-}10 s for Irish potato. Extensive researches show that these figures are, to date, the lowest amount of heat ever used to cook beans and potato and less than half the energy used in conventional cooking with a pressure cooker. The efficiency of the stove was estimated to be 52.5{+-}2 %. Discussion is made to further improve the efficiency in cooking with normal stove and solar cooker and to save food nutrients further. Our method of cooking when applied globally is expected to contribute to the clean development management (CDM) potential. The approximate values of the minimum and maximum CDM potentials are estimated to be 7.5 x 10{sup 11} and 2.2 x 10{sup 13} kg of carbon credit annually. The precise estimation CDM potential of our cooking method will be reported later.
ProxImaL: efficient image optimization using proximal algorithms
Heide, Felix
2016-07-11
Computational photography systems are becoming increasingly diverse, while computational resources-for example on mobile platforms-are rapidly increasing. As diverse as these camera systems may be, slightly different variants of the underlying image processing tasks, such as demosaicking, deconvolution, denoising, inpainting, image fusion, and alignment, are shared between all of these systems. Formal optimization methods have recently been demonstrated to achieve state-of-the-art quality for many of these applications. Unfortunately, different combinations of natural image priors and optimization algorithms may be optimal for different problems, and implementing and testing each combination is currently a time-consuming and error-prone process. ProxImaL is a domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety of linear and nonlinear image formation models and cost functions, advanced image priors, and noise models. The compiler intelligently chooses the best way to translate a problem formulation and choice of optimization algorithm into an efficient solver implementation. In applications to the image processing pipeline, deconvolution in the presence of Poisson-distributed shot noise, and burst denoising, we show that a few lines of ProxImaL code can generate highly efficient solvers that achieve state-of-the-art results. We also show applications to the nonlinear and nonconvex problem of phase retrieval.
Methods for Distributed Optimal Energy Management
DEFF Research Database (Denmark)
Brehm, Robert
The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast to convent......The presented research deals with the fundamental underlying methods and concepts of how the growing number of distributed generation units based on renewable energy resources and distributed storage devices can be most efficiently integrated into the existing utility grid. In contrast...... to conventional centralised optimal energy flow management systems, here-in, focus is set on how optimal energy management can be achieved in a decentralised distributed architecture such as a multi-agent system. Distributed optimisation methods are introduced, targeting optimisation of energy flow in virtual......-consumption of renewable energy resources in low voltage grids. It can be shown that this method prevents mutual discharging of batteries and prevents peak loads, a supervisory control instance can dictate the level of autarchy from the utility grid. Further it is shown that the problem of optimal energy flow management...
On-line efficiency optimization of a synchronous reluctance motor
Energy Technology Data Exchange (ETDEWEB)
Lubin, Thierry; Razik, Hubert; Rezzoug, Abderrezak [Groupe de Recherche en Electrotechnique et Electronique de Nancy, GREEN, CNRS-UMR 7037, Universite Henri Poincare, BP 239, 54506 Vandoeuvre-les-Nancy Cedex (France)
2007-04-15
This paper deals with an on-line optimum-efficiency control of a synchronous reluctance motor drive. The input power minimization control is implemented with a search controller using Fibonacci search algorithm. It searches the optimal reference value of the d-axis stator current for which the input power is minimum. The input power is calculated from the measured dc-bus current and dc-bus voltage of the inverter. A rotor-oriented vector control of the synchronous reluctance machine with the optimization efficiency controller is achieved with a DSP board (TMS302C31). Experimental results are presented to validate the proposed control methods. It is shown that stability problems can appear during the search process. (author)
Improving the efficiency of aerodynamic shape optimization procedures
Burgreen, Greg W.; Baysal, Oktay; Eleshaky, Mohamed E.
1992-01-01
The computational efficiency of an aerodynamic shape optimization procedure which is based on discrete sensitivity analysis is increased through the implementation of two improvements. The first improvement involves replacing a grid point-based approach for surface representation with a Bezier-Bernstein polynomial parameterization of the surface. Explicit analytical expressions for the grid sensitivity terms are developed for both approaches. The second improvement proposes the use of Newton's method in lieu of an alternating direction implicit (ADI) methodology to calculate the highly converged flow solutions which are required to compute the sensitivity coefficients. The modified design procedure is demonstrated by optimizing the shape of an internal-external nozzle configuration. A substantial factor of 8 decrease in computational time for the optimization process was achieved by implementing both of the design improvements.
A new optimal seam method for seamless image stitching
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.
Efficient methods of piping cleaning
Directory of Open Access Journals (Sweden)
Orlov Vladimir Aleksandrovich
2014-01-01
Full Text Available The article contains the analysis of the efficient methods of piping cleaning of water supply and sanitation systems. Special attention is paid to the ice cleaning method, in course of which biological foil and various mineral and organic deposits are removed due to the ice crust buildup on the inner surface of water supply and drainage pipes. These impurities are responsible for the deterioration of the organoleptic properties of the transported drinking water or narrowing cross-section of drainage pipes. The co-authors emphasize that the use of ice compared to other methods of pipe cleaning has a number of advantages due to the relative simplicity and cheapness of the process, economical efficiency and lack of environmental risk. The equipment for performing ice cleaning is presented, its technological options, terms of cleansing operations, as well as the volumes of disposed pollution per unit length of the water supply and drainage pipelines. It is noted that ice cleaning requires careful planning in the process of cooking ice and in the process of its supply in the pipe. There are specific requirements to its quality. In particular, when you clean drinking water system the ice applied should be hygienically clean and meet sanitary requirements.In pilot projects, in particular, quantitative and qualitative analysis of sediments adsorbed by ice is conducted, as well as temperature and the duration of the process. The degree of pollution of the pipeline was estimated by the volume of the remote sediment on 1 km of pipeline. Cleaning pipelines using ice can be considered one of the methods of trenchless technologies, being a significant alternative to traditional methods of cleaning the pipes. The method can be applied in urban pipeline systems of drinking water supply for the diameters of 100—600 mm, and also to diversion collectors. In the world today 450 km of pipelines are subject to ice cleaning method.Ice cleaning method is simple
Directory of Open Access Journals (Sweden)
Dongxiao Niu
2018-03-01
Full Text Available The electricity market of China is currently in the process of a new institutional reform. Diversified electricity retail entities are gradually being established with the opening of the marketing electricity side. In the face of a complex market environment and fierce competition, the operating efficiency can directly reflect the current market position and development of electricity retail companies. TOPSIS method can make full use of the information of original data, calculate the distance between evaluated objects and the ideal solutions and get the relative proximity, which is generally used in the overall department and comprehensive evaluation of the benefits. Least squares support vector machine (LSSVM, with high convergence precision, helps save the training time of algorithm by solving linear equations and is used to predict the comprehensive evaluation value. Considering the ultimate goal of sustainable development, a comprehensive evaluation model on operating efficiency of electricity retail companies based on the improved TOPSIS method and LSSVM optimized by modified ant colony algorithm is proposed in this paper. Firstly, from the view of sustainable development, an operating efficiency evaluation indicator system is constructed. Secondly, the entropy weight method is applied to empower the indicators objectively. After that, based on the improved TOPSIS method, the reverse problem in the evaluation process is eliminated. According to the relative proximity between the evaluated objects and the absolute ideal solutions, the scores of comprehensive evaluation for operating efficiency can then be ranked. Finally, the LSSVM optimized by modified ant colony algorithm is introduced to realize the simplified expert scoring process and fast calculation in the comprehensive evaluation process, and its improved learning and generalization ability can be used in the comprehensive evaluation of similar projects. The example analysis proves
Optimized method for manufacturing large aspheric surfaces
Zhou, Xusheng; Li, Shengyi; Dai, Yifan; Xie, Xuhui
2007-12-01
Aspheric optics are being used more and more widely in modern optical systems, due to their ability of correcting aberrations, enhancing image quality, enlarging the field of view and extending the range of effect, while reducing the weight and volume of the system. With optical technology development, we have more pressing requirement to large-aperture and high-precision aspheric surfaces. The original computer controlled optical surfacing (CCOS) technique cannot meet the challenge of precision and machining efficiency. This problem has been thought highly of by researchers. Aiming at the problem of original polishing process, an optimized method for manufacturing large aspheric surfaces is put forward. Subsurface damage (SSD), full aperture errors and full band of frequency errors are all in control of this method. Lesser SSD depth can be gained by using little hardness tool and small abrasive grains in grinding process. For full aperture errors control, edge effects can be controlled by using smaller tools and amendment model with material removal function. For full band of frequency errors control, low frequency errors can be corrected with the optimized material removal function, while medium-high frequency errors by using uniform removing principle. With this optimized method, the accuracy of a K9 glass paraboloid mirror can reach rms 0.055 waves (where a wave is 0.6328μm) in a short time. The results show that the optimized method can guide large aspheric surface manufacturing effectively.
Efficient dynamic optimization of logic programs
Laird, Phil
1992-01-01
A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.
Efficient relaxations for joint chance constrained AC optimal power flow
Energy Technology Data Exchange (ETDEWEB)
Baker, Kyri; Toomey, Bridget
2017-07-01
Evolving power systems with increasing levels of stochasticity call for a need to solve optimal power flow problems with large quantities of random variables. Weather forecasts, electricity prices, and shifting load patterns introduce higher levels of uncertainty and can yield optimization problems that are difficult to solve in an efficient manner. Solution methods for single chance constraints in optimal power flow problems have been considered in the literature, ensuring single constraints are satisfied with a prescribed probability; however, joint chance constraints, ensuring multiple constraints are simultaneously satisfied, have predominantly been solved via scenario-based approaches or by utilizing Boole's inequality as an upper bound. In this paper, joint chance constraints are used to solve an AC optimal power flow problem while preventing overvoltages in distribution grids under high penetrations of photovoltaic systems. A tighter version of Boole's inequality is derived and used to provide a new upper bound on the joint chance constraint, and simulation results are shown demonstrating the benefit of the proposed upper bound. The new framework allows for a less conservative and more computationally efficient solution to considering joint chance constraints, specifically regarding preventing overvoltages.
Efficient methods for overlapping group lasso.
Yuan, Lei; Liu, Jun; Ye, Jieping
2013-09-01
The group Lasso is an extension of the Lasso for feature selection on (predefined) nonoverlapping groups of features. The nonoverlapping group structure limits its applicability in practice. There have been several recent attempts to study a more general formulation where groups of features are given, potentially with overlaps between the groups. The resulting optimization is, however, much more challenging to solve due to the group overlaps. In this paper, we consider the efficient optimization of the overlapping group Lasso penalized problem. We reveal several key properties of the proximal operator associated with the overlapping group Lasso, and compute the proximal operator by solving the smooth and convex dual problem, which allows the use of the gradient descent type of algorithms for the optimization. Our methods and theoretical results are then generalized to tackle the general overlapping group Lasso formulation based on the l(q) norm. We further extend our algorithm to solve a nonconvex overlapping group Lasso formulation based on the capped norm regularization, which reduces the estimation bias introduced by the convex penalty. We have performed empirical evaluations using both a synthetic and the breast cancer gene expression dataset, which consists of 8,141 genes organized into (overlapping) gene sets. Experimental results show that the proposed algorithm is more efficient than existing state-of-the-art algorithms. Results also demonstrate the effectiveness of the nonconvex formulation for overlapping group Lasso.
Trajectory Optimization Based on Multi-Interval Mesh Refinement Method
Directory of Open Access Journals (Sweden)
Ningbo Li
2017-01-01
Full Text Available In order to improve the optimization accuracy and convergence rate for trajectory optimization of the air-to-air missile, a multi-interval mesh refinement Radau pseudospectral method was introduced. This method made the mesh endpoints converge to the practical nonsmooth points and decreased the overall collocation points to improve convergence rate and computational efficiency. The trajectory was divided into four phases according to the working time of engine and handover of midcourse and terminal guidance, and then the optimization model was built. The multi-interval mesh refinement Radau pseudospectral method with different collocation points in each mesh interval was used to solve the trajectory optimization model. Moreover, this method was compared with traditional h method. Simulation results show that this method can decrease the dimensionality of nonlinear programming (NLP problem and therefore improve the efficiency of pseudospectral methods for solving trajectory optimization problems.
The computational optimization of heat exchange efficiency in stack chimneys
Energy Technology Data Exchange (ETDEWEB)
Van Goch, T.A.J.
2012-02-15
For many industrial processes, the chimney is the final step before hot fumes, with high thermal energy content, are discharged into the atmosphere. Tapping into this energy and utilizing it for heating or cooling applications, could improve sustainability, efficiency and/or reduce operational costs. Alternatively, an unused chimney, like the monumental chimney at the Eindhoven University of Technology, could serve as an 'energy channeler' once more; it can enhance free cooling by exploiting the stack effect. This study aims to identify design parameters that influence annual heat exchange in such stack chimney applications and optimize these parameters for specific scenarios to maximize the performance. Performance is defined by annual heat exchange, system efficiency and costs. The energy required for the water pump as compared to the energy exchanged, defines the system efficiency, which is expressed in an efficiency coefficient (EC). This study is an example of applying building performance simulation (BPS) tools for decision support in the early phase of the design process. In this study, BPS tools are used to provide design guidance, performance evaluation and optimization. A general method for optimization of simulation models will be studied, and applied in two case studies with different applications (heating/cooling), namely; (1) CERES case: 'Eindhoven University of Technology monumental stack chimney equipped with a heat exchanger, rejects heat to load the cold source of the aquifer system on the campus of the university and/or provides free cooling to the CERES building'; and (2) Industrial case: 'Heat exchanger in an industrial stack chimney, which recoups heat for use in e.g. absorption cooling'. The main research question, addressing the concerns of both cases, is expressed as follows: 'what is the optimal set of design parameters so heat exchange in stack chimneys is optimized annually for the cases in which a
Optimization design of power efficiency of exponential impedance transformer
International Nuclear Information System (INIS)
Wang Meng; Zou Wenkang; Chen Lin; Guan Yongchao; Fu Jiabin; Xie Weiping
2011-01-01
The paper investigates the optimization design of power efficiency of exponential impedance transformer with analytic method and numerical method. In numerical calculation, a sine wave Jantage with hypothesis of rising edge equivalence is regarded as the forward-going Jantage at input of transformer, and its dominant angular frequency is determined by typical rise-time of actual Jantage waveforms. At the same time, dissipative loss in water dielectric is neglected. The numerical results of three typical modes of impedance transformation, viz. linear mode, saturation mode and steep mode,are compared. Pivotal factors which affect the power efficiency of exponential impedance transformer are discussed, and a certain extent quantitative range of intermediate variables and accordance coefficients are obtained. Finally, the paper discusses some important issues in actual design, such as insulation safety factor in structure design, effects of coupling capacitance on impedance calculation, and dissipative loss in water dielectric. (authors)
Exergetic efficiency optimization for an irreversible heat pump ...
Indian Academy of Sciences (India)
This paper deals with the performance analysis and optimization for irreversible heat pumps working on reversed Brayton cycle with constant-temperature heat reservoirs by taking exergetic efficiency as the optimization objective combining exergy concept with finite-time thermodynamics (FTT). Exergetic efficiency is ...
Kantian Optimization, Social Ethos, and Pareto Efficiency
John E. Roemer
2012-01-01
Although evidence accrues in biology, anthropology and experimental economics that homo sapiens is a cooperative species, the reigning assumption in economic theory is that individuals optimize in an autarkic manner (as in Nash and Walrasian equilibrium). I here postulate an interdependent kind of optimizing behavior, called Kantian. It is shown that in simple economic models, when there are negative externalities (such as congestion effects from use of a commonly owned resource) or positive ...
Finite-size effect on optimal efficiency of heat engines.
Tajima, Hiroyasu; Hayashi, Masahito
2017-07-01
The optimal efficiency of quantum (or classical) heat engines whose heat baths are n-particle systems is given by the strong large deviation. We give the optimal work extraction process as a concrete energy-preserving unitary time evolution among the heat baths and the work storage. We show that our optimal work extraction turns the disordered energy of the heat baths to the ordered energy of the work storage, by evaluating the ratio of the entropy difference to the energy difference in the heat baths and the work storage, respectively. By comparing the statistical mechanical optimal efficiency with the macroscopic thermodynamic bound, we evaluate the accuracy of the macroscopic thermodynamics with finite-size heat baths from the statistical mechanical viewpoint. We also evaluate the quantum coherence effect on the optimal efficiency of the cycle processes without restricting their cycle time by comparing the classical and quantum optimal efficiencies.
METHODS OF INTEGRATED OPTIMIZATION MAGLEV TRANSPORT SYSTEMS
Directory of Open Access Journals (Sweden)
A. Lasher
2013-09-01
Full Text Available Purpose. To demonstrate feasibility of the proposed integrated optimization of various MTS parameters to reduce capital investments as well as decrease any operational and maintenance expense. This will make use of MTS reasonable. At present, the Maglev Transport Systems (MTS for High-Speed Ground Transportation (HSGT almost do not apply. Significant capital investments, high operational and maintenance costs are the main reasons why Maglev Transport Systems (MTS are hardly currently used for the High-Speed Ground Transportation (HSGT. Therefore, this article justifies use of Theory of Complex Optimization of Transport (TCOT, developed by one of the co-authors, to reduce MTS costs. Methodology. According to TCOT, authors developed an abstract model of the generalized transport system (AMSTG. This model mathematically determines the optimal balance between all components of the system and thus provides the ultimate adaptation of any transport systems to the conditions of its application. To identify areas for effective use of MTS, by TCOT, the authors developed a dynamic model of distribution and expansion of spheres of effective use of transport systems (DMRRSEPTS. Based on this model, the most efficient transport system was selected for each individual track. The main estimated criterion at determination of efficiency of application of MTS is the size of the specific transportation tariff received from calculation of payback of total given expenses to a standard payback period or term of granting the credit. Findings. The completed multiple calculations of four types of MTS: TRANSRAPID, MLX01, TRANSMAG and TRANSPROGRESS demonstrated efficiency of the integrated optimization of the parameters of such systems. This research made possible expending the scope of effective usage of MTS in about 2 times. The achieved results were presented at many international conferences in Germany, Switzerland, United States, China, Ukraine, etc. Using MTS as an
A new efficient mixture screening design for optimization of media.
Rispoli, Fred; Shah, Vishal
2009-01-01
Screening ingredients for the optimization of media is an important first step to reduce the many potential ingredients down to the vital few components. In this study, we propose a new method of screening for mixture experiments called the centroid screening design. Comparison of the proposed design with Plackett-Burman, fractional factorial, simplex lattice design, and modified mixture design shows that the centroid screening design is the most efficient of all the designs in terms of the small number of experimental runs needed and for detecting high-order interaction among ingredients. (c) 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009.
Adaptive scalarization methods in multiobjective optimization
Eichfelder, Gabriele
2008-01-01
This book presents adaptive solution methods for multiobjective optimization problems based on parameter dependent scalarization approaches. Readers will benefit from the new adaptive methods and ideas for solving multiobjective optimization.
Lean and Efficient Software: Whole-Program Optimization of Executables
2015-09-30
Lean and Efficient Software: Whole-Program Optimization of Executables” Project Summary Report #5 (Report Period: 7/1/2015 to 9/30/2015...TYPE 3. DATES COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Lean and Efficient Software: Whole-Program Optimization of Executables 5a...unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Lean and Efficient Software: Whole-Program
Efficient Load Scheduling Method For Power Management
Directory of Open Access Journals (Sweden)
Vijo M Joy
2015-08-01
Full Text Available An efficient load scheduling method to meet varying power supply needs is presented in this paper. At peak load times the power generation system fails due to its instability. Traditionally we use load shedding process. In load shedding process disconnect the unnecessary and extra loads. The proposed method overcomes this problem by scheduling the load based on the requirement. Artificial neural networks are used for this optimal load scheduling process. For generate economic scheduling artificial neural network has been used because generation of power from each source is economically different. In this the total load required is the inputs of this network and the power generation from each source and power losses at the time of transmission are the output of the neural network. Training and programming of the artificial neural networks are done using MATLAB.
Efficiency Improvements of Antenna Optimization Using Orthogonal Fractional Experiments
Directory of Open Access Journals (Sweden)
Yen-Sheng Chen
2015-01-01
Full Text Available This paper presents an extremely efficient method for antenna design and optimization. Traditionally, antenna optimization relies on nature-inspired heuristic algorithms, which are time-consuming due to their blind-search nature. In contrast, design of experiments (DOE uses a completely different framework from heuristic algorithms, reducing the design cycle by formulating the surrogates of a design problem. However, the number of required simulations grows exponentially if a full factorial design is used. In this paper, a much more efficient technique is presented to achieve substantial time savings. By using orthogonal fractional experiments, only a small subset of the full factorial design is required, yet the resultant response surface models are still effective. The capability of orthogonal fractional experiments is demonstrated through three examples, including two tag antennas for radio-frequency identification (RFID applications and one internal antenna for long-term-evolution (LTE handheld devices. In these examples, orthogonal fractional experiments greatly improve the efficiency of DOE, thereby facilitating the antenna design with less simulation runs.
A Review of Design Optimization Methods for Electrical Machines
Directory of Open Access Journals (Sweden)
Gang Lei
2017-11-01
Full Text Available Electrical machines are the hearts of many appliances, industrial equipment and systems. In the context of global sustainability, they must fulfill various requirements, not only physically and technologically but also environmentally. Therefore, their design optimization process becomes more and more complex as more engineering disciplines/domains and constraints are involved, such as electromagnetics, structural mechanics and heat transfer. This paper aims to present a review of the design optimization methods for electrical machines, including design analysis methods and models, optimization models, algorithms and methods/strategies. Several efficient optimization methods/strategies are highlighted with comments, including surrogate-model based and multi-level optimization methods. In addition, two promising and challenging topics in both academic and industrial communities are discussed, and two novel optimization methods are introduced for advanced design optimization of electrical machines. First, a system-level design optimization method is introduced for the development of advanced electric drive systems. Second, a robust design optimization method based on the design for six-sigma technique is introduced for high-quality manufacturing of electrical machines in production. Meanwhile, a proposal is presented for the development of a robust design optimization service based on industrial big data and cloud computing services. Finally, five future directions are proposed, including smart design optimization method for future intelligent design and production of electrical machines.
Review of design optimization methods for turbomachinery aerodynamics
Li, Zhihui; Zheng, Xinqian
2017-08-01
In today's competitive environment, new turbomachinery designs need to be not only more efficient, quieter, and ;greener; but also need to be developed at on much shorter time scales and at lower costs. A number of advanced optimization strategies have been developed to achieve these requirements. This paper reviews recent progress in turbomachinery design optimization to solve real-world aerodynamic problems, especially for compressors and turbines. This review covers the following topics that are important for optimizing turbomachinery designs. (1) optimization methods, (2) stochastic optimization combined with blade parameterization methods and the design of experiment methods, (3) gradient-based optimization methods for compressors and turbines and (4) data mining techniques for Pareto Fronts. We also present our own insights regarding the current research trends and the future optimization of turbomachinery designs.
Computation of Optimal Monotonicity Preserving General Linear Methods
Ketcheson, David I.
2009-07-01
Monotonicity preserving numerical methods for ordinary differential equations prevent the growth of propagated errors and preserve convex boundedness properties of the solution. We formulate the problem of finding optimal monotonicity preserving general linear methods for linear autonomous equations, and propose an efficient algorithm for its solution. This algorithm reliably finds optimal methods even among classes involving very high order accuracy and that use many steps and/or stages. The optimality of some recently proposed methods is verified, and many more efficient methods are found. We use similar algorithms to find optimal strong stability preserving linear multistep methods of both explicit and implicit type, including methods for hyperbolic PDEs that use downwind-biased operators.
Exergetic optimization of turbofan engine with genetic algorithm method
Energy Technology Data Exchange (ETDEWEB)
Turan, Onder [Anadolu University, School of Civil Aviation (Turkey)], e-mail: onderturan@anadolu.edu.tr
2011-07-01
With the growth of passenger numbers, emissions from the aeronautics sector are increasing and the industry is now working on improving engine efficiency to reduce fuel consumption. The aim of this study is to present the use of genetic algorithms, an optimization method based on biological principles, to optimize the exergetic performance of turbofan engines. The optimization was carried out using exergy efficiency, overall efficiency and specific thrust of the engine as evaluation criteria and playing on pressure and bypass ratio, turbine inlet temperature and flight altitude. Results showed exergy efficiency can be maximized with higher altitudes, fan pressure ratio and turbine inlet temperature; the turbine inlet temperature is the most important parameter for increased exergy efficiency. This study demonstrated that genetic algorithms are effective in optimizing complex systems in a short time.
International Nuclear Information System (INIS)
Suzuki, Tadakazu
1979-11-01
Thirty two programs for linear and nonlinear optimization problems with or without constraints have been developed or incorporated, and their stability, convergence and efficiency have been examined. On the basis of these evaluations, the first version of the optimization code system SCOOP-I has been completed. The SCOOP-I is designed to be an efficient, reliable, useful and also flexible system for general applications. The system enables one to find global optimization point for a wide class of problems by selecting the most appropriate optimization method built in it. (author)
Maximum super angle optimization method for array antenna pattern synthesis
DEFF Research Database (Denmark)
Wu, Ji; Roederer, A. G
1991-01-01
Different optimization criteria related to antenna pattern synthesis are discussed. Based on the maximum criteria and vector space representation, a simple and efficient optimization method is presented for array and array fed reflector power pattern synthesis. A sector pattern synthesized by a 2...
Qi, Feifei; Jian, Ningge; Qian, Liangliang; Cao, Weixin; Xu, Qian; Li, Jian
2017-09-01
A simple and efficient three-step sample preparation method was developed and optimized for the simultaneous analysis of illegal anionic and cationic dyes (acid orange 7, metanil yellow, auramine-O, and chrysoidine) in food samples. A novel solid-phase extraction (SPE) procedure based on nanofibers mat (NFsM) was proposed after solvent extraction and freeze-salting out purification. The preferred SPE sorbent was selected from five functionalized NFsMs by orthogonal experimental design, and the optimization of SPE parameters was achieved through response surface methodology (RSM) based on the Box-Behnken design (BBD). Under the optimal conditions, the target analytes could be completely adsorbed by polypyrrole-functionalized polyacrylonitrile NFsM (PPy/PAN NFsM), and the eluent was directly analyzed by high-performance liquid chromatography-diode array detection (HPLC-DAD). The limits of detection (LODs) were between 0.002 and 0.01 mg kg -1 , and satisfactory linearity with correlation coefficients (R > 0.99) for each dye in all samples was achieved. Compared with the Chinese standard method and the published methods, the proposed method was simplified greatly with much lower requirement of sorbent (5.0 mg) and organic solvent (2.8 mL) and higher sample preparation speed (10 min/sample), while higher recovery (83.6-116.5%) and precision (RSDs < 7.1%) were obtained. With this developed method, we have successfully detected illegal ionic dyes in three common representative foods: yellow croaker, soybean products, and chili seasonings. Graphical abstract Schematic representation of the process of the three-step sample preparation.
More efficient optimization of long-term water supply portfolios
Kirsch, Brian R.; Characklis, Gregory W.; Dillard, Karen E. M.; Kelley, C. T.
2009-03-01
The use of temporary transfers, such as options and leases, has grown as utilities attempt to meet increases in demand while reducing dependence on the expansion of costly infrastructure capacity (e.g., reservoirs). Earlier work has been done to construct optimal portfolios comprising firm capacity and transfers, using decision rules that determine the timing and volume of transfers. However, such work has only focused on the short-term (e.g., 1-year scenarios), which limits the utility of these planning efforts. Developing multiyear portfolios can lead to the exploration of a wider range of alternatives but also increases the computational burden. This work utilizes a coupled hydrologic-economic model to simulate the long-term performance of a city's water supply portfolio. This stochastic model is linked with an optimization search algorithm that is designed to handle the high-frequency, low-amplitude noise inherent in many simulations, particularly those involving expected values. This noise is detrimental to the accuracy and precision of the optimized solution and has traditionally been controlled by investing greater computational effort in the simulation. However, the increased computational effort can be substantial. This work describes the integration of a variance reduction technique (control variate method) within the simulation/optimization as a means of more efficiently identifying minimum cost portfolios. Random variation in model output (i.e., noise) is moderated using knowledge of random variations in stochastic input variables (e.g., reservoir inflows, demand), thereby reducing the computing time by 50% or more. Using these efficiency gains, water supply portfolios are evaluated over a 10-year period in order to assess their ability to reduce costs and adapt to demand growth, while still meeting reliability goals. As a part of the evaluation, several multiyear option contract structures are explored and compared.
Efficient Training Methods for Conditional Random Fields
National Research Council Canada - National Science Library
Sutton, Charles A
2008-01-01
.... In this thesis, I investigate efficient training methods for conditional random fields with complex graphical structure, focusing on local methods which avoid propagating information globally along the graph...
Optimal Energy Taxation for Environment and Efficiency
Energy Technology Data Exchange (ETDEWEB)
Pak, Y.D. [Korea Energy Economics Institute, Euiwang (Korea)
2001-11-01
Main purpose of this research is to investigate about how to use energy tax system to reconcile environmental protection and economic growth, and promote sustainable development with the emphasis of double dividend hypothesis. As preliminary work to attain this target, in this limited study I will investigate the specific conditions under which double dividend hypothesis can be valid, and set up the model for optimal energy taxation. The model will be used in the simulation process in the next project. As the beginning part in this research, I provide a brief review about energy taxation policies in Sweden, Netherlands, and the United States. From this review it can be asserted that European countries are more aggressive in the application of environmental taxes like energy taxes for a cleaner environment than the United States. In next part I examined the rationale for optimal environmental taxation in the first-best and the second-best setting. Then I investigated energy taxation how it can provoke various distortions in markets and be connected to the marginal environmental damages and environmental taxation. In the next chapter, I examined the environmentally motivated taxation in the point of optimal commodity taxation view. Also I identified the impacts of environmental taxation in various circumstances intensively to find out when the environment tax can yield double dividend after taking into account of even tax-interaction effects. Then it can be found that even though in general the environmental tax exacerbates the distortion in the market rather than alleviates, it can also improve the welfare and the employment under several specific circumstances which are classified as various inefficiencies in the existing tax system. (author). 30 refs.
Gadolinium burnable absorber optimization by the method of conjugate gradients
International Nuclear Information System (INIS)
Drumm, C.R.; Lee, J.C.
1987-01-01
The optimal axial distribution of gadolinium burnable poison in a pressurized water reactor is determined to yield an improved power distribution. The optimization scheme is based on Pontryagin's maximum principle, with the objective function accounting for a target power distribution. The conjugate gradients optimization method is used to solve the resulting Euler-Lagrange equations iteratively, efficiently handling the high degree of nonlinearity of the problem
OPTIMIZATION METHODS AND SEO TOOLS
Directory of Open Access Journals (Sweden)
Maria Cristina ENACHE
2014-06-01
Full Text Available SEO is the activity of optimizing Web pages or whole sites in order to make them more search engine friendly, thus getting higher positions in search results. Search engine optimization (SEO involves designing, writing, and coding a website in a way that helps to improve the volume and quality of traffic to your website from people using search engines. While Search Engine Optimization is the focus of this booklet, keep in mind that it is one of many marketing techniques. A brief overview of other marketing techniques is provided at the end of this booklet.
An Efficient Simulation Method for Rare Events
Rached, Nadhir B.
2015-01-07
Estimating the probability that a sum of random variables (RVs) exceeds a given threshold is a well-known challenging problem. Closed-form expressions for the sum distribution do not generally exist, which has led to an increasing interest in simulation approaches. A crude Monte Carlo (MC) simulation is the standard technique for the estimation of this type of probability. However, this approach is computationally expensive, especially when dealing with rare events. Variance reduction techniques are alternative approaches that can improve the computational efficiency of naive MC simulations. We propose an Importance Sampling (IS) simulation technique based on the well-known hazard rate twisting approach, that presents the advantage of being asymptotically optimal for any arbitrary RVs. The wide scope of applicability of the proposed method is mainly due to our particular way of selecting the twisting parameter. It is worth observing that this interesting feature is rarely satisfied by variance reduction algorithms whose performances were only proven under some restrictive assumptions. It comes along with a good efficiency, illustrated by some selected simulation results comparing the performance of our method with that of an algorithm based on a conditional MC technique.
An Efficient Simulation Method for Rare Events
Rached, Nadhir B.; Benkhelifa, Fatma; Kammoun, Abla; Alouini, Mohamed-Slim; Tempone, Raul
2015-01-01
Estimating the probability that a sum of random variables (RVs) exceeds a given threshold is a well-known challenging problem. Closed-form expressions for the sum distribution do not generally exist, which has led to an increasing interest in simulation approaches. A crude Monte Carlo (MC) simulation is the standard technique for the estimation of this type of probability. However, this approach is computationally expensive, especially when dealing with rare events. Variance reduction techniques are alternative approaches that can improve the computational efficiency of naive MC simulations. We propose an Importance Sampling (IS) simulation technique based on the well-known hazard rate twisting approach, that presents the advantage of being asymptotically optimal for any arbitrary RVs. The wide scope of applicability of the proposed method is mainly due to our particular way of selecting the twisting parameter. It is worth observing that this interesting feature is rarely satisfied by variance reduction algorithms whose performances were only proven under some restrictive assumptions. It comes along with a good efficiency, illustrated by some selected simulation results comparing the performance of our method with that of an algorithm based on a conditional MC technique.
Optimization of a high efficiency FEL amplifier
International Nuclear Information System (INIS)
Schneidmiller, E.A.; Yurkov, M.V.
2014-10-01
The problem of an efficiency increase of an FEL amplifier is now of great practical importance. Technique of undulator tapering in the post-saturation regime is used at the existing X-ray FELs LCLS and SACLA, and is planned for use at the European XFEL, Swiss FEL, and PAL XFEL. There are also discussions on the future of high peak and average power FELs for scientific and industrial applications. In this paper we perform detailed analysis of the tapering strategies for high power seeded FEL amplifiers. Application of similarity techniques allows us to derive universal law of the undulator tapering.
Global optimization methods for engineering design
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.
New drilling optimization technologies make drilling more efficient
Energy Technology Data Exchange (ETDEWEB)
Chen, D.C.-K. [Halliburton Energy Services, Calgary, AB (Canada). Sperry Division
2004-07-01
Several new technologies have been adopted by the upstream petroleum industry in the past two decades in order to optimize drilling operations and improve drilling efficiency. Since financial returns from an oil and gas investment strongly depend on drilling costs, it is important to reduce non-productive time due to stuck pipes, lost circulation, hole cleaning and well bore stability problems. The most notable new technologies are the use of computer-based instrumentation and data acquisition systems, integrated rig site systems and networks, and Measurement-While-Drilling and Logging-While-Drilling (MWD/LWD) systems. Drilling optimization should include solutions for drillstring integrity, hydraulics management and wellbore integrity. New drilling optimization methods emphasize information management and real-time decision making. A recent study for drilling in shallow water in the Gulf of Mexico demonstrates that trouble time accounts for 25 per cent of rig time. This translates to about $1.5 MM U.S. per well. A reduction in trouble time could result in significant cost savings for the industry. This paper presents a case study on vibration prevention to demonstrate how the drilling industry has benefited from new technologies. 13 refs., 10 figs.
Use Conditions and Efficiency Measurements of DC Power Optimizers for Photovoltaic Systems: Preprint
Energy Technology Data Exchange (ETDEWEB)
Deline, C.; MacAlpine, S.
2013-10-01
No consensus standard exists for estimating annual conversion efficiency of DC-DC converters or power optimizers in photovoltaic (PV) applications. The performance benefits of PV power electronics including per-panel DC-DC converters depend in large part on the operating conditions of the PV system, along with the performance characteristics of the power optimizer itself. This work presents acase study of three system configurations that take advantage of the capabilities of DC power optimizers. Measured conversion efficiencies of DC-DC converters are applied to these scenarios to determine the annual weighted operating efficiency. A simplified general method of reporting weighted efficiency is given, based on the California Energy Commission's CEC efficiency rating and severalinput / output voltage ratios. Efficiency measurements of commercial power optimizer products are presented using the new performance metric, along with a description of the limitations of the approach.
Fast sequential Monte Carlo methods for counting and optimization
Rubinstein, Reuven Y; Vaisman, Radislav
2013-01-01
A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the
Quantitative Efficiency Evaluation Method for Transportation Networks
Directory of Open Access Journals (Sweden)
Jin Qin
2014-11-01
Full Text Available An effective evaluation of transportation network efficiency/performance is essential to the establishment of sustainable development in any transportation system. Based on a redefinition of transportation network efficiency, a quantitative efficiency evaluation method for transportation network is proposed, which could reflect the effects of network structure, traffic demands, travel choice, and travel costs on network efficiency. Furthermore, the efficiency-oriented importance measure for network components is presented, which can be used to help engineers identify the critical nodes and links in the network. The numerical examples show that, compared with existing efficiency evaluation methods, the network efficiency value calculated by the method proposed in this paper can portray the real operation situation of the transportation network as well as the effects of main factors on network efficiency. We also find that the network efficiency and the importance values of the network components both are functions of demands and network structure in the transportation network.
Efficient searching in meshfree methods
Olliff, James; Alford, Brad; Simkins, Daniel C.
2018-04-01
Meshfree methods such as the Reproducing Kernel Particle Method and the Element Free Galerkin method have proven to be excellent choices for problems involving complex geometry, evolving topology, and large deformation, owing to their ability to model the problem domain without the constraints imposed on the Finite Element Method (FEM) meshes. However, meshfree methods have an added computational cost over FEM that come from at least two sources: increased cost of shape function evaluation and the determination of adjacency or connectivity. The focus of this paper is to formally address the types of adjacency information that arises in various uses of meshfree methods; a discussion of available techniques for computing the various adjacency graphs; propose a new search algorithm and data structure; and finally compare the memory and run time performance of the methods.
A Concept for Optimizing Behavioural Effectiveness & Efficiency
Barca, Jan Carlo; Rumantir, Grace; Li, Raymond
Both humans and machines exhibit strengths and weaknesses that can be enhanced by merging the two entities. This research aims to provide a broader understanding of how closer interactions between these two entities can facilitate more optimal goal-directed performance through the use of artificial extensions of the human body. Such extensions may assist us in adapting to and manipulating our environments in a more effective way than any system known today. To demonstrate this concept, we have developed a simulation where a semi interactive virtual spider can be navigated through an environment consisting of several obstacles and a virtual predator capable of killing the spider. The virtual spider can be navigated through the use of three different control systems that can be used to assist in optimising overall goal directed performance. The first two control systems use, an onscreen button interface and a touch sensor, respectively to facilitate human navigation of the spider. The third control system is an autonomous navigation system through the use of machine intelligence embedded in the spider. This system enables the spider to navigate and react to changes in its local environment. The results of this study indicate that machines should be allowed to override human control in order to maximise the benefits of collaboration between man and machine. This research further indicates that the development of strong machine intelligence, sensor systems that engage all human senses, extra sensory input systems, physical remote manipulators, multiple intelligent extensions of the human body, as well as a tighter symbiosis between man and machine, can support an upgrade of the human form.
Hybrid intelligent optimization methods for engineering problems
Pehlivanoglu, Yasin Volkan
quantification studies, we improved new mutation strategies and operators to provide beneficial diversity within the population. We called this new approach as multi-frequency vibrational GA or PSO. They were applied to different aeronautical engineering problems in order to study the efficiency of these new approaches. These implementations were: applications to selected benchmark test functions, inverse design of two-dimensional (2D) airfoil in subsonic flow, optimization of 2D airfoil in transonic flow, path planning problems of autonomous unmanned aerial vehicle (UAV) over a 3D terrain environment, 3D radar cross section minimization problem for a 3D air vehicle, and active flow control over a 2D airfoil. As demonstrated by these test cases, we observed that new algorithms outperform the current popular algorithms. The principal role of this multi-frequency approach was to determine which individuals or particles should be mutated, when they should be mutated, and which ones should be merged into the population. The new mutation operators, when combined with a mutation strategy and an artificial intelligent method, such as, neural networks or fuzzy logic process, they provided local and global diversities during the reproduction phases of the generations. Additionally, the new approach also introduced random and controlled diversity. Due to still being population-based techniques, these methods were as robust as the plain GA or PSO algorithms. Based on the results obtained, it was concluded that the variants of the present multi-frequency vibrational GA and PSO were efficient algorithms, since they successfully avoided all local optima within relatively short optimization cycles.
Toward solving the sign problem with path optimization method
Mori, Yuto; Kashiwa, Kouji; Ohnishi, Akira
2017-12-01
We propose a new approach to circumvent the sign problem in which the integration path is optimized to control the sign problem. We give a trial function specifying the integration path in the complex plane and tune it to optimize the cost function which represents the seriousness of the sign problem. We call it the path optimization method. In this method, we do not need to solve the gradient flow required in the Lefschetz-thimble method and then the construction of the integration-path contour arrives at the optimization problem where several efficient methods can be applied. In a simple model with a serious sign problem, the path optimization method is demonstrated to work well; the residual sign problem is resolved and precise results can be obtained even in the region where the global sign problem is serious.
Optimal control of operation efficiency of belt conveyor systems
International Nuclear Information System (INIS)
Zhang, Shirong; Xia, Xiaohua
2010-01-01
The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study.
Optimal control of operation efficiency of belt conveyor systems
Energy Technology Data Exchange (ETDEWEB)
Zhang, Shirong [Department of Automation, Wuhan University, Wuhan 430072 (China); Xia, Xiaohua [Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002 (South Africa)
2010-06-15
The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment or operation levels. Switching control and variable speed control are proposed in literature to improve energy efficiency of belt conveyors. The current implementations mostly focus on lower level control loops or an individual belt conveyor without operational considerations at the system level. In this paper, an optimal switching control and a variable speed drive (VSD) based optimal control are proposed to improve the energy efficiency of belt conveyor systems at the operational level, where time-of-use (TOU) tariff, ramp rate of belt speed and other system constraints are considered. A coal conveying system in a coal-fired power plant is taken as a case study, where great saving of energy cost is achieved by the two optimal control strategies. Moreover, considerable energy saving resulting from VSD based optimal control is also proved by the case study. (author)
Efficient Methods for Fast Shading
Directory of Open Access Journals (Sweden)
ROMANYUK, A.
2008-06-01
Full Text Available On devices without battery consuming and specialized hardware for rendering, it is important to improve the speed and quality so that these methods are suitable for real-time rendering. Furthermore such algorithms are needed on the coming multicore architectures. We show how the methods by Gouraud and Phong, the commonly most used methods for shading, can be improved and made faster for both software rendering as well as simple low energy consuming hardware implementations. Moreover, this paper summarizes the authors' achievements in increasing shading speed and performance and a Bidirectional Reflectance Distribution Function is simplified for faster computing and hardware implementation.
Biologically inspired optimization methods an introduction
Wahde, M
2008-01-01
The advent of rapid, reliable and cheap computing power over the last decades has transformed many, if not most, fields of science and engineering. The multidisciplinary field of optimization is no exception. First of all, with fast computers, researchers and engineers can apply classical optimization methods to problems of larger and larger size. In addition, however, researchers have developed a host of new optimization algorithms that operate in a rather different way than the classical ones, and that allow practitioners to attack optimization problems where the classical methods are either not applicable or simply too costly (in terms of time and other resources) to apply.This book is intended as a course book for introductory courses in stochastic optimization algorithms (in this book, the terms optimization method and optimization algorithm will be used interchangeably), and it has grown from a set of lectures notes used in courses, taught by the author, at the international master programme Complex Ada...
Efficient decomposition and linearization methods for the stochastic transportation problem
International Nuclear Information System (INIS)
Holmberg, K.
1993-01-01
The stochastic transportation problem can be formulated as a convex transportation problem with nonlinear objective function and linear constraints. We compare several different methods based on decomposition techniques and linearization techniques for this problem, trying to find the most efficient method or combination of methods. We discuss and test a separable programming approach, the Frank-Wolfe method with and without modifications, the new technique of mean value cross decomposition and the more well known Lagrangian relaxation with subgradient optimization, as well as combinations of these approaches. Computational tests are presented, indicating that some new combination methods are quite efficient for large scale problems. (authors) (27 refs.)
Tax optimization methods of international companies
Černá, Kateřina
2015-01-01
This thesis is focusing on methods of tax optimization of international companies. These international concerns are endeavoring tax minimization. The disparity of the tax systems gives to these companies a possibility of profit and tax base shifting. At first this thesis compares the differences of tax optimization, aggressive tax planning and tax evasion. Among the areas of the optimization methods, which are described in this thesis, belongs tax residention, dividends, royalty payments, tra...
Modeling and energy efficiency optimization of belt conveyors
International Nuclear Information System (INIS)
Zhang, Shirong; Xia, Xiaohua
2011-01-01
Highlights: → We take optimization approach to improve operation efficiency of belt conveyors. → An analytical energy model, originating from ISO 5048, is proposed. → Then an off-line and an on-line parameter estimation schemes are investigated. → In a case study, six optimization problems are formulated with solutions in simulation. - Abstract: The improvement of the energy efficiency of belt conveyor systems can be achieved at equipment and operation levels. Specifically, variable speed control, an equipment level intervention, is recommended to improve operation efficiency of belt conveyors. However, the current implementations mostly focus on lower level control loops without operational considerations at the system level. This paper intends to take a model based optimization approach to improve the efficiency of belt conveyors at the operational level. An analytical energy model, originating from ISO 5048, is firstly proposed, which lumps all the parameters into four coefficients. Subsequently, both an off-line and an on-line parameter estimation schemes are applied to identify the new energy model, respectively. Simulation results are presented for the estimates of the four coefficients. Finally, optimization is done to achieve the best operation efficiency of belt conveyors under various constraints. Six optimization problems of a typical belt conveyor system are formulated, respectively, with solutions in simulation for a case study.
Systematization of Accurate Discrete Optimization Methods
Directory of Open Access Journals (Sweden)
V. A. Ovchinnikov
2015-01-01
Full Text Available The object of study of this paper is to define accurate methods for solving combinatorial optimization problems of structural synthesis. The aim of the work is to systemize the exact methods of discrete optimization and define their applicability to solve practical problems.The article presents the analysis, generalization and systematization of classical methods and algorithms described in the educational and scientific literature.As a result of research a systematic presentation of combinatorial methods for discrete optimization described in various sources is given, their capabilities are described and properties of the tasks to be solved using the appropriate methods are specified.
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
Carbon and nutrient use efficiencies optimally balance stoichiometric imbalances
Manzoni, Stefano; Čapek, Petr; Lindahl, Björn; Mooshammer, Maria; Richter, Andreas; Šantrůčková, Hana
2016-04-01
Decomposer organisms face large stoichiometric imbalances because their food is generally poor in nutrients compared to the decomposer cellular composition. The presence of excess carbon (C) requires adaptations to utilize nutrients effectively while disposing of or investing excess C. As food composition changes, these adaptations lead to variable C- and nutrient-use efficiencies (defined as the ratios of C and nutrients used for growth over the amounts consumed). For organisms to be ecologically competitive, these changes in efficiencies with resource stoichiometry have to balance advantages and disadvantages in an optimal way. We hypothesize that efficiencies are varied so that community growth rate is optimized along stoichiometric gradients of their resources. Building from previous theories, we predict that maximum growth is achieved when C and nutrients are co-limiting, so that the maximum C-use efficiency is reached, and nutrient release is minimized. This optimality principle is expected to be applicable across terrestrial-aquatic borders, to various elements, and at different trophic levels. While the growth rate maximization hypothesis has been evaluated for consumers and predators, in this contribution we test it for terrestrial and aquatic decomposers degrading resources across wide stoichiometry gradients. The optimality hypothesis predicts constant efficiencies at low substrate C:N and C:P, whereas above a stoichiometric threshold, C-use efficiency declines and nitrogen- and phosphorus-use efficiencies increase up to one. Thus, high resource C:N and C:P lead to low C-use efficiency, but effective retention of nitrogen and phosphorus. Predictions are broadly consistent with efficiency trends in decomposer communities across terrestrial and aquatic ecosystems.
Miao, Zhidong; Liu, Dake; Gong, Chen
2017-10-01
Inductive wireless power transfer (IWPT) is a promising power technology for implantable biomedical devices, where the power consumption is low and the efficiency is the most important consideration. In this paper, we propose an optimization method of impedance matching networks (IMN) to maximize the IWPT efficiency. The IMN at the load side is designed to achieve the optimal load, and the IMN at the source side is designed to deliver the required amount of power (no-more-no-less) from the power source to the load. The theoretical analyses and design procedure are given. An IWPT system for an implantable glaucoma therapeutic prototype is designed as an example. Compared with the efficiency of the resonant IWPT system, the efficiency of our optimized system increases with a factor of 1.73. Besides, the efficiency of our optimized IWPT system is 1.97 times higher than that of the IWPT system optimized by the traditional maximum power transfer method. All the discussions indicate that the optimization method proposed in this paper could achieve a high efficiency and long working time when the system is powered by a battery.
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
Lean and Efficient Software: Whole Program Optimization of Executables
2016-12-31
19b. TELEPHONE NUMBER (Include area code) 12/31/2016 Final Technical Report (Phase I - Base Period) 30-06-2014 - 31-12-2016 Lean and Efficient...Software: Whole-Program Optimization of Executables Final Report Evan Driscoll Tom Johnson GrammaTech, Inc. 531 Esty Street Ithaca, NY 14850 Office of...hardening U U U UU 30 Tom Johnson (607) 273-7340 x.134 Page 1 of 30 “ Lean and Efficient Software: Whole-Program Optimization of Executables
Modifying nodal pricing method considering market participants optimality and reliability
Directory of Open Access Journals (Sweden)
A. R. Soofiabadi
2015-06-01
Full Text Available This paper develops a method for nodal pricing and market clearing mechanism considering reliability of the system. The effects of components reliability on electricity price, market participants’ profit and system social welfare is considered. This paper considers reliability both for evaluation of market participant’s optimality as well as for fair pricing and market clearing mechanism. To achieve fair pricing, nodal price has been obtained through a two stage optimization problem and to achieve fair market clearing mechanism, comprehensive criteria has been introduced for optimality evaluation of market participant. Social welfare of the system and system efficiency are increased under proposed modified nodal pricing method.
Gradient-based methods for production optimization of oil reservoirs
Energy Technology Data Exchange (ETDEWEB)
Suwartadi, Eka
2012-07-01
Production optimization for water flooding in the secondary phase of oil recovery is the main topic in this thesis. The emphasis has been on numerical optimization algorithms, tested on case examples using simple hypothetical oil reservoirs. Gradientbased optimization, which utilizes adjoint-based gradient computation, is used to solve the optimization problems. The first contribution of this thesis is to address output constraint problems. These kinds of constraints are natural in production optimization. Limiting total water production and water cut at producer wells are examples of such constraints. To maintain the feasibility of an optimization solution, a Lagrangian barrier method is proposed to handle the output constraints. This method incorporates the output constraints into the objective function, thus avoiding additional computations for the constraints gradient (Jacobian) which may be detrimental to the efficiency of the adjoint method. The second contribution is the study of the use of second-order adjoint-gradient information for production optimization. In order to speedup convergence rate in the optimization, one usually uses quasi-Newton approaches such as BFGS and SR1 methods. These methods compute an approximation of the inverse of the Hessian matrix given the first-order gradient from the adjoint method. The methods may not give significant speedup if the Hessian is ill-conditioned. We have developed and implemented the Hessian matrix computation using the adjoint method. Due to high computational cost of the Newton method itself, we instead compute the Hessian-timesvector product which is used in a conjugate gradient algorithm. Finally, the last contribution of this thesis is on surrogate optimization for water flooding in the presence of the output constraints. Two kinds of model order reduction techniques are applied to build surrogate models. These are proper orthogonal decomposition (POD) and the discrete empirical interpolation method (DEIM
International Nuclear Information System (INIS)
Han, In-Su; Park, Sang-Kyun; Chung, Chang-Bock
2016-01-01
Highlights: • A proton exchange membrane fuel cell system is operationally optimized. • A constrained optimization problem is formulated to maximize fuel cell efficiency. • Empirical and semi-empirical models for most system components are developed. • Sensitivity analysis is performed to elucidate the effects of major operating variables. • The optimization results are verified by comparison with actual operation data. - Abstract: This paper presents an operation optimization method and demonstrates its application to a proton exchange membrane fuel cell system. A constrained optimization problem was formulated to maximize the efficiency of a fuel cell system by incorporating practical models derived from actual operations of the system. Empirical and semi-empirical models for most of the system components were developed based on artificial neural networks and semi-empirical equations. Prior to system optimizations, the developed models were validated by comparing simulation results with the measured ones. Moreover, sensitivity analyses were performed to elucidate the effects of major operating variables on the system efficiency under practical operating constraints. Then, the optimal operating conditions were sought at various system power loads. The optimization results revealed that the efficiency gaps between the worst and best operation conditions of the system could reach 1.2–5.5% depending on the power output range. To verify the optimization results, the optimal operating conditions were applied to the fuel cell system, and the measured results were compared with the expected optimal values. The discrepancies between the measured and expected values were found to be trivial, indicating that the proposed operation optimization method was quite successful for a substantial increase in the efficiency of the fuel cell system.
DESIGN OPTIMIZATION METHOD USED IN MECHANICAL ENGINEERING
Directory of Open Access Journals (Sweden)
SCURTU Iacob Liviu
2016-11-01
Full Text Available This paper presents an optimization study in mechanical engineering. First part of the research describe the structural optimization method used, followed by the presentation of several optimization studies conducted in recent years. The second part of the paper presents the CAD modelling of an agricultural plough component. The beam of the plough is analysed using finite element method. The plough component is meshed in solid elements, and the load case which mimics the working conditions of agricultural equipment of this are created. The model is prepared to find the optimal structural design, after the FEA study of the model is done. The mass reduction of part is the criterion applied for this optimization study. The end of this research presents the final results and the model optimized shape.
An analytical optimization method for electric propulsion orbit transfer vehicles
International Nuclear Information System (INIS)
Oleson, S.R.
1993-01-01
Due to electric propulsion's inherent propellant mass savings over chemical propulsion, electric propulsion orbit transfer vehicles (EPOTVs) are a highly efficient mode of orbit transfer. When selecting an electric propulsion device (ion, MPD, or arcjet) and propellant for a particular mission, it is preferable to use quick, analytical system optimization methods instead of time intensive numerical integration methods. It is also of interest to determine each thruster's optimal operating characteristics for a specific mission. Analytical expressions are derived which determine the optimal specific impulse (Isp) for each type of electric thruster to maximize payload fraction for a desired thrusting time. These expressions take into account the variation of thruster efficiency with specific impulse. Verification of the method is made with representative electric propulsion values on a LEO-to-GEO mission. Application of the method to specific missions is discussed
Increase of Gas-Turbine Plant Efficiency by Optimizing Operation of Compressors
Matveev, V.; Goriachkin, E.; Volkov, A.
2018-01-01
The article presents optimization method for improving of the working process of axial compressors of gas turbine engines. Developed method allows to perform search for the best geometry of compressor blades automatically by using optimization software IOSO and CFD software NUMECA Fine/Turbo. The calculation of the compressor parameters was performed for work and stall point of its performance map on each optimization step. Study was carried out for seven-stage high-pressure compressor and three-stage low-pressure compressors. As a result of optimization, improvement of efficiency was achieved for all investigated compressors.
Optimal shaping and positioning of energy-efficient buildings
Directory of Open Access Journals (Sweden)
Barović Dušan D.
2017-01-01
Full Text Available Due to the number of variables and the complexity of objective functions, optimal design of an energy-efficient building is hard combinatorial problem of multi-objective optimisation. Therefore, it is necessary to describe structure and its position in surroundings precisely but by as few variables as possible. This paper presents methodology for finding adequate methodology for defining geometry and orientation of a given building, as well as its elements of importance for energy-efficiency analysis.
A fractional optimal control problem for maximizing advertising efficiency
Igor Bykadorov; Andrea Ellero; Stefania Funari; Elena Moretti
2007-01-01
We propose an optimal control problem to model the dynamics of the communication activity of a firm with the aim of maximizing its efficiency. We assume that the advertising effort undertaken by the firm contributes to increase the firm's goodwill and that the goodwill affects the firm's sales. The aim is to find the advertising policies in order to maximize the firm's efficiency index which is computed as the ratio between "outputs" and "inputs" properly weighted; the outputs are represented...
Method for Household Refrigerators Efficiency Increasing
Lebedev, V. V.; Sumzina, L. V.; Maksimov, A. V.
2017-11-01
The relevance of working processes parameters optimization in air conditioning systems is proved in the work. The research is performed with the use of the simulation modeling method. The parameters optimization criteria are considered, the analysis of target functions is given while the key factors of technical and economic optimization are considered in the article. The search for the optimal solution at multi-purpose optimization of the system is made by finding out the minimum of the dual-target vector created by the Pareto method of linear and weight compromises from target functions of the total capital costs and total operating costs. The tasks are solved in the MathCAD environment. The research results show that the values of technical and economic parameters of air conditioning systems in the areas relating to the optimum solutions’ areas manifest considerable deviations from the minimum values. At the same time, the tendencies for significant growth in deviations take place at removal of technical parameters from the optimal values of both the capital investments and operating costs. The production and operation of conditioners with the parameters which are considerably deviating from the optimal values will lead to the increase of material and power costs. The research allows one to establish the borders of the area of the optimal values for technical and economic parameters at air conditioning systems’ design.
International Nuclear Information System (INIS)
Navardi, Mohammad Javad; Babaghorbani, Behnaz; Ketabi, Abbas
2014-01-01
Highlights: • This paper proposes a new method to optimize a Switched Reluctance Motor (SRM). • A combination of SOA and GA with Finite Element Method (FEM) analysis is employed to solve the SRM design optimization. • The results show that optimized SRM obtains higher average torque and higher efficiency. - Abstract: In this paper, performance optimization of Switched Reluctance Motor (SRM) was determined using Seeker Optimization Algorithm (SOA). The most efficient aim of the algorithm was found for maximum torque value at a minimum mass of the entire construction, following changing the geometric parameters. The optimization process was carried out using a combination of Seeker Optimization Algorithm and Finite Element Method (FEM). Fitness value was calculated by FEM analysis using COMSOL3.4, and the SOA was realized by MATLAB. The proposed method has been applied for a case study and it has been also compared with Genetic Algorithm (GA). The results show that the optimized motor using SOA had higher torque value and efficiency with lower mass and torque ripple, exhibiting the validity of this methodology for SRM design
OPTIMIZATION METHODS IN TRANSPORTATION OF FOREST PRODUCTS
Directory of Open Access Journals (Sweden)
Selçuk Gümüş
2008-04-01
Full Text Available Turkey has total of 21.2 million ha (27 % forest land. In this area, average 9 million m3 of logs and 5 million stere of fuel wood have been annually produced by the government forest enterprises. The total annual production is approximately 13million m3 Considering the fact that the costs of transporting forest products was about . 160 million TL in the year of 2006, the importance of optimizing the total costs in transportation can be better understood. Today, there is not common optimization method used at whole transportation problems. However, the decision makers select the most appropriate methods according to their aims.Comprehending of features and capacity of optimization methods is important for selecting of the most appropriate method. The evaluation of optimization methods that can be used at forest products transportation is aimed in this study.
Engineering applications of heuristic multilevel optimization methods
Barthelemy, Jean-Francois M.
1989-01-01
Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.
Efficient Sensor Placement Optimization Using Gradient Descent and Probabilistic Coverage
Directory of Open Access Journals (Sweden)
Vahab Akbarzadeh
2014-08-01
Full Text Available We are proposing an adaptation of the gradient descent method to optimize the position and orientation of sensors for the sensor placement problem. The novelty of the proposed method lies in the combination of gradient descent optimization with a realistic model, which considers both the topography of the environment and a set of sensors with directional probabilistic sensing. The performance of this approach is compared with two other black box optimization methods over area coverage and processing time. Results show that our proposed method produces competitive results on smaller maps and superior results on larger maps, while requiring much less computation than the other optimization methods to which it has been compared.
Modeling Vertical Flow Treatment Wetland Hydraulics to Optimize Treatment Efficiency
2011-03-24
be forced to flow in a 90 serpentine manner back and forth as it moves upward through the wetland (think waiting in line at Disneyland ). This...Flow Treatment Wetland Hydraulics to Optimize Treatment Efficiency 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR
Comparing effectiveness and efficiency in technical specifications and maintenance optimization
International Nuclear Information System (INIS)
Martorell, Sebastian; Sanchez, Ana; Carlos, Sofia; Serradell, Vicente
2002-01-01
Optimization of technical specification requirements and maintenance (TS and M) has been found interesting from the very beginning at Nuclear Power Plants (NPPs). However, the resolution of such a kind of optimization problem has been limited often to focus only on individual TS and M-related parameters (STI, AOT, PM frequency, etc.) and/or adopting an individual optimization criterion (availability, costs, plant risks, etc.). Nevertheless, a number of reasons exist (e.g. interaction, similar scope, etc.) that justify the interest to focus on the coordinated optimization of all of the relevant TS and M-related parameters based on multiple criteria. The purpose of this paper is on signifying benefits and improvement areas in performing the coordinated optimization of TS and M through reviewing the effectiveness and efficiency of common strategies for optimizing TS and M at system level. A case of application is provided for a stand-by safety-related system to demonstrate the basic procedure and to extract a number of conclusions and recommendations from the results achieved. Thus, it is concluded that the optimized values depend on the particular TS and M-related parameters being involved and the solutions with the largest benefit (minimum risk or minimum cost) are achieved when considering the simultaneous optimization of all of them, although increased computational resources are also required. Consequently, it is necessary to analyze not only the value reached but also the performance of the optimization procedure through effectiveness and efficiency measures which lead to recommendations on potential improvement areas
[Optimized application of nested PCR method for detection of malaria].
Yao-Guang, Z; Li, J; Zhen-Yu, W; Li, C
2017-04-28
Objective To optimize the application of the nested PCR method for the detection of malaria according to the working practice, so as to improve the efficiency of malaria detection. Methods Premixing solution of PCR, internal primers for further amplification and new designed primers that aimed at two Plasmodium ovale subspecies were employed to optimize the reaction system, reaction condition and specific primers of P . ovale on basis of routine nested PCR. Then the specificity and the sensitivity of the optimized method were analyzed. The positive blood samples and examination samples of malaria were detected by the routine nested PCR and the optimized method simultaneously, and the detection results were compared and analyzed. Results The optimized method showed good specificity, and its sensitivity could reach the pg to fg level. The two methods were used to detect the same positive malarial blood samples simultaneously, the results indicated that the PCR products of the two methods had no significant difference, but the non-specific amplification reduced obviously and the detection rates of P . ovale subspecies improved, as well as the total specificity also increased through the use of the optimized method. The actual detection results of 111 cases of malarial blood samples showed that the sensitivity and specificity of the routine nested PCR were 94.57% and 86.96%, respectively, and those of the optimized method were both 93.48%, and there was no statistically significant difference between the two methods in the sensitivity ( P > 0.05), but there was a statistically significant difference between the two methods in the specificity ( P PCR can improve the specificity without reducing the sensitivity on the basis of the routine nested PCR, it also can save the cost and increase the efficiency of malaria detection as less experiment links.
Method optimization of ocular patches
Directory of Open Access Journals (Sweden)
Kamalesh Upreti
2012-01-01
Full Text Available The intraocular patches were prepared using gelatin as the polymer. Ocular patch were prepared by solvent casting method. The patches were prepared for six formulations GP1, GP2, GP3, GP4, GP5 and GP6. Petri dishes were used for formulation of ocular patch. Gelatin was used as a polymer of choice. Glutaraldehyde used as cross linking agent and (DMSO dimethylsulfoxide used as solubility enhancer. The elasticity depends upon the concentration of gelatin. 400 mg amount of polymer i.e gelatin gave the required elasticity for the formulation.
Novel Area Optimization in FPGA Implementation Using Efficient VHDL Code
Zulfikar, Z
2012-01-01
A new novel method for area efficiency in FPGA implementation is presented. The method is realized through flexibility and wide capability of VHDL coding. This method exposes the arithmetic operations such as addition, subtraction and others. The design technique aim to reduce occupies area for multi stages circuits by selecting suitable range of all value involved in every step of calculations. Conventional and efficient VHDL coding methods are presented and the synthesis result is compared....
ASSESSMENT OF THE EFFICIENCY OF DISINFECTION METHOD ...
African Journals Online (AJOL)
eobe
ABSTRACT. The efficiencies of three disinfection methods namely boiling, water guard and pur purifier were assessed. ... Water is an indispensable resource for supporting life systems [2- ...... developing country context: improving decisions.
Towards Cost-efficient Sampling Methods
Peng, Luo; Yongli, Li; Chong, Wu
2014-01-01
The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper presents two new sampling methods based on the perspective that a small part of vertices with high node degree can possess the most structure information of a network. The two proposed sampling methods are efficient in sampling the nodes with high degree. The first new sampling method is improved on the basis of the stratified random sampling method and...
Coordinated Optimal Operation Method of the Regional Energy Internet
Directory of Open Access Journals (Sweden)
Rishang Long
2017-05-01
Full Text Available The development of the energy internet has become one of the key ways to solve the energy crisis. This paper studies the system architecture, energy flow characteristics and coordinated optimization method of the regional energy internet. Considering the heat-to-electric ratio of a combined cooling, heating and power unit, energy storage life and real-time electricity price, a double-layer optimal scheduling model is proposed, which includes economic and environmental benefit in the upper layer and energy efficiency in the lower layer. A particle swarm optimizer–individual variation ant colony optimization algorithm is used to solve the computational efficiency and accuracy. Through the calculation and simulation of the simulated system, the energy savings, level of environmental protection and economic optimal dispatching scheme are realized.
Improving Battery Reactor Core Design Using Optimization Method
International Nuclear Information System (INIS)
Son, Hyung M.; Suh, Kune Y.
2011-01-01
The Battery Omnibus Reactor Integral System (BORIS) is a small modular fast reactor being designed at Seoul National University to satisfy various energy demands, to maintain inherent safety by liquid-metal coolant lead for natural circulation heat transport, and to improve power conversion efficiency with the Modular Optimal Balance Integral System (MOBIS) using the supercritical carbon dioxide as working fluid. This study is focused on developing the Neutronics Optimized Reactor Analysis (NORA) method that can quickly generate conceptual design of a battery reactor core by means of first principle calculations, which is part of the optimization process for reactor assembly design of BORIS
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.
An Efficient PageRank Approach for Urban Traffic Optimization
Directory of Open Access Journals (Sweden)
Florin Pop
2012-01-01
to determine optimal decisions for each traffic light, based on the solution given by Larry Page for page ranking in Web environment (Page et al. (1999. Our approach is similar with work presented by Sheng-Chung et al. (2009 and Yousef et al. (2010. We consider that the traffic lights are controlled by servers and a score for each road is computed based on efficient PageRank approach and is used in cost function to determine optimal decisions. We demonstrate that the cumulative contribution of each car in the traffic respects the main constrain of PageRank approach, preserving all the properties of matrix consider in our model.
Energy efficient LED layout optimization for near-uniform illumination
Ali, Ramy E.; Elgala, Hany
2016-09-01
In this paper, we consider the problem of designing energy efficient light emitting diodes (LEDs) layout while satisfying the illumination constraints. Towards this objective, we present a simple approach to the illumination design problem based on the concept of the virtual LED. We formulate a constrained optimization problem for minimizing the power consumption while maintaining a near-uniform illumination throughout the room. By solving the resulting constrained linear program, we obtain the number of required LEDs and the optimal output luminous intensities that achieve the desired illumination constraints.
ROTAX: a nonlinear optimization program by axes rotation method
International Nuclear Information System (INIS)
Suzuki, Tadakazu
1977-09-01
A nonlinear optimization program employing the axes rotation method has been developed for solving nonlinear problems subject to nonlinear inequality constraints and its stability and convergence efficiency were examined. The axes rotation method is a direct search of the optimum point by rotating the orthogonal coordinate system in a direction giving the minimum objective. The searching direction is rotated freely in multi-dimensional space, so the method is effective for the problems represented with the contours having deep curved valleys. In application of the axes rotation method to the optimization problems subject to nonlinear inequality constraints, an improved version of R.R. Allran and S.E.J. Johnsen's method is used, which deals with a new objective function composed of the original objective and a penalty term to consider the inequality constraints. The program is incorporated in optimization code system SCOOP. (auth.)
Panorama parking assistant system with improved particle swarm optimization method
Cheng, Ruzhong; Zhao, Yong; Li, Zhichao; Jiang, Weigang; Wang, Xin'an; Xu, Yong
2013-10-01
A panorama parking assistant system (PPAS) for the automotive aftermarket together with a practical improved particle swarm optimization method (IPSO) are proposed in this paper. In the PPAS system, four fisheye cameras are installed in the vehicle with different views, and four channels of video frames captured by the cameras are processed as a 360-deg top-view image around the vehicle. Besides the embedded design of PPAS, the key problem for image distortion correction and mosaicking is the efficiency of parameter optimization in the process of camera calibration. In order to address this problem, an IPSO method is proposed. Compared with other parameter optimization methods, the proposed method allows a certain range of dynamic change for the intrinsic and extrinsic parameters, and can exploit only one reference image to complete all of the optimization; therefore, the efficiency of the whole camera calibration is increased. The PPAS is commercially available, and the IPSO method is a highly practical way to increase the efficiency of the installation and the calibration of PPAS in automobile 4S shops.
Institute of Scientific and Technical Information of China (English)
杨帆; 程坦
2016-01-01
对光伏发电系统的太阳能采集板的能效最优倾角的准确计算可以改善电机的转矩输出,提高对光伏电机的输出功率增益.当前的光伏发电系统的能效最优倾角估算方法采用贝叶斯参量估计算法,随着电机磁损耗的增加,导致能效最优倾角参量估计精度不高.提出一种基于电磁耦合器轴向切面磁场估计的光伏发电系统的能效最优倾角计算方法.分析了光伏发电系统的电磁耦合系统结构模型,利用蓄电池放电率特性修正原则,建立光伏发电系统的能效最优倾角目标函数,实现能效控制输出的目标参量系统传递函数构建,设计电磁耦合器轴向切面磁场估计算法,实现对光伏发电系统的能效最优倾角计算的算法改进.仿真结果表明,采用该算法进行光伏发电系统中能效最优倾角的计算,精度较高,优化了太阳能向电能的转换过程,有效提高对光伏发电系统的输出功率增益.%The accurate calculation of the optimal tilt angle of the solar energy collection board in the photovoltaic power generation system can improve the torque output of the motor and improve the output power of the photovoltaic motor. At present, the optimal tilt angle estimation method for photovoltaic power generation system is based on the Bayesian parameter estimation algorithm, and the estimation accuracy of the optimum tilt angle is not high with the increase of the magnetic loss of the motor. An optimal method for calculating the optimum tilt angle of photovoltaic power generation system based on the magnetic field of the axial section of the electromagnetic coupling is proposed. The structure model of photovoltaic power generation system is analyzed, and the energy efficiency of photovoltaic power generation system is set up by using the principle of discharge rate characteristic correction. Simulation results show that the proposed algorithm is used to calculate the optimum tilt angle of
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....
Ariyarit, Atthaphon; Sugiura, Masahiko; Tanabe, Yasutada; Kanazaki, Masahiro
2018-06-01
A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.
Improvement in PWR automatic optimization reloading methods using genetic algorithm
International Nuclear Information System (INIS)
Levine, S.H.; Ivanov, K.; Feltus, M.
1996-01-01
The objective of using automatic optimized reloading methods is to provide the Nuclear Engineer with an efficient method for reloading a nuclear reactor which results in superior core configurations that minimize fuel costs. Previous methods developed by Levine et al required a large effort to develop the initial core loading using a priority loading scheme. Subsequent modifications to this core configuration were made using expert rules to produce the final core design. Improvements in this technique have been made by using a genetic algorithm to produce improved core reload designs for PWRs more efficiently (authors)
Improvement in PWR automatic optimization reloading methods using genetic algorithm
Energy Technology Data Exchange (ETDEWEB)
Levine, S H; Ivanov, K; Feltus, M [Pennsylvania State Univ., University Park, PA (United States)
1996-12-01
The objective of using automatic optimized reloading methods is to provide the Nuclear Engineer with an efficient method for reloading a nuclear reactor which results in superior core configurations that minimize fuel costs. Previous methods developed by Levine et al required a large effort to develop the initial core loading using a priority loading scheme. Subsequent modifications to this core configuration were made using expert rules to produce the final core design. Improvements in this technique have been made by using a genetic algorithm to produce improved core reload designs for PWRs more efficiently (authors).
Aerodynamic shape optimization using preconditioned conjugate gradient methods
Burgreen, Greg W.; Baysal, Oktay
1993-01-01
In an effort to further improve upon the latest advancements made in aerodynamic shape optimization procedures, a systematic study is performed to examine several current solution methodologies as applied to various aspects of the optimization procedure. It is demonstrated that preconditioned conjugate gradient-like methodologies dramatically decrease the computational efforts required for such procedures. The design problem investigated is the shape optimization of the upper and lower surfaces of an initially symmetric (NACA-012) airfoil in inviscid transonic flow and at zero degree angle-of-attack. The complete surface shape is represented using a Bezier-Bernstein polynomial. The present optimization method then automatically obtains supercritical airfoil shapes over a variety of freestream Mach numbers. Furthermore, the best optimization strategy examined resulted in a factor of 8 decrease in computational time as well as a factor of 4 decrease in memory over the most efficient strategies in current use.
Efficiency Test Method for Electric Vehicle Chargers
DEFF Research Database (Denmark)
Kieldsen, Andreas; Thingvad, Andreas; Martinenas, Sergejus
2016-01-01
This paper investigates different methods for measuring the charger efficiency of mass produced electric vehicles (EVs), in order to compare the different models. The consumers have low attention to the loss in the charger though the impact on the driving cost is high. It is not a high priority...... different vehicles. A unified method for testing the efficiency of the charger in EVs, without direct access to the component, is presented. The method is validated through extensive tests of the models Renault Zoe, Nissan LEAF and Peugeot iOn. The results show a loss between 15 % and 40 %, which is far...
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...
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.
Multiobjective optimal design of runner blade using efficiency and draft tube pulsation criteria
International Nuclear Information System (INIS)
Pilev, I M; Sotnikov, A A; Rigin, V E; Semenova, A V; Cherny, S G; Chirkov, D V; Bannikov, D V; Skorospelov, V A
2012-01-01
In the present work new criteria of optimal design method for turbine runner [1] are proposed. Firstly, based on the efficient method which couples direct simulation of 3D turbulent flow and engineering semi empirical formulas, the combined method is built for hydraulic energy losses estimation in the whole turbine water passage and the efficiency criterion is formulated. Secondly, the criterion of dynamic loads minimization is developed for those caused by vortex rope precession downstream of the runner. This criterion is based on the finding that the monotonic increase of meridional velocity component in the direction to runner hub, downstream of its blades, provides for decreasing the intensity of vortex rope and thereafter, minimization of pressure pulsation amplitude. The developed algorithm was applied to optimal design of 640 MW Francis turbine runner. It can ensure high efficiency at best efficiency operating point as well as diminished pressure pulsations at full load regime.
Optimizing How We Teach Research Methods
Cvancara, Kristen E.
2017-01-01
Courses: Research Methods (undergraduate or graduate level). Objective: The aim of this exercise is to optimize the ability for students to integrate an understanding of various methodologies across research paradigms within a 15-week semester, including a review of procedural steps and experiential learning activities to practice each method, a…
Optimization of breeding methods when introducing multiple ...
African Journals Online (AJOL)
Optimization of breeding methods when introducing multiple resistance genes from American to Chinese wheat. JN Qi, X Zhang, C Yin, H Li, F Lin. Abstract. Stripe rust is one of the most destructive diseases of wheat worldwide. Growing resistant cultivars with resistance genes is the most effective method to control this ...
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 ...
Novel Area Optimization in FPGA Implementation Using Efficient VHDL Code
Directory of Open Access Journals (Sweden)
. Zulfikar
2012-10-01
Full Text Available A new novel method for area efficiency in FPGA implementation is presented. The method is realized through flexibility and wide capability of VHDL coding. This method exposes the arithmetic operations such as addition, subtraction and others. The design technique aim to reduce occupies area for multi stages circuits by selecting suitable range of all value involved in every step of calculations. Conventional and efficient VHDL coding methods are presented and the synthesis result is compared. The VHDL code which limits range of integer values is occupies less area than the one which is not. This VHDL coding method is suitable for multi stage circuits.
Novel Area Optimization in FPGA Implementation Using Efficient VHDL Code
Directory of Open Access Journals (Sweden)
Zulfikar .
2015-05-01
Full Text Available A new novel method for area efficiency in FPGA implementation is presented. The method is realized through flexibility and wide capability of VHDL coding. This method exposes the arithmetic operations such as addition, subtraction and others. The design technique aim to reduce occupies area for multi stages circuits by selecting suitable range of all value involved in every step of calculations. Conventional and efficient VHDL coding methods are presented and the synthesis result is compared. The VHDL code which limits range of integer values is occupies less area than the one which is not. This VHDL coding method is suitable for multi stage circuits.
Optimal power and efficiency of quantum Stirling heat engines
Yin, Yong; Chen, Lingen; Wu, Feng
2017-01-01
A quantum Stirling heat engine model is established in this paper in which imperfect regeneration and heat leakage are considered. A single particle which contained in a one-dimensional infinite potential well is studied, and the system consists of countless replicas. Each particle is confined in its own potential well, whose occupation probabilities can be expressed by the thermal equilibrium Gibbs distributions. Based on the Schrödinger equation, the expressions of power output and efficiency for the engine are obtained. Effects of imperfect regeneration and heat leakage on the optimal performance are discussed. The optimal performance region and the optimal values of important parameters of the engine cycle are obtained. The results obtained can provide some guidelines for the design of a quantum Stirling heat engine.
High-efficiency design optimization of a centrifugal pump
Energy Technology Data Exchange (ETDEWEB)
Heo, Man Woong; Ma, Sang Bum; Shim, Hyeon Seok; Kim, Kwang Yong [Dept. of Mechanical Engineering, Inha University, Incheon (Korea, Republic of)
2016-09-15
Design optimization of a backward-curved blades centrifugal pump with specific speed of 150 has been performed to improve hydraulic performance of the pump using surrogate modeling and three-dimensional steady Reynolds-averaged Navier-Stokes analysis. The shear stress transport model was used for the analysis of turbulence. Four geometric variables defining the blade hub inlet angle, hub contours, blade outlet angle, and blade angle profile of impeller were selected as design variables, and total efficiency of the pump at design flow rate was set as the objective function for the optimization. Thirty-six design points were chosen using the Latin hypercube sampling, and three different surrogate models were constructed using the objective function values calculated at these design points. The optimal point was searched from the constructed surrogate model by using sequential quadratic programming. The optimum designs of the centrifugal pump predicted by the surrogate models show considerable increases in efficiency compared to a reference design. Performance of the best optimum design was validated compared to experimental data for total efficiency and head.
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
An Integrated Method for Airfoil Optimization
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
Topology optimization using the finite volume method
DEFF Research Database (Denmark)
in this presentation is focused on a prototype model for topology optimization of steady heat diffusion. This allows for a study of the basic ingredients in working with FVM methods when dealing with topology optimization problems. The FVM and FEM based formulations differ both in how one computes the design...... derivative of the system matrix K and in how one computes the discretized version of certain objective functions. Thus for a cost function for minimum dissipated energy (like minimum compliance for an elastic structure) one obtains an expression c = u^\\T \\tilde{K}u $, where \\tilde{K} is different from K...... the well known Reuss lower bound. [1] Bendsøe, M.P.; Sigmund, O. 2004: Topology Optimization - Theory, Methods, and Applications. Berlin Heidelberg: Springer Verlag [2] Versteeg, H. K.; W. Malalasekera 1995: An introduction to Computational Fluid Dynamics: the Finite Volume Method. London: Longman...
Efficiency optimization potential in supercritical Organic Rankine Cycles
Energy Technology Data Exchange (ETDEWEB)
Schuster, A.; Aumann, R. [Technische Universitaet Muenchen Institute of Energy Systems Boltzmannstr. 15, 85748 Garching (Germany); Karellas, S. [National Technical University of Athens Laboratory of Steam Boilers and Thermal Plants Heroon Polytechniou 9, 15780 Athens (Greece)
2010-02-15
Nowadays, the use of Organic Rankine Cycle (ORC) in decentralised applications is linked with the fact that this process allows the use of low temperature heat sources and offers an advantageous efficiency in small-scale concepts. Many state-of-the-art and innovative applications can successfully use the ORC process. In this process, according to the heat source level, special attention must be drawn to the choice of the appropriate working fluid, which is a factor that affects the thermal and exergetic efficiency of the cycle. The investigation of supercritical parameters of various working fluids in ORC applications seems to bring promising results concerning the efficiency of the application. This paper presents the results from a simulation of the ORC and the optimization potential of the process when using supercritical parameters. In order to optimize the process, various working fluids are considered and compared concerning their thermal efficiency and the usable percentage of heat. The reduction of exergy losses is discussed based on the need of surplus heat exchanger surface. (author)
On some other preferred method for optimizing the welded joint
Directory of Open Access Journals (Sweden)
Pejović Branko B.
2016-01-01
Full Text Available The paper shows an example of performed optimization of sizes in terms of welding costs in a characteristic loaded welded joint. Hence, in the first stage, the variables and constant parameters are defined, and mathematical shape of the optimization function is determined. The following stage of the procedure defines and places the most important constraint functions that limit the design of structures, that the technologist and the designer should take into account. Subsequently, a mathematical optimization model of the problem is derived, that is efficiently solved by a proposed method of geometric programming. Further, a mathematically based thorough optimization algorithm is developed of the proposed method, with a main set of equations defining the problem that are valid under certain conditions. Thus, the primary task of optimization is reduced to the dual task through a corresponding function, which is easier to solve than the primary task of the optimized objective function. The main reason for this is a derived set of linear equations. Apparently, a correlation is used between the optimal primary vector that minimizes the objective function and the dual vector that maximizes the dual function. The method is illustrated on a computational practical example with a different number of constraint functions. It is shown that for the case of a lower level of complexity, a solution is reached through an appropriate maximization of the dual function by mathematical analysis and differential calculus.
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
Optimal and efficient decoding of concatenated quantum block codes
International Nuclear Information System (INIS)
Poulin, David
2006-01-01
We consider the problem of optimally decoding a quantum error correction code--that is, to find the optimal recovery procedure given the outcomes of partial ''check'' measurements on the system. In general, this problem is NP hard. However, we demonstrate that for concatenated block codes, the optimal decoding can be efficiently computed using a message-passing algorithm. We compare the performance of the message-passing algorithm to that of the widespread blockwise hard decoding technique. Our Monte Carlo results using the five-qubit and Steane's code on a depolarizing channel demonstrate significant advantages of the message-passing algorithms in two respects: (i) Optimal decoding increases by as much as 94% the error threshold below which the error correction procedure can be used to reliably send information over a noisy channel; and (ii) for noise levels below these thresholds, the probability of error after optimal decoding is suppressed at a significantly higher rate, leading to a substantial reduction of the error correction overhead
Directory of Open Access Journals (Sweden)
Ruisheng Sun
2016-01-01
Full Text Available This paper presents a new parametric optimization approach based on a modified particle swarm optimization (PSO to design a class of impulsive-correction projectiles with discrete, flexible-time interval, and finite-energy control. In terms of optimal control theory, the task is described as the formulation of minimum working number of impulses and minimum control error, which involves reference model linearization, boundary conditions, and discontinuous objective function. These result in difficulties in finding the global optimum solution by directly utilizing any other optimization approaches, for example, Hp-adaptive pseudospectral method. Consequently, PSO mechanism is employed for optimal setting of impulsive control by considering the time intervals between two neighboring lateral impulses as design variables, which makes the briefness of the optimization process. A modification on basic PSO algorithm is developed to improve the convergence speed of this optimization through linearly decreasing the inertial weight. In addition, a suboptimal control and guidance law based on PSO technique are put forward for the real-time consideration of the online design in practice. Finally, a simulation case coupled with a nonlinear flight dynamic model is applied to validate the modified PSO control algorithm. The results of comparative study illustrate that the proposed optimal control algorithm has a good performance in obtaining the optimal control efficiently and accurately and provides a reference approach to handling such impulsive-correction problem.
An introduction to harmony search optimization method
Wang, Xiaolei; Zenger, Kai
2014-01-01
This brief provides a detailed introduction, discussion and bibliographic review of the nature1-inspired optimization algorithm called Harmony Search. It uses a large number of simulation results to demonstrate the advantages of Harmony Search and its variants and also their drawbacks. The authors show how weaknesses can be amended by hybridization with other optimization methods. The Harmony Search Method with Applications will be of value to researchers in computational intelligence in demonstrating the state of the art of research on an algorithm of current interest. It also helps researche
Optimal boarding method for airline passengers
Energy Technology Data Exchange (ETDEWEB)
Steffen, Jason H.; /Fermilab
2008-02-01
Using a Markov Chain Monte Carlo optimization algorithm and a computer simulation, I find the passenger ordering which minimizes the time required to board the passengers onto an airplane. The model that I employ assumes that the time that a passenger requires to load his or her luggage is the dominant contribution to the time needed to completely fill the aircraft. The optimal boarding strategy may reduce the time required to board and airplane by over a factor of four and possibly more depending upon the dimensions of the aircraft. I explore some features of the optimal boarding method and discuss practical modifications to the optimal. Finally, I mention some of the benefits that could come from implementing an improved passenger boarding scheme.
International Nuclear Information System (INIS)
Qianqian, Li; Xiaofeng, Jiang; Shaohong, Zhang
2010-01-01
Simulated Annealing Algorithm (SAA) for solving combinatorial optimization problems is a popular method for loading pattern optimization. The main purpose of this paper is to understand the underlying search mechanism of SAA and to study its efficiency. In this study, a general SAA that employs random pair exchange of fuel assemblies to search for the optimum fuel Loading Pattern (LP) is applied to an exhaustively searched LP optimization benchmark problem. All the possible LPs of the benchmark problem have been enumerated and evaluated via the use of the very fast and accurate Hybrid Harmonics and Linear Perturbation (HHLP) method, such that the mechanism of SA for LP optimization can be explicitly analyzed and its search efficiency evaluated. The generic core geometry itself dictates that only a small number LPs can be generated by performing random single pair exchanges and that the LPs are necessarily mostly similar to the initial LP. This phase space effect turns out to be the basic mechanism in SAA that can explain its efficiency and good local search ability. A measure of search efficiency is introduced which shows that the stochastic nature of SAA greatly influences the variability of its search efficiency. It is also found that using fuel assembly k-infinity distribution as a technique to filter the LPs can significantly enhance the SAA search efficiency. (authors)
Optimization methods applied to hybrid vehicle design
Donoghue, J. F.; Burghart, J. H.
1983-01-01
The use of optimization methods as an effective design tool in the design of hybrid vehicle propulsion systems is demonstrated. Optimization techniques were used to select values for three design parameters (battery weight, heat engine power rating and power split between the two on-board energy sources) such that various measures of vehicle performance (acquisition cost, life cycle cost and petroleum consumption) were optimized. The apporach produced designs which were often significant improvements over hybrid designs already reported on in the literature. The principal conclusions are as follows. First, it was found that the strategy used to split the required power between the two on-board energy sources can have a significant effect on life cycle cost and petroleum consumption. Second, the optimization program should be constructed so that performance measures and design variables can be easily changed. Third, the vehicle simulation program has a significant effect on the computer run time of the overall optimization program; run time can be significantly reduced by proper design of the types of trips the vehicle takes in a one year period. Fourth, care must be taken in designing the cost and constraint expressions which are used in the optimization so that they are relatively smooth functions of the design variables. Fifth, proper handling of constraints on battery weight and heat engine rating, variables which must be large enough to meet power demands, is particularly important for the success of an optimization study. Finally, the principal conclusion is that optimization methods provide a practical tool for carrying out the design of a hybrid vehicle propulsion system.
Kinoform design with an optimal-rotation-angle method.
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.
Optimization Methods in Emotion Recognition System
Directory of Open Access Journals (Sweden)
L. Povoda
2016-09-01
Full Text Available Emotions play big role in our everyday communication and contain important information. This work describes a novel method of automatic emotion recognition from textual data. The method is based on well-known data mining techniques, novel approach based on parallel run of SVM (Support Vector Machine classifiers, text preprocessing and 3 optimization methods: sequential elimination of attributes, parameter optimization based on token groups, and method of extending train data sets during practical testing and production release final tuning. We outperformed current state of the art methods and the results were validated on bigger data sets (3346 manually labelled samples which is less prone to overfitting when compared to related works. The accuracy achieved in this work is 86.89% for recognition of 5 emotional classes. The experiments were performed in the real world helpdesk environment, was processing Czech language but the proposed methodology is general and can be applied to many different languages.
Path optimization method for the sign problem
Directory of Open Access Journals (Sweden)
Ohnishi Akira
2018-01-01
Full Text Available We propose a path optimization method (POM to evade the sign problem in the Monte-Carlo calculations for complex actions. Among many approaches to the sign problem, the Lefschetz-thimble path-integral method and the complex Langevin method are promising and extensively discussed. In these methods, real field variables are complexified and the integration manifold is determined by the flow equations or stochastically sampled. When we have singular points of the action or multiple critical points near the original integral surface, however, we have a risk to encounter the residual and global sign problems or the singular drift term problem. One of the ways to avoid the singular points is to optimize the integration path which is designed not to hit the singular points of the Boltzmann weight. By specifying the one-dimensional integration-path as z = t +if(t(f ϵ R and by optimizing f(t to enhance the average phase factor, we demonstrate that we can avoid the sign problem in a one-variable toy model for which the complex Langevin method is found to fail. In this proceedings, we propose POM and discuss how we can avoid the sign problem in a toy model. We also discuss the possibility to utilize the neural network to optimize the path.
International Nuclear Information System (INIS)
Negi, Lalit Mohan; Talegaonkar, Sushama; Jaggi, Manu
2013-01-01
Development of an effective formulation involves careful optimization of a number of excipient and process variables. Sometimes the number of variables is so large that even the most efficient optimization designs require a very large number of trials which put stress on costs as well as time. A creative combination of a number of design methods leads to a smaller number of trials. This study was aimed at the development of nanostructured lipid carriers (NLCs) by using a combination of different optimization methods. A total of 11 variables were first screened using the Plackett–Burman design for their effects on formulation characteristics like size and entrapment efficiency. Four out of 11 variables were found to have insignificant effects on the formulation parameters and hence were screened out. Out of the remaining seven variables, four (concentration of tween-80, lecithin, sodium taurocholate, and total lipid) were found to have significant effects on the size of the particles while the other three (phase ratio, drug to lipid ratio, and sonication time) had a higher influence on the entrapment efficiency. The first four variables were optimized for their effect on size using the Taguchi L9 orthogonal array. The optimized values of the surfactants and lipids were kept constant for the next stage, where the sonication time, phase ratio, and drug:lipid ratio were varied using the Box–Behnken design response surface method to optimize the entrapment efficiency. Finally, by performing only 38 trials, we have optimized 11 variables for the development of NLCs with a size of 143.52 ± 1.2 nm, zeta potential of −32.6 ± 0.54 mV, and 98.22 ± 2.06% entrapment efficiency. (paper)
Adaptive finite element method for shape optimization
Morin, Pedro; Nochetto, Ricardo H.; Pauletti, Miguel S.; Verani, Marco
2012-01-01
We examine shape optimization problems in the context of inexact sequential quadratic programming. Inexactness is a consequence of using adaptive finite element methods (AFEM) to approximate the state and adjoint equations (via the dual weighted residual method), update the boundary, and compute the geometric functional. We present a novel algorithm that equidistributes the errors due to shape optimization and discretization, thereby leading to coarse resolution in the early stages and fine resolution upon convergence, and thus optimizing the computational effort. We discuss the ability of the algorithm to detect whether or not geometric singularities such as corners are genuine to the problem or simply due to lack of resolution - a new paradigm in adaptivity. © EDP Sciences, SMAI, 2012.
Topology optimization using the finite volume method
DEFF Research Database (Denmark)
Gersborg-Hansen, Allan; Bendsøe, Martin P.; Sigmund, Ole
2005-01-01
in this presentation is focused on a prototype model for topology optimization of steady heat diffusion. This allows for a study of the basic ingredients in working with FVM methods when dealing with topology optimization problems. The FVM and FEM based formulations differ both in how one computes the design...... derivative of the system matrix $\\mathbf K$ and in how one computes the discretized version of certain objective functions. Thus for a cost function for minimum dissipated energy (like minimum compliance for an elastic structure) one obtains an expression $ c = \\mathbf u^\\T \\tilde{\\mathbf K} \\mathbf u...... the arithmetic and harmonic average with the latter being the well known Reuss lower bound. [1] Bendsøe, MP and Sigmund, O 2004: Topology Optimization - Theory, Methods, and Applications. Berlin Heidelberg: Springer Verlag [2] Versteeg, HK and Malalasekera, W 1995: An introduction to Computational Fluid Dynamics...
Adaptive finite element method for shape optimization
Morin, Pedro
2012-01-16
We examine shape optimization problems in the context of inexact sequential quadratic programming. Inexactness is a consequence of using adaptive finite element methods (AFEM) to approximate the state and adjoint equations (via the dual weighted residual method), update the boundary, and compute the geometric functional. We present a novel algorithm that equidistributes the errors due to shape optimization and discretization, thereby leading to coarse resolution in the early stages and fine resolution upon convergence, and thus optimizing the computational effort. We discuss the ability of the algorithm to detect whether or not geometric singularities such as corners are genuine to the problem or simply due to lack of resolution - a new paradigm in adaptivity. © EDP Sciences, SMAI, 2012.
Toward cost-efficient sampling methods
Luo, Peng; Li, Yongli; Wu, Chong; Zhang, Guijie
2015-09-01
The sampling method has been paid much attention in the field of complex network in general and statistical physics in particular. This paper proposes two new sampling methods based on the idea that a small part of vertices with high node degree could possess the most structure information of a complex network. The two proposed sampling methods are efficient in sampling high degree nodes so that they would be useful even if the sampling rate is low, which means cost-efficient. The first new sampling method is developed on the basis of the widely used stratified random sampling (SRS) method and the second one improves the famous snowball sampling (SBS) method. In order to demonstrate the validity and accuracy of two new sampling methods, we compare them with the existing sampling methods in three commonly used simulation networks that are scale-free network, random network, small-world network, and also in two real networks. The experimental results illustrate that the two proposed sampling methods perform much better than the existing sampling methods in terms of achieving the true network structure characteristics reflected by clustering coefficient, Bonacich centrality and average path length, especially when the sampling rate is low.
Optimizing Usability Studies by Complementary Evaluation Methods
Schmettow, Martin; Bach, Cedric; Scapin, Dominique
2014-01-01
This paper examines combinations of complementary evaluation methods as a strategy for efficient usability problem discovery. A data set from an earlier study is re-analyzed, involving three evaluation methods applied to two virtual environment applications. Results of a mixed-effects logistic
Efficient Methods of Estimating Switchgrass Biomass Supplies
Switchgrass (Panicum virgatum L.) is being developed as a biofuel feedstock for the United States. Efficient and accurate methods to estimate switchgrass biomass feedstock supply within a production area will be required by biorefineries. Our main objective was to determine the effectiveness of in...
Directory of Open Access Journals (Sweden)
Bin He
2014-01-01
Full Text Available In city traffic, it is important to improve transportation efficiency and the spacing of platoon should be shortened when crossing the street. The best method to deal with this problem is automatic control of vehicles. In this paper, a mathematical model is established for the platoon’s longitudinal movement. A systematic analysis of longitudinal control law is presented for the platoon of vehicles. However, the parameter calibration for the platoon model is relatively difficult because the platoon model is complex and the parameters are coupled with each other. In this paper, the particle swarm optimization method is introduced to effectively optimize the parameters of platoon. The proposed method effectively finds the optimal parameters based on simulations and makes the spacing of platoon shorter.
O. Severyn; O. Shulika
2017-01-01
The results of optimization of gravimetric coefficients for indexes included in the integral criterion of estimation of the efficiency of transport-technological charts of cargo delivery are resulted. The values of gravimetric coefficients are determined on the basis of two methods of experimental researches: questioning of respondents among the specialists of motor transport production and imitation design.
Efficiency optimization of green phosphorescent organic light-emitting device
Energy Technology Data Exchange (ETDEWEB)
Park, Jung Soo; Jeon, Woo Sik; Yu, Jae Hyung [Department of Information Display, Kyung Hee University, Dongdaemoon-gu, Seoul 130-701 (Korea, Republic of); Pode, Ramchandra, E-mail: rbpode@khu.ac.k [Department of Physics, Kyung Hee University, Dongdaemoon-gu, Seoul 130-701 (Korea, Republic of); Kwon, Jang Hyuk, E-mail: jhkwon@khu.ac.k [Department of Information Display, Kyung Hee University, Dongdaemoon-gu, Seoul 130-701 (Korea, Republic of)
2011-03-01
Using a narrow band gap host of bis[2-(2-hydroxyphenyl)-pyridine]beryllium (Bepp{sub 2}) and green phosphorescent Ir(ppy){sub 3} [fac-tris(2-phenylpyridine) iridium III] guest concentration as low as 2%, high efficiency phosphorescent organic light-emitting diode (PHOLED) is realized. Current and power efficiencies of 62.5 cd/A (max.), 51.0 lm/W (max.), and external quantum efficiency (max.) of 19.8% are reported in this green PHOLED. A low current efficiency roll-off value of 10% over the brightness of 10,000 cd/m{sup 2} is noticed in this Bepp{sub 2} single host device. Such a high efficiency is obtained by the optimization of the doping concentration with the knowledge of the hole trapping and the emission zone situations in this host-guest system. It is suggested that the reported device performance is suitable for applications in high brightness displays and lighting.
Utilization of Flexible Airspace Structure in Flight Efficiency Optimization
Directory of Open Access Journals (Sweden)
Tomislav Mihetec
2013-04-01
Full Text Available With increasing air traffic demand in the Pan-European airspace there is a need for optimizing the use of the airspace structure (civilian and military in a manner that would satisfy the requirements of civil and military users. In the area of Europe with the highest levels of air traffic (Core area 32% of the volume of airspace above FL 195 is shared by both civil and military users. Until the introduction of the concept of flexible use of airspace, flexible airspace structures were 24 hours per day unavailable for commercial air transport. Flexible use of airspace concept provides a substantial level of dynamic airspace management by the usage of conditional routes. This paper analyses underutilization of resources, flexible airspace structures in the Pan-European airspace, especially in the south-eastern part of the traffic flows (East South Axis, reducing the efficiency of flight operations, as result of delegating the flexible structures to military users. Based on previous analysis, utilization model for flexible use of airspace is developed (scenarios with defined airspace structure. The model is based on the temporal, vertical, and modular airspace sectorisation parameters in order to optimize flight efficiency. The presented model brings significant improvement in flight efficiency (in terms of reduced flight distance for air carriers that planned to fly through the selected flexible airspace structure (LI_RST-49.
On Improving Efficiency of Differential Evolution for Aerodynamic Shape Optimization Applications
Madavan, Nateri K.
2004-01-01
Differential Evolution (DE) is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Although DE offers several advantages over traditional optimization approaches, its use in applications such as aerodynamic shape optimization where the objective function evaluations are computationally expensive is limited by the large number of function evaluations often required. In this paper various approaches for improving the efficiency of DE are reviewed and discussed. These approaches are implemented in a DE-based aerodynamic shape optimization method that uses a Navier-Stokes solver for the objective function evaluations. Parallelization techniques on distributed computers are used to reduce turnaround times. Results are presented for the inverse design of a turbine airfoil. The efficiency improvements achieved by the different approaches are evaluated and compared.
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.
Clustering methods for the optimization of atomic cluster structure
Bagattini, Francesco; Schoen, Fabio; Tigli, Luca
2018-04-01
In this paper, we propose a revised global optimization method and apply it to large scale cluster conformation problems. In the 1990s, the so-called clustering methods were considered among the most efficient general purpose global optimization techniques; however, their usage has quickly declined in recent years, mainly due to the inherent difficulties of clustering approaches in large dimensional spaces. Inspired from the machine learning literature, we redesigned clustering methods in order to deal with molecular structures in a reduced feature space. Our aim is to show that by suitably choosing a good set of geometrical features coupled with a very efficient descent method, an effective optimization tool is obtained which is capable of finding, with a very high success rate, all known putative optima for medium size clusters without any prior information, both for Lennard-Jones and Morse potentials. The main result is that, beyond being a reliable approach, the proposed method, based on the idea of starting a computationally expensive deep local search only when it seems worth doing so, is capable of saving a huge amount of searches with respect to an analogous algorithm which does not employ a clustering phase. In this paper, we are not claiming the superiority of the proposed method compared to specific, refined, state-of-the-art procedures, but rather indicating a quite straightforward way to save local searches by means of a clustering scheme working in a reduced variable space, which might prove useful when included in many modern methods.
A Gradient Taguchi Method for Engineering Optimization
Hwang, Shun-Fa; Wu, Jen-Chih; He, Rong-Song
2017-10-01
To balance the robustness and the convergence speed of optimization, a novel hybrid algorithm consisting of Taguchi method and the steepest descent method is proposed in this work. Taguchi method using orthogonal arrays could quickly find the optimum combination of the levels of various factors, even when the number of level and/or factor is quite large. This algorithm is applied to the inverse determination of elastic constants of three composite plates by combining numerical method and vibration testing. For these problems, the proposed algorithm could find better elastic constants in less computation cost. Therefore, the proposed algorithm has nice robustness and fast convergence speed as compared to some hybrid genetic algorithms.
Computational efficiency for the surface renewal method
Kelley, Jason; Higgins, Chad
2018-04-01
Measuring surface fluxes using the surface renewal (SR) method requires programmatic algorithms for tabulation, algebraic calculation, and data quality control. A number of different methods have been published describing automated calibration of SR parameters. Because the SR method utilizes high-frequency (10 Hz+) measurements, some steps in the flux calculation are computationally expensive, especially when automating SR to perform many iterations of these calculations. Several new algorithms were written that perform the required calculations more efficiently and rapidly, and that tested for sensitivity to length of flux averaging period, ability to measure over a large range of lag timescales, and overall computational efficiency. These algorithms utilize signal processing techniques and algebraic simplifications that demonstrate simple modifications that dramatically improve computational efficiency. The results here complement efforts by other authors to standardize a robust and accurate computational SR method. Increased speed of computation time grants flexibility to implementing the SR method, opening new avenues for SR to be used in research, for applied monitoring, and in novel field deployments.
Efficiency enhancement of a gas turbine cycle using an optimized tubular recuperative heat exchanger
International Nuclear Information System (INIS)
Sayyaadi, Hoseyn; Mehrabipour, Reza
2012-01-01
A simple gas turbine cycle namely as the Kraftwerk Union AG unit including a Siemens gas turbine model V93.1 with 60 MW nominal power and 26.0% thermal efficiency utilized in the Fars power plant located is considered for the efficiency enhancement. A typical tubular vertical recuperative heat exchanger is designed in order to integrate into the cycle as an air pre-heater for thermal efficiency improvement. Thermal and geometric specifications of the recuperative heat exchanger are obtained in a multi-objective optimization process. The exergetic efficiency of the gas cycle is maximized while the payback time for the capital investment of the recuperator is minimized. Combination of these objectives and decision variables with suitable engineering and physical constraints makes a set of the MINLP optimization problem. Optimization programming is performed using the NSGA-II algorithm and Pareto optimal frontiers are obtained in three cases including the minimum, average and maximum ambient air temperatures. In each case, the final optimal solution has been selected using three decision-making approaches including the fuzzy Bellman-Zadeh, LINMAP and TOPSIS methods. It has been shown that the TOPSIS and LINMAP decision-makers when applied on the Pareto frontier which is obtained at average ambient air temperature yields best results in comparison to other cases. -- Highlights: ► A simple Brayton gas cycle is considered for the efficiency improvement by integrating of a recuperator. ► Objective functions based on thermodynamic and economic analysis are obtained. ► The payback time for the capital investment is minimized and the exergetic efficiency of the system is maximized. ► Pareto optimal frontiers at various site conditions are obtained. ► A final optimal configuration is found using various decision-making approaches.
Optimized iterative decoding method for TPC coded CPM
Ma, Yanmin; Lai, Penghui; Wang, Shilian; Xie, Shunqin; Zhang, Wei
2018-05-01
Turbo Product Code (TPC) coded Continuous Phase Modulation (CPM) system (TPC-CPM) has been widely used in aeronautical telemetry and satellite communication. This paper mainly investigates the improvement and optimization on the TPC-CPM system. We first add the interleaver and deinterleaver to the TPC-CPM system, and then establish an iterative system to iteratively decode. However, the improved system has a poor convergence ability. To overcome this issue, we use the Extrinsic Information Transfer (EXIT) analysis to find the optimal factors for the system. The experiments show our method is efficient to improve the convergence performance.
Computerized method for rapid optimization of immunoassays
International Nuclear Information System (INIS)
Rousseau, F.; Forest, J.C.
1990-01-01
The authors have developed an one step quantitative method for radioimmunoassay optimization. The method is rapid and necessitates only to perform a series of saturation curves with different titres of the antiserum. After calculating the saturation point at several antiserum titres using the Scatchard plot, the authors have produced a table that predicts the main characteristics of the standard curve (Bo/T, Bo and T) that will prevail for any combination of antiserum titre and percentage of sites saturation. The authors have developed a microcomputer program able to interpolate all the data needed to produce such a table from the results of the saturation curves. This computer program permits also to predict the sensitivity of the assay at any experimental conditions if the antibody does not discriminate between the labeled and the non labeled antigen. The authors have tested the accuracy of this optimization table with two in house RIA systems: 17-β-estradiol, and hLH. The results obtained experimentally, including sensitivity determinations, were concordant with those predicted from the optimization table. This method accerelates and improves greatly the process of optimization of radioimmunoassays [fr
Decomposition based parallel processing technique for efficient collaborative optimization
International Nuclear Information System (INIS)
Park, Hyung Wook; Kim, Sung Chan; Kim, Min Soo; Choi, Dong Hoon
2000-01-01
In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several MultiDisciplinary Analysis SubSystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and Multidisciplinary Design Optimization(MDO) methodology
Optimal Learning for Efficient Experimentation in Nanotechnology and Biochemistry
2015-12-22
AFRL-AFOSR-VA-TR-2016-0018 Optimal Learning for Efficient Experimentation in Nanotechnology, Biochemistry Warren Powell TRUSTEES OF PRINCETON... Biochemistry 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-12-1-0200 5c. PROGRAM ELEMENT NUMBER 61102F 6. AUTHOR(S) Warren Powell 5d. PROJECT NUMBER 5e...scientists. 15. SUBJECT TERMS Biochemistry 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF 19a. NAME OF RESPONSIBLE PERSON Warren
International Nuclear Information System (INIS)
Gao, Hao
2016-01-01
For the treatment planning during intensity modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT), beam fluence maps can be first optimized via fluence map optimization (FMO) under the given dose prescriptions and constraints to conformally deliver the radiation dose to the targets while sparing the organs-at-risk, and then segmented into deliverable MLC apertures via leaf or arc sequencing algorithms. This work is to develop an efficient algorithm for FMO based on alternating direction method of multipliers (ADMM). Here we consider FMO with the least-square cost function and non-negative fluence constraints, and its solution algorithm is based on ADMM, which is efficient and simple-to-implement. In addition, an empirical method for optimizing the ADMM parameter is developed to improve the robustness of the ADMM algorithm. The ADMM based FMO solver was benchmarked with the quadratic programming method based on the interior-point (IP) method using the CORT dataset. The comparison results suggested the ADMM solver had a similar plan quality with slightly smaller total objective function value than IP. A simple-to-implement ADMM based FMO solver with empirical parameter optimization is proposed for IMRT or VMAT. (paper)
Opportunities of Optimization in Administrative Structures for Efficient Management
Directory of Open Access Journals (Sweden)
Venelin Terziev
2017-12-01
Full Text Available Current paper presents studies on the administrative structures in order to optimize the activities and the overall management through the example of the Bulgarian Commission for Protection against Discrimination. It aims at establishing duplicate functions in the organization under study. The main tasks in the analysis are related to the display of the basic findings and conclusions for the strongest sides and the fields for improvement regarding the relevance, the effectiveness and the efficiency of the administration of the Commission for Protection against Discrimination in Bulgaria. The following areas are thoroughly and critically analyzed: relevance of the functions and efficiency of the activity. As a result of the study a Strategy for Organizational Development and a Training Plan have been drafted.
Global Optimization Ensemble Model for Classification Methods
Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab
2014-01-01
Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382
Global Optimization Ensemble Model for Classification Methods
Directory of Open Access Journals (Sweden)
Hina Anwar
2014-01-01
Full Text Available Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity.
Boosting the IGCLC process efficiency by optimizing the desulfurization step
International Nuclear Information System (INIS)
Hamers, H.P.; Romano, M.C.; Spallina, V.; Chiesa, P.; Gallucci, F.; Sint Annaland, M. van
2015-01-01
Highlights: • Pre-CLC hot gas desulfurization and post-CLC desulfurization are assessed. • Process efficiency increases by 0.5–1% points with alternative desulfurization methods. • Alternative desulfurization methods are more beneficial for CFB configurations. - Abstract: In this paper the influence of the desulfurization method on the process efficiency of an integrated gasification chemical-looping combustion (IGCLC) systems is investigated for both packed beds and circulating fluidized bed CLC systems. Both reactor types have been integrated in an IGCLC power plant, in which three desulfurization methods have been compared: conventional cold gas desulfurization with Selexol (CGD), hot gas desulfurization with ZnO (HGD) and flue gas desulfurization after the CLC reactors (post-CLC). For CLC with packed bed reactors, the efficiency gain of the alternative desulfurization methods is about 0.5–0.7% points. This is relatively small, because of the relatively large amount of steam that has to be mixed with the fuel to avoid carbon deposition on the oxygen carrier. The HGD and post-CLC configurations do not contain a saturator and therefore more steam has to be mixed with a negative influence on the process efficiency. Carbon deposition is not an issue for circulating fluidized bed systems and therefore a somewhat higher efficiency gain of 0.8–1.0% point can be reached for this reactor system, assuming that complete fuel conversion can be reached and no sulfur species are formed on the solid, which is however thermodynamically possible for iron and manganese based oxygen carriers. From this study, it can be concluded that the adaptation of the desulfurization method results in higher process efficiencies, especially for the circulating fluidized bed system, while the number of operating units is reduced.
Optimal control methods for rapidly time-varying Hamiltonians
International Nuclear Information System (INIS)
Motzoi, F.; Merkel, S. T.; Wilhelm, F. K.; Gambetta, J. M.
2011-01-01
In this article, we develop a numerical method to find optimal control pulses that accounts for the separation of timescales between the variation of the input control fields and the applied Hamiltonian. In traditional numerical optimization methods, these timescales are treated as being the same. While this approximation has had much success, in applications where the input controls are filtered substantially or mixed with a fast carrier, the resulting optimized pulses have little relation to the applied physical fields. Our technique remains numerically efficient in that the dimension of our search space is only dependent on the variation of the input control fields, while our simulation of the quantum evolution is accurate on the timescale of the fast variation in the applied Hamiltonian.
Yan, Rongge; Guo, Xiaoting; Cao, Shaoqing; Zhang, Changgeng
2018-05-01
Magnetically coupled resonance (MCR) wireless power transfer (WPT) system is a promising technology in electric energy transmission. But, if its system parameters are designed unreasonably, output power and transmission efficiency will be low. Therefore, optimized parameters design of MCR WPT has important research value. In the MCR WPT system with designated coil structure, the main parameters affecting output power and transmission efficiency are the distance between the coils, the resonance frequency and the resistance of the load. Based on the established mathematical model and the differential evolution algorithm, the change of output power and transmission efficiency with parameters can be simulated. From the simulation results, it can be seen that output power and transmission efficiency of the two-coil MCR WPT system and four-coil one with designated coil structure are improved. The simulation results confirm the validity of the optimization method for MCR WPT system with designated coil structure.
STOCHASTIC GRADIENT METHODS FOR UNCONSTRAINED OPTIMIZATION
Directory of Open Access Journals (Sweden)
Nataša Krejić
2014-12-01
Full Text Available This papers presents an overview of gradient based methods for minimization of noisy functions. It is assumed that the objective functions is either given with error terms of stochastic nature or given as the mathematical expectation. Such problems arise in the context of simulation based optimization. The focus of this presentation is on the gradient based Stochastic Approximation and Sample Average Approximation methods. The concept of stochastic gradient approximation of the true gradient can be successfully extended to deterministic problems. Methods of this kind are presented for the data fitting and machine learning problems.
QUADRO: A SUPERVISED DIMENSION REDUCTION METHOD VIA RAYLEIGH QUOTIENT OPTIMIZATION.
Fan, Jianqing; Ke, Zheng Tracy; Liu, Han; Xia, Lucy
We propose a novel Rayleigh quotient based sparse quadratic dimension reduction method-named QUADRO (Quadratic Dimension Reduction via Rayleigh Optimization)-for analyzing high-dimensional data. Unlike in the linear setting where Rayleigh quotient optimization coincides with classification, these two problems are very different under nonlinear settings. In this paper, we clarify this difference and show that Rayleigh quotient optimization may be of independent scientific interests. One major challenge of Rayleigh quotient optimization is that the variance of quadratic statistics involves all fourth cross-moments of predictors, which are infeasible to compute for high-dimensional applications and may accumulate too many stochastic errors. This issue is resolved by considering a family of elliptical models. Moreover, for heavy-tail distributions, robust estimates of mean vectors and covariance matrices are employed to guarantee uniform convergence in estimating non-polynomially many parameters, even though only the fourth moments are assumed. Methodologically, QUADRO is based on elliptical models which allow us to formulate the Rayleigh quotient maximization as a convex optimization problem. Computationally, we propose an efficient linearized augmented Lagrangian method to solve the constrained optimization problem. Theoretically, we provide explicit rates of convergence in terms of Rayleigh quotient under both Gaussian and general elliptical models. Thorough numerical results on both synthetic and real datasets are also provided to back up our theoretical results.
Efficiency and stability of the DSBGK method
Li, Jun
2012-07-09
Recently, the DSBGK method (Note: the original name DS-BGK is changed to DSBGK for simplicity) was proposed to reduce the stochastic noise in simulating rarefied gas flows at low velocity. Its total computational time is almost independent of the magnitude of deviation from equilibrium state. It was verified by the DSMC method in different benchmark problems over a wide range of Kn number. Some simulation results of the closed lid-driven cavity flow, thermal transpiration flow and the open channel flow by the DSBGK method are given here to show its efficiency and numerical stability. In closed problems, the density distribution is subject to unphysical fluctuation due to the absence of density constraint at the boundary. Thus, many simulated molecules are employed by DSBGK simulations to improve the stability and reduce the magnitude of fluctuation. This increases the memory usage remarkably but has small influence to the efficiency of DSBGK simulations. In open problems, the DSBGK simulation remains stable when using about 10 simulated molecules per cell because the fixed number densities at open boundaries eliminate the unphysical fluctuation. Small modification to the CLL reflection model is introduced to further improve the efficiency slightly.
Efficiency and stability of the DSBGK method
Li, Jun
2012-01-01
Recently, the DSBGK method (Note: the original name DS-BGK is changed to DSBGK for simplicity) was proposed to reduce the stochastic noise in simulating rarefied gas flows at low velocity. Its total computational time is almost independent of the magnitude of deviation from equilibrium state. It was verified by the DSMC method in different benchmark problems over a wide range of Kn number. Some simulation results of the closed lid-driven cavity flow, thermal transpiration flow and the open channel flow by the DSBGK method are given here to show its efficiency and numerical stability. In closed problems, the density distribution is subject to unphysical fluctuation due to the absence of density constraint at the boundary. Thus, many simulated molecules are employed by DSBGK simulations to improve the stability and reduce the magnitude of fluctuation. This increases the memory usage remarkably but has small influence to the efficiency of DSBGK simulations. In open problems, the DSBGK simulation remains stable when using about 10 simulated molecules per cell because the fixed number densities at open boundaries eliminate the unphysical fluctuation. Small modification to the CLL reflection model is introduced to further improve the efficiency slightly.
Zhang, Li; Wu, Kexin; Liu, Yang
2017-12-01
A multi-objective performance optimization method is proposed, and the problem that single structural parameters of small fan balance the optimization between the static characteristics and the aerodynamic noise is solved. In this method, three structural parameters are selected as the optimization variables. Besides, the static pressure efficiency and the aerodynamic noise of the fan are regarded as the multi-objective performance. Furthermore, the response surface method and the entropy method are used to establish the optimization function between the optimization variables and the multi-objective performances. Finally, the optimized model is found when the optimization function reaches its maximum value. Experimental data shows that the optimized model not only enhances the static characteristics of the fan but also obviously reduces the noise. The results of the study will provide some reference for the optimization of multi-objective performance of other types of rotating machinery.
Effects of upper body parameters on biped walking efficiency studied by dynamic optimization
Directory of Open Access Journals (Sweden)
Kang An
2016-12-01
Full Text Available Walking efficiency is one of the considerations for designing biped robots. This article uses the dynamic optimization method to study the effects of upper body parameters, including upper body length and mass, on walking efficiency. Two minimal actuations, hip joint torque and push-off impulse, are used in the walking model, and minimal constraints are set in a free search using the dynamic optimization. Results show that there is an optimal solution of upper body length for the efficient walking within a range of walking speed and step length. For short step length, walking with a lighter upper body mass is found to be more efficient and vice versa. It is also found that for higher speed locomotion, the increase of the upper body length and mass can make the walking gait optimal rather than other kind of gaits. In addition, the typical strategy of an optimal walking gait is that just actuating the swing leg at the beginning of the step.
Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A
2012-07-02
Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of
Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach
Amin, Osama
2015-04-23
In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.
Energy Efficiency - Spectral Efficiency Trade-off: A Multiobjective Optimization Approach
Amin, Osama; Bedeer, Ebrahim; Ahmed, Mohamed; Dobre, Octavia
2015-01-01
In this paper, we consider the resource allocation problem for energy efficiency (EE) - spectral efficiency (SE) trade-off. Unlike traditional research that uses the EE as an objective function and imposes constraints either on the SE or achievable rate, we propound a multiobjective optimization approach that can flexibly switch between the EE and SE functions or change the priority level of each function using a trade-off parameter. Our dynamic approach is more tractable than the conventional approaches and more convenient to realistic communication applications and scenarios. We prove that the multiobjective optimization of the EE and SE is equivalent to a simple problem that maximizes the achievable rate/SE and minimizes the total power consumption. Then we apply the generalized framework of the resource allocation for the EE-SE trade-off to optimally allocate the subcarriers’ power for orthogonal frequency division multiplexing (OFDM) with imperfect channel estimation. Finally, we use numerical results to discuss the choice of the trade-off parameter and study the effect of the estimation error, transmission power budget and channel-to-noise ratio on the multiobjective optimization.
Layout optimization with algebraic multigrid methods
Regler, Hans; Ruede, Ulrich
1993-01-01
Finding the optimal position for the individual cells (also called functional modules) on the chip surface is an important and difficult step in the design of integrated circuits. This paper deals with the problem of relative placement, that is the minimization of a quadratic functional with a large, sparse, positive definite system matrix. The basic optimization problem must be augmented by constraints to inhibit solutions where cells overlap. Besides classical iterative methods, based on conjugate gradients (CG), we show that algebraic multigrid methods (AMG) provide an interesting alternative. For moderately sized examples with about 10000 cells, AMG is already competitive with CG and is expected to be superior for larger problems. Besides the classical 'multiplicative' AMG algorithm where the levels are visited sequentially, we propose an 'additive' variant of AMG where levels may be treated in parallel and that is suitable as a preconditioner in the CG algorithm.
Application of an efficient Bayesian discretization method to biomedical data
Directory of Open Access Journals (Sweden)
Gopalakrishnan Vanathi
2011-07-01
Full Text Available Abstract Background Several data mining methods require data that are discrete, and other methods often perform better with discrete data. We introduce an efficient Bayesian discretization (EBD method for optimal discretization of variables that runs efficiently on high-dimensional biomedical datasets. The EBD method consists of two components, namely, a Bayesian score to evaluate discretizations and a dynamic programming search procedure to efficiently search the space of possible discretizations. We compared the performance of EBD to Fayyad and Irani's (FI discretization method, which is commonly used for discretization. Results On 24 biomedical datasets obtained from high-throughput transcriptomic and proteomic studies, the classification performances of the C4.5 classifier and the naïve Bayes classifier were statistically significantly better when the predictor variables were discretized using EBD over FI. EBD was statistically significantly more stable to the variability of the datasets than FI. However, EBD was less robust, though not statistically significantly so, than FI and produced slightly more complex discretizations than FI. Conclusions On a range of biomedical datasets, a Bayesian discretization method (EBD yielded better classification performance and stability but was less robust than the widely used FI discretization method. The EBD discretization method is easy to implement, permits the incorporation of prior knowledge and belief, and is sufficiently fast for application to high-dimensional data.
A least squares approach for efficient and reliable short-term versus long-term optimization
DEFF Research Database (Denmark)
Christiansen, Lasse Hjuler; Capolei, Andrea; Jørgensen, John Bagterp
2017-01-01
The uncertainties related to long-term forecasts of oil prices impose significant financial risk on ventures of oil production. To minimize risk, oil companies are inclined to maximize profit over short-term horizons ranging from months to a few years. In contrast, conventional production...... optimization maximizes long-term profits over horizons that span more than a decade. To address this challenge, the oil literature has introduced short-term versus long-term optimization. Ideally, this problem is solved by a posteriori multi-objective optimization methods that generate an approximation...... the balance between the objectives, leaving an unfulfilled potential to increase profits. To promote efficient and reliable short-term versus long-term optimization, this paper introduces a natural way to characterize desirable Pareto points and proposes a novel least squares (LS) method. Unlike hierarchical...
Layout optimization using the homogenization method
Suzuki, Katsuyuki; Kikuchi, Noboru
1993-01-01
A generalized layout problem involving sizing, shape, and topology optimization is solved by using the homogenization method for three-dimensional linearly elastic shell structures in order to seek a possibility of establishment of an integrated design system of automotive car bodies, as an extension of the previous work by Bendsoe and Kikuchi. A formulation of a three-dimensional homogenized shell, a solution algorithm, and several examples of computing the optimum layout are presented in this first part of the two articles.
Hydrothermal optimal power flow using continuation method
International Nuclear Information System (INIS)
Raoofat, M.; Seifi, H.
2001-01-01
The problem of optimal economic operation of hydrothermal electric power systems is solved using powerful continuation method. While in conventional approach, fixed generation voltages are used to avoid convergence problems, in the algorithm, they are treated as variables so that better solutions can be obtained. The algorithm is tested for a typical 5-bus and 17-bus New Zealand networks. Its capabilities and promising results are assessed
Methods for Large-Scale Nonlinear Optimization.
1980-05-01
STANFORD, CALIFORNIA 94305 METHODS FOR LARGE-SCALE NONLINEAR OPTIMIZATION by Philip E. Gill, Waiter Murray, I Michael A. Saunden, and Masgaret H. Wright...typical iteration can be partitioned so that where B is an m X m basise matrix. This partition effectively divides the vari- ables into three classes... attention is given to the standard of the coding or the documentation. A much better way of obtaining mathematical software is from a software library
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.
Directory of Open Access Journals (Sweden)
Guo-Qiang Zeng
2014-01-01
Full Text Available As a novel evolutionary optimization method, extremal optimization (EO has been successfully applied to a variety of combinatorial optimization problems. However, the applications of EO in continuous optimization problems are relatively rare. This paper proposes an improved real-coded population-based EO method (IRPEO for continuous unconstrained optimization problems. The key operations of IRPEO include generation of real-coded random initial population, evaluation of individual and population fitness, selection of bad elements according to power-law probability distribution, generation of new population based on uniform random mutation, and updating the population by accepting the new population unconditionally. The experimental results on 10 benchmark test functions with the dimension N=30 have shown that IRPEO is competitive or even better than the recently reported various genetic algorithm (GA versions with different mutation operations in terms of simplicity, effectiveness, and efficiency. Furthermore, the superiority of IRPEO to other evolutionary algorithms such as original population-based EO, particle swarm optimization (PSO, and the hybrid PSO-EO is also demonstrated by the experimental results on some benchmark functions.
International Nuclear Information System (INIS)
Cao, Dingzhou; Murat, Alper; Chinnam, Ratna Babu
2013-01-01
This paper proposes a decomposition-based approach to exactly solve the multi-objective Redundancy Allocation Problem for series-parallel systems. Redundancy allocation problem is a form of reliability optimization and has been the subject of many prior studies. The majority of these earlier studies treat redundancy allocation problem as a single objective problem maximizing the system reliability or minimizing the cost given certain constraints. The few studies that treated redundancy allocation problem as a multi-objective optimization problem relied on meta-heuristic solution approaches. However, meta-heuristic approaches have significant limitations: they do not guarantee that Pareto points are optimal and, more importantly, they may not identify all the Pareto-optimal points. In this paper, we treat redundancy allocation problem as a multi-objective problem, as is typical in practice. We decompose the original problem into several multi-objective sub-problems, efficiently and exactly solve sub-problems, and then systematically combine the solutions. The decomposition-based approach can efficiently generate all the Pareto-optimal solutions for redundancy allocation problems. Experimental results demonstrate the effectiveness and efficiency of the proposed method over meta-heuristic methods on a numerical example taken from the literature.
portfolio optimization based on nonparametric estimation methods
Directory of Open Access Journals (Sweden)
mahsa ghandehari
2017-03-01
Full Text Available One of the major issues investors are facing with in capital markets is decision making about select an appropriate stock exchange for investing and selecting an optimal portfolio. This process is done through the risk and expected return assessment. On the other hand in portfolio selection problem if the assets expected returns are normally distributed, variance and standard deviation are used as a risk measure. But, the expected returns on assets are not necessarily normal and sometimes have dramatic differences from normal distribution. This paper with the introduction of conditional value at risk ( CVaR, as a measure of risk in a nonparametric framework, for a given expected return, offers the optimal portfolio and this method is compared with the linear programming method. The data used in this study consists of monthly returns of 15 companies selected from the top 50 companies in Tehran Stock Exchange during the winter of 1392 which is considered from April of 1388 to June of 1393. The results of this study show the superiority of nonparametric method over the linear programming method and the nonparametric method is much faster than the linear programming method.
Energy-Efficient Optimization for HARQ Schemes over Time-Correlated Fading Channels
Shi, Zheng; Ma, Shaodan; Yang, Guanghua; Alouini, Mohamed-Slim
2018-01-01
in the optimization, which further differentiates this work from prior ones. Using a unified expression of asymptotic outage probabilities, optimal transmission powers and optimal rate are derived in closed-forms to maximize the energy efficiency while satisfying
Chen, Xi; Xu, Yixuan; Liu, Anfeng
2017-04-19
High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs. However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%.
Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.
Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie
2018-05-04
Particle swarm optimization is a powerful metaheuristic population-based global optimization algorithm. However, when applied to non-separable objective functions its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant particle swarm optimization algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates a superior performance across several nonlinear, multimodal benchmark functions compared to the rotation-invariant Particle Swam Optimization (PSO) algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in ReaxFF-lg reactive force field is carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents a better performance compared to a Genetic Algorithm optimization method in the optimization of a ReaxFF-lg correction model parameters. The computational framework is implemented in a standalone C++ code that allows a straightforward development of ReaxFF reactive force fields.
An Efficient Vital Area Identification Method
International Nuclear Information System (INIS)
Jung, Woo Sik
2017-01-01
A new Vital Area Identification (VAI) method was developed in this study for minimizing the burden of VAI procedure. It was accomplished by performing simplification of sabotage event trees or Probabilistic Safety Assessment (PSA) event trees at the very first stage of VAI procedure. Target sets and prevention sets are calculated from the sabotage fault tree. The rooms in the shortest (most economical) prevention set are selected and protected as vital areas. All physical protection is emphasized to protect these vital areas. All rooms in the protected area, the sabotage of which could lead to core damage, should be incorporated into sabotage fault tree. So, sabotage fault tree development is a very difficult task that requires high engineering costs. IAEA published INFCIRC/225/Rev.5 in 2011 which includes principal international guidelines for the physical protection of nuclear material and nuclear installations. A new efficient VAI method was developed and demonstrated in this study. Since this method drastically reduces VAI problem size, it provides very quick and economical VAI procedure. A consistent and integrated VAI procedure had been developed by taking advantage of PSA results, and more efficient VAI method was further developed in this study by inserting PSA event tree simplification at the initial stage of VAI procedure.
Optimization of the working process of the axial compressor according to the criterion of efficiency
Baturin, O. V.; Popov, G. M.; Goryachkin, E. S.; Novikova, Yu D.
2017-01-01
The paper shows search results of the optimal shape of low pressure compressor blades of the industrial gas turbine plant using methods of computational fluid dynamics and multicriteria methods of mathematical optimization. The essence of the methods is that an increase in compressor efficiency should be achieved by increasing the degree of compression up to 2%, and reducing the air flow to 8% relative to basic engine parameters. However, the compressor design elements should be retained as maximally unchanged as possible. During the work, the calculation model of the workflow in the test compressor has been developed and verified in the NUMECA software package, the automated algorithm of the blades shape change has been also developed using a small number of variables, while maintaining its stress-strain state. It allows reducing the number of changeable variables more than twofold. As the result of this study, the option of compressor performance was found, which can increase its efficiency by 1.3% (abs.).
Parallel processing based decomposition technique for efficient collaborative optimization
International Nuclear Information System (INIS)
Park, Hyung Wook; Kim, Sung Chan; Kim, Min Soo; Choi, Dong Hoon
2001-01-01
In practical design studies, most of designers solve multidisciplinary problems with large sized and complex design system. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder the original design processes to minimize total computational cost. This is accomplished by decomposing large multidisciplinary problem into several MultiDisciplinary Analysis SubSystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and Multidisciplinary Design Optimization(MDO) methodology
Topology optimization of hyperelastic structures using a level set method
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.
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
Assisted closed-loop optimization of SSVEP-BCI efficiency
Directory of Open Access Journals (Sweden)
Jacobo eFernandez-Vargas
2013-02-01
Full Text Available We designed a novel assisted closed-loop optimization protocol to improve the efficiency of brain computer interfaces (BCI based on steady state visually evoked potentials (SSVEP. In traditional paradigms, the control over the BCI-performance completely depends on the subjects’ ability to learn from the given feedback cues. By contrast, in the proposed protocol both the subject and the machine share information and control over the BCI goal. Generally, the innovative assistance consists in the delivery of online information together with the online adaptation of BCI stimuli properties. In our case, this adaptive optimization process is realized by (i a closed-loop search for the best set of SSVEP flicker frequencies and (ii feedback of actual SSVEP magnitudes to both the subject and the machine. These closed-loop interactions between subject and machine are evaluated in real-time by continuous measurement of their efficiencies, which are used as online criteria to adapt the BCI control parameters. The proposed protocol aims to compensate for variability in possibly unknown subjects’ state and trait dimensions. In a study with N = 18 subjects, we found significant evidence that our protocol outperformed classic SSVEP-BCI control paradigms. Evidence is presented that it takes indeed into account interindividual variabilities: e.g. under the new protocol, baseline resting state EEG measures predict subjects’ BCI performances. This paper illustrates the promising potential of assisted closed-loop protocols in BCI systems. Probably their applicability might be expanded to innovative uses, e.g. as possible new diagnostic/therapeutic tools for clinical contexts and as new paradigms for basic research.
Efficiency optimization of wireless power transmission systems for active capsule endoscopes.
Zhiwei, Jia; Guozheng, Yan; Jiangpingping; Zhiwu, Wang; Hua, Liu
2011-10-01
Multipurpose active capsule endoscopes have drawn considerable attention in recent years, but these devices continue to suffer from energy limitations. A wireless power supply system is regarded as a practical way to overcome the power shortage problem in such devices. This paper focuses on the efficiency optimization of a wireless energy supply system with size and safety constraints. A mathematical programming model in which these constraints are considered is proposed for transmission efficiency, optimal frequency and current, and overall system effectiveness. To verify the feasibility of the proposed method, we use a wireless active capsule endoscope as an illustrative example. The achieved efficiency can be regarded as an index for evaluating the system, and the proposed approach can be used to direct the design of transmitting and receiving coils.
Efficiency optimization of wireless power transmission systems for active capsule endoscopes
International Nuclear Information System (INIS)
Zhiwei, Jia; Guozheng, Yan; Jiangpingping; Zhiwu, Wang; Hua, Liu
2011-01-01
Multipurpose active capsule endoscopes have drawn considerable attention in recent years, but these devices continue to suffer from energy limitations. A wireless power supply system is regarded as a practical way to overcome the power shortage problem in such devices. This paper focuses on the efficiency optimization of a wireless energy supply system with size and safety constraints. A mathematical programming model in which these constraints are considered is proposed for transmission efficiency, optimal frequency and current, and overall system effectiveness. To verify the feasibility of the proposed method, we use a wireless active capsule endoscope as an illustrative example. The achieved efficiency can be regarded as an index for evaluating the system, and the proposed approach can be used to direct the design of transmitting and receiving coils
Energy Technology Data Exchange (ETDEWEB)
Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew
2006-01-01
Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and
International Nuclear Information System (INIS)
Santos Coelho, Leandro dos
2009-01-01
The reliability-redundancy optimization problems can involve the selection of components with multiple choices and redundancy levels that produce maximum benefits, and are subject to the cost, weight, and volume constraints. Many classical mathematical methods have failed in handling nonconvexities and nonsmoothness in reliability-redundancy optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solutions. One of these meta-heuristics is the particle swarm optimization (PSO). PSO is a population-based heuristic optimization technique inspired by social behavior of bird flocking and fish schooling. This paper presents an efficient PSO algorithm based on Gaussian distribution and chaotic sequence (PSO-GC) to solve the reliability-redundancy optimization problems. In this context, two examples in reliability-redundancy design problems are evaluated. Simulation results demonstrate that the proposed PSO-GC is a promising optimization technique. PSO-GC performs well for the two examples of mixed-integer programming in reliability-redundancy applications considered in this paper. The solutions obtained by the PSO-GC are better than the previously best-known solutions available in the recent literature
Energy Technology Data Exchange (ETDEWEB)
Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br
2009-04-15
The reliability-redundancy optimization problems can involve the selection of components with multiple choices and redundancy levels that produce maximum benefits, and are subject to the cost, weight, and volume constraints. Many classical mathematical methods have failed in handling nonconvexities and nonsmoothness in reliability-redundancy optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solutions. One of these meta-heuristics is the particle swarm optimization (PSO). PSO is a population-based heuristic optimization technique inspired by social behavior of bird flocking and fish schooling. This paper presents an efficient PSO algorithm based on Gaussian distribution and chaotic sequence (PSO-GC) to solve the reliability-redundancy optimization problems. In this context, two examples in reliability-redundancy design problems are evaluated. Simulation results demonstrate that the proposed PSO-GC is a promising optimization technique. PSO-GC performs well for the two examples of mixed-integer programming in reliability-redundancy applications considered in this paper. The solutions obtained by the PSO-GC are better than the previously best-known solutions available in the recent literature.
Optimal management strategies in variable environments: Stochastic optimal control methods
Williams, B.K.
1985-01-01
Dynamic optimization was used to investigate the optimal defoliation of salt desert shrubs in north-western Utah. Management was formulated in the context of optimal stochastic control theory, with objective functions composed of discounted or time-averaged biomass yields. Climatic variability and community patterns of salt desert shrublands make the application of stochastic optimal control both feasible and necessary. A primary production model was used to simulate shrub responses and harvest yields under a variety of climatic regimes and defoliation patterns. The simulation results then were used in an optimization model to determine optimal defoliation strategies. The latter model encodes an algorithm for finite state, finite action, infinite discrete time horizon Markov decision processes. Three questions were addressed: (i) What effect do changes in weather patterns have on optimal management strategies? (ii) What effect does the discounting of future returns have? (iii) How do the optimal strategies perform relative to certain fixed defoliation strategies? An analysis was performed for the three shrub species, winterfat (Ceratoides lanata), shadscale (Atriplex confertifolia) and big sagebrush (Artemisia tridentata). In general, the results indicate substantial differences among species in optimal control strategies, which are associated with differences in physiological and morphological characteristics. Optimal policies for big sagebrush varied less with variation in climate, reserve levels and discount rates than did either shadscale or winterfat. This was attributed primarily to the overwintering of photosynthetically active tissue and to metabolic activity early in the growing season. Optimal defoliation of shadscale and winterfat generally was more responsive to differences in plant vigor and climate, reflecting the sensitivity of these species to utilization and replenishment of carbohydrate reserves. Similarities could be seen in the influence of both
An hp symplectic pseudospectral method for nonlinear optimal control
Peng, Haijun; Wang, Xinwei; Li, Mingwu; Chen, Biaosong
2017-01-01
An adaptive symplectic pseudospectral method based on the dual variational principle is proposed and is successfully applied to solving nonlinear optimal control problems in this paper. The proposed method satisfies the first order necessary conditions of continuous optimal control problems, also the symplectic property of the original continuous Hamiltonian system is preserved. The original optimal control problem is transferred into a set of nonlinear equations which can be solved easily by Newton-Raphson iterations, and the Jacobian matrix is found to be sparse and symmetric. The proposed method, on one hand, exhibits exponent convergence rates when the number of collocation points are increasing with the fixed number of sub-intervals; on the other hand, exhibits linear convergence rates when the number of sub-intervals is increasing with the fixed number of collocation points. Furthermore, combining with the hp method based on the residual error of dynamic constraints, the proposed method can achieve given precisions in a few iterations. Five examples highlight the high precision and high computational efficiency of the proposed method.
PRODUCT OPTIMIZATION METHOD BASED ON ANALYSIS OF OPTIMAL VALUES OF THEIR CHARACTERISTICS
Directory of Open Access Journals (Sweden)
Constantin D. STANESCU
2016-05-01
Full Text Available The paper presents an original method of optimizing products based on the analysis of optimal values of their characteristics . Optimization method comprises statistical model and analytical model . With this original method can easily and quickly obtain optimal product or material .
Hayashibe, Mitsuhiro; Shimoda, Shingo
2014-01-01
A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach
Hayashibe, Mitsuhiro; Shimoda, Shingo
2014-01-01
A human motor system can improve its behavior toward optimal movement. The skeletal system has more degrees of freedom than the task dimensions, which incurs an ill-posed problem. The multijoint system involves complex interaction torques between joints. To produce optimal motion in terms of energy consumption, the so-called cost function based optimization has been commonly used in previous works.Even if it is a fact that an optimal motor pattern is employed phenomenologically, there is no evidence that shows the existence of a physiological process that is similar to such a mathematical optimization in our central nervous system.In this study, we aim to find a more primitive computational mechanism with a modular configuration to realize adaptability and optimality without prior knowledge of system dynamics.We propose a novel motor control paradigm based on tacit learning with task space feedback. The motor command accumulation during repetitive environmental interactions, play a major role in the learning process. It is applied to a vertical cyclic reaching which involves complex interaction torques.We evaluated whether the proposed paradigm can learn how to optimize solutions with a 3-joint, planar biomechanical model. The results demonstrate that the proposed method was valid for acquiring motor synergy and resulted in energy efficient solutions for different load conditions. The case in feedback control is largely affected by the interaction torques. In contrast, the trajectory is corrected over time with tacit learning toward optimal solutions.Energy efficient solutions were obtained by the emergence of motor synergy. During learning, the contribution from feedforward controller is augmented and the one from the feedback controller is significantly minimized down to 12% for no load at hand, 16% for a 0.5 kg load condition.The proposed paradigm could provide an optimization process in redundant system with dynamic-model-free and cost-function-free approach.
Directory of Open Access Journals (Sweden)
Alicia Cordero
2018-01-01
Full Text Available We construct a family of derivative-free optimal iterative methods without memory to approximate a simple zero of a nonlinear function. Error analysis demonstrates that the without-memory class has eighth-order convergence and is extendable to with-memory class. The extension of new family to the with-memory one is also presented which attains the convergence order 15.5156 and a very high efficiency index 15.51561/4≈1.9847. Some particular schemes of the with-memory family are also described. Numerical examples and some dynamical aspects of the new schemes are given to support theoretical results.
Abdelhady, Amr, M.; Amin, Osama; Alouini, Mohamed-Slim
2016-01-01
Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.
Abdelhady, Amr, M.
2016-01-06
Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.
The methods and applications of optimization of radiation protection
International Nuclear Information System (INIS)
Liu Hua
2007-01-01
Optimization is the most important principle in radiation protection. The present article briefs the concept and up-to-date progress of optimization of protection, introduces some methods used in current optimization analysis, and presents various applications of optimization of protection. The author emphasizes that optimization of protection is a forward-looking iterative process aimed at preventing exposures before they occur. (author)
International Nuclear Information System (INIS)
Lee, Seung Min; Kim, Jong Hyun; Kim, Man Cheol; Seong, Poong Hyun
2016-01-01
Highlights: • We propose an appropriate automation rate that enables the best human performance. • We analyze the shortest working time considering Situation Awareness Recovery (SAR). • The optimized automation rate is estimated by integrating the automation and ostracism rate estimation methods. • The process to derive the optimized automation rate is demonstrated through case studies. - Abstract: Automation has been introduced in various industries, including the nuclear field, because it is commonly believed that automation promises greater efficiency, lower workloads, and fewer operator errors through reducing operator errors and enhancing operator and system performance. However, the excessive introduction of automation has deteriorated operator performance due to the side effects of automation, which are referred to as Out-of-the-Loop (OOTL), and this is critical issue that must be resolved. Thus, in order to determine the optimal level of automation introduction that assures the best human operator performance, a quantitative method of optimizing the automation is proposed in this paper. In order to propose the optimization method for determining appropriate automation levels that enable the best human performance, the automation rate and ostracism rate, which are estimation methods that quantitatively analyze the positive and negative effects of automation, respectively, are integrated. The integration was conducted in order to derive the shortest working time through considering the concept of situation awareness recovery (SAR), which states that the automation rate with the shortest working time assures the best human performance. The process to derive the optimized automation rate is demonstrated through an emergency operation scenario-based case study. In this case study, four types of procedures are assumed through redesigning the original emergency operating procedure according to the introduced automation and ostracism levels. Using the
Circular SAR Optimization Imaging Method of Buildings
Directory of Open Access Journals (Sweden)
Wang Jian-feng
2015-12-01
Full Text Available The Circular Synthetic Aperture Radar (CSAR can obtain the entire scattering properties of targets because of its great ability of 360° observation. In this study, an optimal orientation of the CSAR imaging algorithm of buildings is proposed by applying a combination of coherent and incoherent processing techniques. FEKO software is used to construct the electromagnetic scattering modes and simulate the radar echo. The FEKO imaging results are compared with the isotropic scattering results. On comparison, the optimal azimuth coherent accumulation angle of CSAR imaging of buildings is obtained. Practically, the scattering directions of buildings are unknown; therefore, we divide the 360° echo of CSAR into many overlapped and few angle echoes corresponding to the sub-aperture and then perform an imaging procedure on each sub-aperture. Sub-aperture imaging results are applied to obtain the all-around image using incoherent fusion techniques. The polarimetry decomposition method is used to decompose the all-around image and further retrieve the edge information of buildings successfully. The proposed method is validated with P-band airborne CSAR data from Sichuan, China.
Optimization methods for activities selection problems
Mahad, Nor Faradilah; Alias, Suriana; Yaakop, Siti Zulaika; Arshad, Norul Amanina Mohd; Mazni, Elis Sofia
2017-08-01
Co-curriculum activities must be joined by every student in Malaysia and these activities bring a lot of benefits to the students. By joining these activities, the students can learn about the time management and they can developing many useful skills. This project focuses on the selection of co-curriculum activities in secondary school using the optimization methods which are the Analytic Hierarchy Process (AHP) and Zero-One Goal Programming (ZOGP). A secondary school in Negeri Sembilan, Malaysia was chosen as a case study. A set of questionnaires were distributed randomly to calculate the weighted for each activity based on the 3 chosen criteria which are soft skills, interesting activities and performances. The weighted was calculated by using AHP and the results showed that the most important criteria is soft skills. Then, the ZOGP model will be analyzed by using LINGO Software version 15.0. There are two priorities to be considered. The first priority which is to minimize the budget for the activities is achieved since the total budget can be reduced by RM233.00. Therefore, the total budget to implement the selected activities is RM11,195.00. The second priority which is to select the co-curriculum activities is also achieved. The results showed that 9 out of 15 activities were selected. Thus, it can concluded that AHP and ZOGP approach can be used as the optimization methods for activities selection problem.
An Optimization Method for Virtual Globe Ocean Surface Dynamic Visualization
Directory of Open Access Journals (Sweden)
HUANG Wumeng
2016-12-01
Full Text Available The existing visualization method in the virtual globe mainly uses the projection grid to organize the ocean grid. This special grid organization has the defects in reflecting the difference characteristics of different ocean areas. The method of global ocean visualization based on global discrete grid can make up the defect of the projection grid method by matching with the discrete space of the virtual globe, so it is more suitable for the virtual ocean surface simulation application.But the available global discrete grids method has many problems which limiting its application such as the low efficiency of rendering and loading, the need of repairing grid crevices. To this point, we propose an optimization for the global discrete grids method. At first, a GPU-oriented multi-scale grid model of ocean surface which develops on the foundation of global discrete grids was designed to organize and manage the ocean surface grids. Then, in order to achieve the wind-drive wave dynamic rendering, this paper proposes a dynamic wave rendering method based on the multi-scale ocean surface grid model to support real-time wind field updating. At the same time, considering the effect of repairing grid crevices on the system efficiency, this paper presents an efficient method for repairing ocean surface grid crevices based on the characteristics of ocean grid and GPU technology. At last, the feasibility and validity of the method are verified by the comparison experiment. The experimental results show that the proposed method is efficient, stable and fast, and can compensate for the lack of function of the existing methods, so the application range is more extensive.
Dissolution-recrystallization method for high efficiency perovskite solar cells
Energy Technology Data Exchange (ETDEWEB)
Han, Fei; Luo, Junsheng; Wan, Zhongquan; Liu, Xingzhao; Jia, Chunyang, E-mail: cyjia@uestc.edu.cn
2017-06-30
Highlights: • Dissolution-recrystallization method can improve perovskite crystallization. • Dissolution-recrystallization method can improve TiO{sub 2}/perovskite interface. • The optimal perovskite solar cell obtains the champion PCE of 16.76%. • The optimal devices are of high reproducibility. - Abstract: In this work, a dissolution-recrystallization method (DRM) with chlorobenzene and dimethylsulfoxide treating the perovskite films during the spin-coating process is reported. This is the first time that DRM is used to control perovskite crystallization and improve the device performance. Furthermore, the DRM is good for reducing defects and grain boundaries, improving perovskite crystallization and even improving TiO{sub 2}/perovskite interface. By optimizing, the DRM2-treated perovskite solar cell (PSC) obtains the best photoelectric conversion efficiency (PCE) of 16.76% under AM 1.5 G illumination (100 mW cm{sup −2}) with enhanced J{sub sc} and V{sub oc} compared to CB-treated PSC.
Optimization of the southern electrophoretic transfer method
International Nuclear Information System (INIS)
Allison, M.A.; Fujimura, R.K.
1987-01-01
The technique of separating DNA fragments using agarose gel electrophoresis is essential in the analysis of nucleic acids. Further, after the method of transferring specific DNA fragments from those agarose gels to cellulose nitrate membranes was developed in 1975, a method was developed to transfer DNA, RNA, protein and ribonucleoprotein particles from various gels onto diazobenzyloxymethyl (DBM) paper using electrophoresis as well. This paper describes the optimum conditions for quantitative electrophoretic transfer of DNA onto nylon membranes. This method exemplifies the ability to hybridize the membrane more than once with specific RNA probes by providing sufficient retention of the DNA. Furthermore, the intrinsic properties of the nylon membrane allow for an increase in the efficiency and resolution of transfer while using somewhat harsh alkaline conditions. The use of alkaline conditions is of critical importance since we can now denature the DNA during transfer and thus only a short pre-treatment in acid is required for depurination. 9 refs., 7 figs
Generalized field-splitting algorithms for optimal IMRT delivery efficiency
Energy Technology Data Exchange (ETDEWEB)
Kamath, Srijit [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Sahni, Sartaj [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Li, Jonathan [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Ranka, Sanjay [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Palta, Jatinder [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States)
2007-09-21
Intensity-modulated radiation therapy (IMRT) uses radiation beams of varying intensities to deliver varying doses of radiation to different areas of the tissue. The use of IMRT has allowed the delivery of higher doses of radiation to the tumor and lower doses to the surrounding healthy tissue. It is not uncommon for head and neck tumors, for example, to have large treatment widths that are not deliverable using a single field. In such cases, the intensity matrix generated by the optimizer needs to be split into two or three matrices, each of which may be delivered using a single field. Existing field-splitting algorithms used the pre-specified arbitrary split line or region where the intensity matrix is split along a column, i.e., all rows of the matrix are split along the same column (with or without the overlapping of split fields, i.e., feathering). If three fields result, then the two splits are along the same two columns for all rows. In this paper we study the problem of splitting a large field into two or three subfields with the field width as the only constraint, allowing for an arbitrary overlap of the split fields, so that the total MU efficiency of delivering the split fields is maximized. Proof of optimality is provided for the proposed algorithm. An average decrease of 18.8% is found in the total MUs when compared to the split generated by a commercial treatment planning system and that of 10% is found in the total MUs when compared to the split generated by our previously published algorithm. For more information on this article, see medicalphysicsweb.org.
Efficient computation method of Jacobian matrix
International Nuclear Information System (INIS)
Sasaki, Shinobu
1995-05-01
As well known, the elements of the Jacobian matrix are complex trigonometric functions of the joint angles, resulting in a matrix of staggering complexity when we write it all out in one place. This article addresses that difficulties to this subject are overcome by using velocity representation. The main point is that its recursive algorithm and computer algebra technologies allow us to derive analytical formulation with no human intervention. Particularly, it is to be noted that as compared to previous results the elements are extremely simplified throughout the effective use of frame transformations. Furthermore, in case of a spherical wrist, it is shown that the present approach is computationally most efficient. Due to such advantages, the proposed method is useful in studying kinematically peculiar properties such as singularity problems. (author)
A Fast Optimization Method for General Binary Code Learning.
Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng
2016-09-22
Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.
DEFF Research Database (Denmark)
Justesen, Kristian Kjær; Andreasen, Søren Juhl
2015-01-01
In this work a method for choosing the optimal reformer temperature for a reformed methanol fuel cell system is presented based on a case study of a H3 350 module produced by Serenergy A/S. The method is based on ANFIS models of the dependence of the reformer output gas composition on the reformer...... temperature and fuel flow, and the dependence of the fuel cell voltage on the fuel cell temperature, current and anode supply gas CO content. These models are combined to give a matrix of system efficiencies at different fuel cell currents and reformer temperatures. This matrix is then used to find...... the reformer temperature which gives the highest efficiency for each fuel cell current. The average of this optimal efficiency curve is 32.11% and the average efficiency achieved using the standard constant temperature is 30.64% an increase of 1.47 percentage points. The gain in efficiency is 4 percentage...
Efficiency Optimization Control of IPM Synchronous Motor Drives with Online Parameter Estimation
Directory of Open Access Journals (Sweden)
Sadegh Vaez-Zadeh
2011-04-01
Full Text Available This paper describes an efficiency optimization control method for high performance interior permanent magnet synchronous motor drives with online estimation of motor parameters. The control system is based on an input-output feedback linearization method which provides high performance control and simultaneously ensures the minimization of the motor losses. The controllable electrical loss can be minimized by the optimal control of the armature current vector. It is shown that parameter variations except at near the nominal conditions have undesirable effect on the controller performance. Therefore, a parameter estimation method based on the second method of Lyapunov is presented which guarantees the stability and convergence of the estimation. The extensive simulation results show the feasibility of the proposed controller and observer and their desirable performances.
On Best Practice Optimization Methods in R
Directory of Open Access Journals (Sweden)
John C. Nash
2014-09-01
Full Text Available R (R Core Team 2014 provides a powerful and flexible system for statistical computations. It has a default-install set of functionality that can be expanded by the use of several thousand add-in packages as well as user-written scripts. While R is itself a programming language, it has proven relatively easy to incorporate programs in other languages, particularly Fortran and C. Success, however, can lead to its own costs: • Users face a confusion of choice when trying to select packages in approaching a problem. • A need to maintain workable examples using early methods may mean some tools offered as a default may be dated. • In an open-source project like R, how to decide what tools offer "best practice" choices, and how to implement such a policy, present a serious challenge. We discuss these issues with reference to the tools in R for nonlinear parameter estimation (NLPE and optimization, though for the present article `optimization` will be limited to function minimization of essentially smooth functions with at most bounds constraints on the parameters. We will abbreviate this class of problems as NLPE. We believe that the concepts proposed are transferable to other classes of problems seen by R users.
Optimization of sequential decisions by least squares Monte Carlo method
DEFF Research Database (Denmark)
Nishijima, Kazuyoshi; Anders, Annett
change adaptation measures, and evacuation of people and assets in the face of an emerging natural hazard event. Focusing on the last example, an efficient solution scheme is proposed by Anders and Nishijima (2011). The proposed solution scheme takes basis in the least squares Monte Carlo method, which...... is proposed by Longstaff and Schwartz (2001) for pricing of American options. The present paper formulates the decision problem in a more general manner and explains how the solution scheme proposed by Anders and Nishijima (2011) is implemented for the optimization of the formulated decision problem...
A Biologically Inspired Energy-Efficient Duty Cycle Design Method for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Jie Zhou
2017-01-01
Full Text Available The recent success of emerging wireless sensor networks technology has encouraged researchers to develop new energy-efficient duty cycle design algorithm in this field. The energy-efficient duty cycle design problem is a typical NP-hard combinatorial optimization problem. In this paper, we investigate an improved elite immune evolutionary algorithm (IEIEA strategy to optimize energy-efficient duty cycle design scheme and monitored area jointly to enhance the network lifetimes. Simulation results show that the network lifetime of the proposed IEIEA method increased compared to the other two methods, which means that the proposed method improves the full coverage constraints.
Optimization design of hydroturbine rotors according to the efficiency-strength criteria
Bannikov, D. V.; Yesipov, D. V.; Cherny, S. G.; Chirkov, D. V.
2010-12-01
The hydroturbine runner designing [1] is optimized by efficient methods for calculation of head loss in entire flow-through part of the turbine and deformation state of the blade. Energy losses are found at modelling of the spatial turbulent flow and engineering semi-empirical formulae. State of deformation is determined from the solution of the linear problem of elasticity for the isolated blade at hydrodynamic pressure with the method of boundary elements. With the use of the proposed system, the problem of the turbine runner design with the capacity of 640 MW providing the preset dependence of efficiency on the turbine work mode (efficiency criterion) is solved. The arising stresses do not exceed the critical value (strength criterion).
Drechsler, Martin
2017-02-01
Auctions have been proposed as alternatives to payments for environmental services when spatial interactions and costs are better known to landowners than to the conservation agency (asymmetric information). Recently, an auction scheme was proposed that delivers optimal conservation in the sense that social welfare is maximized. I examined the social welfare and the budget efficiency delivered by this scheme, where social welfare represents the difference between the monetized ecological benefit and the conservation cost incurred to the landowners and budget efficiency is defined as maximizing the ecological benefit for a given conservation budget. For the analysis, I considered a stylized landscape with land patches that can be used for agriculture or conservation. The ecological benefit was measured by an objective function that increases with increasing number and spatial aggregation of conserved land patches. I compared the social welfare and the budget efficiency of the auction scheme with an agglomeration payment, a policy scheme that considers spatial interactions and that was proposed recently. The auction delivered a higher level of social welfare than the agglomeration payment. However, the agglomeration payment was more efficient budgetarily than the auction, so the comparative performances of the 2 schemes depended on the chosen policy criterion-social welfare or budget efficiency. Both policy criteria are relevant for conservation. Which one should be chosen depends on the problem at hand, for example, whether social preferences should be taken into account in the decision of how much money to invest in conservation or whether the available conservation budget is strictly limited. © 2016 Society for Conservation Biology.
Stochastic Recursive Algorithms for Optimization Simultaneous Perturbation Methods
Bhatnagar, S; Prashanth, L A
2013-01-01
Stochastic Recursive Algorithms for Optimization presents algorithms for constrained and unconstrained optimization and for reinforcement learning. Efficient perturbation approaches form a thread unifying all the algorithms considered. Simultaneous perturbation stochastic approximation and smooth fractional estimators for gradient- and Hessian-based methods are presented. These algorithms: • are easily implemented; • do not require an explicit system model; and • work with real or simulated data. Chapters on their application in service systems, vehicular traffic control and communications networks illustrate this point. The book is self-contained with necessary mathematical results placed in an appendix. The text provides easy-to-use, off-the-shelf algorithms that are given detailed mathematical treatment so the material presented will be of significant interest to practitioners, academic researchers and graduate students alike. The breadth of applications makes the book appropriate for reader from sim...
Optimizing Sampling Efficiency for Biomass Estimation Across NEON Domains
Abercrombie, H. H.; Meier, C. L.; Spencer, J. J.
2013-12-01
Over the course of 30 years, the National Ecological Observatory Network (NEON) will measure plant biomass and productivity across the U.S. to enable an understanding of terrestrial carbon cycle responses to ecosystem change drivers. Over the next several years, prior to operational sampling at a site, NEON will complete construction and characterization phases during which a limited amount of sampling will be done at each site to inform sampling designs, and guide standardization of data collection across all sites. Sampling biomass in 60+ sites distributed among 20 different eco-climatic domains poses major logistical and budgetary challenges. Traditional biomass sampling methods such as clip harvesting and direct measurements of Leaf Area Index (LAI) involve collecting and processing plant samples, and are time and labor intensive. Possible alternatives include using indirect sampling methods for estimating LAI such as digital hemispherical photography (DHP) or using a LI-COR 2200 Plant Canopy Analyzer. These LAI estimations can then be used as a proxy for biomass. The biomass estimates calculated can then inform the clip harvest sampling design during NEON operations, optimizing both sample size and number so that standardized uncertainty limits can be achieved with a minimum amount of sampling effort. In 2011, LAI and clip harvest data were collected from co-located sampling points at the Central Plains Experimental Range located in northern Colorado, a short grass steppe ecosystem that is the NEON Domain 10 core site. LAI was measured with a LI-COR 2200 Plant Canopy Analyzer. The layout of the sampling design included four, 300 meter transects, with clip harvests plots spaced every 50m, and LAI sub-transects spaced every 10m. LAI was measured at four points along 6m sub-transects running perpendicular to the 300m transect. Clip harvest plots were co-located 4m from corresponding LAI transects, and had dimensions of 0.1m by 2m. We conducted regression analyses
METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and
Asymptotic optimality and efficient computation of the leave-subject-out cross-validation
Xu, Ganggang
2012-12-01
Although the leave-subject-out cross-validation (CV) has been widely used in practice for tuning parameter selection for various nonparametric and semiparametric models of longitudinal data, its theoretical property is unknown and solving the associated optimization problem is computationally expensive, especially when there are multiple tuning parameters. In this paper, by focusing on the penalized spline method, we show that the leave-subject-out CV is optimal in the sense that it is asymptotically equivalent to the empirical squared error loss function minimization. An efficient Newton-type algorithm is developed to compute the penalty parameters that optimize the CV criterion. Simulated and real data are used to demonstrate the effectiveness of the leave-subject-out CV in selecting both the penalty parameters and the working correlation matrix. © 2012 Institute of Mathematical Statistics.
Asymptotic optimality and efficient computation of the leave-subject-out cross-validation
Xu, Ganggang; Huang, Jianhua Z.
2012-01-01
Although the leave-subject-out cross-validation (CV) has been widely used in practice for tuning parameter selection for various nonparametric and semiparametric models of longitudinal data, its theoretical property is unknown and solving the associated optimization problem is computationally expensive, especially when there are multiple tuning parameters. In this paper, by focusing on the penalized spline method, we show that the leave-subject-out CV is optimal in the sense that it is asymptotically equivalent to the empirical squared error loss function minimization. An efficient Newton-type algorithm is developed to compute the penalty parameters that optimize the CV criterion. Simulated and real data are used to demonstrate the effectiveness of the leave-subject-out CV in selecting both the penalty parameters and the working correlation matrix. © 2012 Institute of Mathematical Statistics.
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...
Numerical methods and optimization a consumer guide
Walter, Éric
2014-01-01
Initial training in pure and applied sciences tends to present problem-solving as the process of elaborating explicit closed-form solutions from basic principles, and then using these solutions in numerical applications. This approach is only applicable to very limited classes of problems that are simple enough for such closed-form solutions to exist. Unfortunately, most real-life problems are too complex to be amenable to this type of treatment. Numerical Methods and Optimization – A Consumer Guide presents methods for dealing with them. Shifting the paradigm from formal calculus to numerical computation, the text makes it possible for the reader to · discover how to escape the dictatorship of those particular cases that are simple enough to receive a closed-form solution, and thus gain the ability to solve complex, real-life problems; · understand the principles behind recognized algorithms used in state-of-the-art numerical software; · learn the advantag...
Shi, Shengchao; Li, Guangxia; An, Kang; Gao, Bin; Zheng, Gan
2017-09-04
This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach's method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint.
Optimizing Eco-Efficiency Across the Procurement Portfolio.
Pelton, Rylie E O; Li, Mo; Smith, Timothy M; Lyon, Thomas P
2016-06-07
Manufacturing organizations' environmental impacts are often attributable to processes in the firm's upstream supply chain. Environmentally preferable procurement (EPP) and the establishment of environmental purchasing criteria can potentially reduce these indirect impacts. Life-cycle assessment (LCA) can help identify the purchasing criteria that are most effective in reducing environmental impacts. However, the high costs of LCA and the problems associated with the comparability of results have limited efforts to integrate procurement performance with quantitative organizational environmental performance targets. Moreover, environmental purchasing criteria, when implemented, are often established on a product-by-product basis without consideration of other products in the procurement portfolio. We develop an approach that utilizes streamlined LCA methods, together with linear programming, to determine optimal portfolios of product impact-reduction opportunities under budget constraints. The approach is illustrated through a simulated breakfast cereal manufacturing firm procuring grain, containerboard boxes, plastic packaging, electricity, and industrial cleaning solutions. Results suggest that extending EPP decisions and resources to the portfolio level, recently made feasible through the methods illustrated herein, can provide substantially greater CO2e and water-depletion reductions per dollar spend than a product-by-product approach, creating opportunities for procurement organizations to participate in firm-wide environmental impact reduction targets.
Directory of Open Access Journals (Sweden)
Junhao Luo
2018-05-01
Full Text Available As a key factor in the design of a voltage-adjustable LLC resonant converter, frequency regulation range is very important to the optimization of magnetic components and efficiency improvement. This paper presents a novel optimal design method for LLC resonant converters, which can narrow the frequency variation range and ensure high efficiency under the premise of a required gain achievement. A simplified gain model was utilized to simplify the calculation and the expected efficiency was initially set as 96.5%. The restricted area of parameter optimization design can be obtained by taking the intersection of the gain requirement, the efficiency requirement, and three restrictions of ZVS (Zero Voltage Switch. The proposed method was verified by simulation and experiments of a 150 W prototype. The results show that the proposed method can achieve ZVS from full-load to no-load conditions and can reach 1.6 times the normalized voltage gain in the frequency variation range of 18 kHz with a peak efficiency of up to 96.3%. Moreover, the expected efficiency is adjustable, which means a converter with a higher efficiency can be designed. The proposed method can also be used for the design of large-power LLC resonant converters to obtain a wide output voltage range and higher efficiency.
Parallel efficient rate control methods for JPEG 2000
Martínez-del-Amor, Miguel Á.; Bruns, Volker; Sparenberg, Heiko
2017-09-01
Since the introduction of JPEG 2000, several rate control methods have been proposed. Among them, post-compression rate-distortion optimization (PCRD-Opt) is the most widely used, and the one recommended by the standard. The approach followed by this method is to first compress the entire image split in code blocks, and subsequently, optimally truncate the set of generated bit streams according to the maximum target bit rate constraint. The literature proposes various strategies on how to estimate ahead of time where a block will get truncated in order to stop the execution prematurely and save time. However, none of them have been defined bearing in mind a parallel implementation. Today, multi-core and many-core architectures are becoming popular for JPEG 2000 codecs implementations. Therefore, in this paper, we analyze how some techniques for efficient rate control can be deployed in GPUs. In order to do that, the design of our GPU-based codec is extended, allowing stopping the process at a given point. This extension also harnesses a higher level of parallelism on the GPU, leading to up to 40% of speedup with 4K test material on a Titan X. In a second step, three selected rate control methods are adapted and implemented in our parallel encoder. A comparison is then carried out, and used to select the best candidate to be deployed in a GPU encoder, which gave an extra 40% of speedup in those situations where it was really employed.
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
Efficient 3D porous microstructure reconstruction via Gaussian random field and hybrid optimization.
Jiang, Z; Chen, W; Burkhart, C
2013-11-01
Obtaining an accurate three-dimensional (3D) structure of a porous microstructure is important for assessing the material properties based on finite element analysis. Whereas directly obtaining 3D images of the microstructure is impractical under many circumstances, two sets of methods have been developed in literature to generate (reconstruct) 3D microstructure from its 2D images: one characterizes the microstructure based on certain statistical descriptors, typically two-point correlation function and cluster correlation function, and then performs an optimization process to build a 3D structure that matches those statistical descriptors; the other method models the microstructure using stochastic models like a Gaussian random field and generates a 3D structure directly from the function. The former obtains a relatively accurate 3D microstructure, but computationally the optimization process can be very intensive, especially for problems with large image size; the latter generates a 3D microstructure quickly but sacrifices the accuracy due to issues in numerical implementations. A hybrid optimization approach of modelling the 3D porous microstructure of random isotropic two-phase materials is proposed in this paper, which combines the two sets of methods and hence maintains the accuracy of the correlation-based method with improved efficiency. The proposed technique is verified for 3D reconstructions based on silica polymer composite images with different volume fractions. A comparison of the reconstructed microstructures and the optimization histories for both the original correlation-based method and our hybrid approach demonstrates the improved efficiency of the approach. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.
A generic method to optimize instructions for the control of evacuations
Huibregtse, O.L.; Hoogendoorn, S.P.; Pel, A.J.; Bliemer, M.C.J.
2010-01-01
A method is described to develop a set of optimal instructions to evacuate by car the population of a region threatened by a hazard. By giving these instructions to the evacuees, traffic conditions and therefore the evacuation efficiency can be optimized. The instructions, containing a departure
Toward efficient optimization of wind farm layouts: Utilizing exact gradient information
International Nuclear Information System (INIS)
Guirguis, David; Romero, David A.; Amon, Cristina H.
2016-01-01
Highlights: • A mathematical programming approach is proposed to solve the WFLO problem. • Differentiable mathematical models are developed to handle land-use constraints. • Test cases with significant land-use constraints are solved efficiently. • The proposed approach outperforms genetic algorithm. - Abstract: The Wind Farm Layout Optimization (WFLO) problem has attracted a lot of attention from researchers and industry practitioners, as it has been proven that better placement of wind turbines can increase the overall efficiency and the total revenue of a wind farm. Although the engineering wake models are commonly used for layout optimization, the literature seems to have settled on using metaheuristics and stochastic optimization methods. In the present study, we show the effectiveness of non-linear mathematical programming in solving continuous-variable WFLO problems by utilizing exact gradient information of the problem’s objective and constraints. Moreover, mathematical models for handling land-use constraints are developed to solve highly constrained practical problems. For demonstration purposes, the results were compared with those obtained by a genetic algorithm, using a set of test cases that have been frequently used in the WFLO literature. Additional test cases with higher dimensionality, significant land-availability constraints and higher wind farm turbine densities (i.e., turbines per square kilometer) are devised and solved to show the merits of the proposed approach. Our results show the superiority of mathematical programing in solving this problem, as evidenced by the resulting wind farm efficiency and the computational cost required to obtain the solutions.
International Nuclear Information System (INIS)
Pezzini, Paola; Gomis-Bellmunt, Oriol; Frau-Valenti, Joan; Sudria-Andreu, Antoni
2010-01-01
In transmission and distribution systems, the high number of installed transformers, a loss source in networks, suggests a good potential for energy savings. This paper presents how the Spanish Distribution regulation policy, Royal Decree 222/2008, affects the overall energy efficiency in distribution transformers. The objective of a utility is the maximization of the benefit, and in case of failures, to install a chosen transformer in order to maximize the profit. Here, a novel method to optimize energy efficiency, considering the constraints set by the Spanish Distribution regulation policy, is presented; its aim is to achieve the objectives of the utility when installing new transformers. The overall energy efficiency increase is a clear result that can help in meeting the requirements of European environmental plans, such as the '20-20-20' action plan.
Energy Technology Data Exchange (ETDEWEB)
Pezzini, Paola [Centre d' Innovacio en Convertidors Estatics i Accionaments (CITCEA-UPC), E.T.S. Enginyeria Industrial Barcelona, Universitat Politecnica Catalunya, Diagonal, 647, Pl. 2, 08028 Barcelona (Spain); Gomis-Bellmunt, Oriol; Sudria-Andreu, Antoni [Centre d' Innovacio en Convertidors Estatics i Accionaments (CITCEA-UPC), E.T.S. Enginyeria Industrial Barcelona, Universitat Politecnica Catalunya, Diagonal, 647, Pl. 2, 08028 Barcelona (Spain); IREC Catalonia Institute for Energy Research, Josep Pla, B2, Pl. Baixa, 08019 Barcelona (Spain); Frau-Valenti, Joan [ENDESA, Carrer Joan Maragall, 16 07006 Palma (Spain)
2010-12-15
In transmission and distribution systems, the high number of installed transformers, a loss source in networks, suggests a good potential for energy savings. This paper presents how the Spanish Distribution regulation policy, Royal Decree 222/2008, affects the overall energy efficiency in distribution transformers. The objective of a utility is the maximization of the benefit, and in case of failures, to install a chosen transformer in order to maximize the profit. Here, a novel method to optimize energy efficiency, considering the constraints set by the Spanish Distribution regulation policy, is presented; its aim is to achieve the objectives of the utility when installing new transformers. The overall energy efficiency increase is a clear result that can help in meeting the requirements of European environmental plans, such as the '20-20-20' action plan. (author)
Improving efficiency (optimization) of CIGS thin film solar cell using ...
African Journals Online (AJOL)
Jsc ,Voc , FF and Quantum efficiency (QE) decrease due to absorption of electrons of electrons to the surface of back connection and their participation in recomposition. Efficiency increases from 20.3399% to 21.3721% by increasing impurity density of absorbent layer and efficiency increases to 28.9266% and the quantum ...
Domestic energy management methodology for optimizing efficiency in Smart Grids
Molderink, Albert; Bakker, Vincent; Bosman, M.G.C.; Hurink, Johann L.; Smit, Gerardus Johannes Maria
2009-01-01
Increasing energy prices and the greenhouse effect lead to more awareness of energy efficiency of electricity supply. During the last years, a lot of domestic technologies have been developed to improve this efficiency. These technologies on their own already improve the efficiency, but more can be
Models and Methods for Free Material Optimization
DEFF Research Database (Denmark)
Weldeyesus, Alemseged Gebrehiwot
Free Material Optimization (FMO) is a powerful approach for structural optimization in which the design parametrization allows the entire elastic stiffness tensor to vary freely at each point of the design domain. The only requirement imposed on the stiffness tensor lies on its mild necessary...
Travel Efficiency Assessment Method: Three Case Studies
This slide presentation summarizes three case studies EPA conducted in partnership with Boston, Kansas City, and Tucson, to assess the potential benefits of employing travel efficiency strategies in these areas.
Adjoint Optimization of a Wing Using the CSRT Method
Straathof, M.H.; Van Tooren, M.J.L.
2011-01-01
This paper will demonstrate the potential of the Class-Shape-Refinement-Transformation (CSRT) method for aerodynamically optimizing three-dimensional surfaces. The CSRT method was coupled to an in-house Euler solver and this combination was used in an optimization framework to optimize the ONERA M6
Auditory-like filterbank: An optimal speech processor for efficient ...
Indian Academy of Sciences (India)
The transmitter and the receiver in a communication system have to be designed optimally with respect to one another to ensure reliable and efﬁcient communication. Following this principle, we derive an optimal ﬁlterbank for processing speech signal in the listener's auditory system (receiver), so that maximum information ...
A New Optimization Method for Centrifugal Compressors Based on 1D Calculations and Analyses
Directory of Open Access Journals (Sweden)
Pei-Yuan Li
2015-05-01
Full Text Available This paper presents an optimization design method for centrifugal compressors based on one-dimensional calculations and analyses. It consists of two parts: (1 centrifugal compressor geometry optimization based on one-dimensional calculations and (2 matching optimization of the vaned diffuser with an impeller based on the required throat area. A low pressure stage centrifugal compressor in a MW level gas turbine is optimized by this method. One-dimensional calculation results show that D3/D2 is too large in the original design, resulting in the low efficiency of the entire stage. Based on the one-dimensional optimization results, the geometry of the diffuser has been redesigned. The outlet diameter of the vaneless diffuser has been reduced, and the original single stage diffuser has been replaced by a tandem vaned diffuser. After optimization, the entire stage pressure ratio is increased by approximately 4%, and the efficiency is increased by approximately 2%.
Sidler, Dominik; Cristòfol-Clough, Michael; Riniker, Sereina
2017-06-13
Replica-exchange enveloping distribution sampling (RE-EDS) allows the efficient estimation of free-energy differences between multiple end-states from a single molecular dynamics (MD) simulation. In EDS, a reference state is sampled, which can be tuned by two types of parameters, i.e., smoothness parameters(s) and energy offsets, such that all end-states are sufficiently sampled. However, the choice of these parameters is not trivial. Replica exchange (RE) or parallel tempering is a widely applied technique to enhance sampling. By combining EDS with the RE technique, the parameter choice problem could be simplified and the challenge shifted toward an optimal distribution of the replicas in the smoothness-parameter space. The choice of a certain replica distribution can alter the sampling efficiency significantly. In this work, global round-trip time optimization (GRTO) algorithms are tested for the use in RE-EDS simulations. In addition, a local round-trip time optimization (LRTO) algorithm is proposed for systems with slowly adapting environments, where a reliable estimate for the round-trip time is challenging to obtain. The optimization algorithms were applied to RE-EDS simulations of a system of nine small-molecule inhibitors of phenylethanolamine N-methyltransferase (PNMT). The energy offsets were determined using our recently proposed parallel energy-offset (PEOE) estimation scheme. While the multistate GRTO algorithm yielded the best replica distribution for the ligands in water, the multistate LRTO algorithm was found to be the method of choice for the ligands in complex with PNMT. With this, the 36 alchemical free-energy differences between the nine ligands were calculated successfully from a single RE-EDS simulation 10 ns in length. Thus, RE-EDS presents an efficient method for the estimation of relative binding free energies.
International Nuclear Information System (INIS)
Salari, Ehsan; Craft, David; Wala, Jeremiah
2012-01-01
To formulate and solve the fluence-map merging procedure of the recently-published VMAT treatment-plan optimization method, called vmerge, as a bi-criteria optimization problem. Using an exact merging method rather than the previously-used heuristic, we are able to better characterize the trade-off between the delivery efficiency and dose quality. vmerge begins with a solution of the fluence-map optimization problem with 180 equi-spaced beams that yields the ‘ideal’ dose distribution. Neighboring fluence maps are then successively merged, meaning that they are added together and delivered as a single map. The merging process improves the delivery efficiency at the expense of deviating from the initial high-quality dose distribution. We replace the original merging heuristic by considering the merging problem as a discrete bi-criteria optimization problem with the objectives of maximizing the treatment efficiency and minimizing the deviation from the ideal dose. We formulate this using a network-flow model that represents the merging problem. Since the problem is discrete and thus non-convex, we employ a customized box algorithm to characterize the Pareto frontier. The Pareto frontier is then used as a benchmark to evaluate the performance of the standard vmerge algorithm as well as two other similar heuristics. We test the exact and heuristic merging approaches on a pancreas and a prostate cancer case. For both cases, the shape of the Pareto frontier suggests that starting from a high-quality plan, we can obtain efficient VMAT plans through merging neighboring fluence maps without substantially deviating from the initial dose distribution. The trade-off curves obtained by the various heuristics are contrasted and shown to all be equally capable of initial plan simplifications, but to deviate in quality for more drastic efficiency improvements. This work presents a network optimization approach to the merging problem. Contrasting the trade-off curves of the
Salari, Ehsan; Wala, Jeremiah; Craft, David
2012-09-07
To formulate and solve the fluence-map merging procedure of the recently-published VMAT treatment-plan optimization method, called VMERGE, as a bi-criteria optimization problem. Using an exact merging method rather than the previously-used heuristic, we are able to better characterize the trade-off between the delivery efficiency and dose quality. VMERGE begins with a solution of the fluence-map optimization problem with 180 equi-spaced beams that yields the 'ideal' dose distribution. Neighboring fluence maps are then successively merged, meaning that they are added together and delivered as a single map. The merging process improves the delivery efficiency at the expense of deviating from the initial high-quality dose distribution. We replace the original merging heuristic by considering the merging problem as a discrete bi-criteria optimization problem with the objectives of maximizing the treatment efficiency and minimizing the deviation from the ideal dose. We formulate this using a network-flow model that represents the merging problem. Since the problem is discrete and thus non-convex, we employ a customized box algorithm to characterize the Pareto frontier. The Pareto frontier is then used as a benchmark to evaluate the performance of the standard VMERGE algorithm as well as two other similar heuristics. We test the exact and heuristic merging approaches on a pancreas and a prostate cancer case. For both cases, the shape of the Pareto frontier suggests that starting from a high-quality plan, we can obtain efficient VMAT plans through merging neighboring fluence maps without substantially deviating from the initial dose distribution. The trade-off curves obtained by the various heuristics are contrasted and shown to all be equally capable of initial plan simplifications, but to deviate in quality for more drastic efficiency improvements. This work presents a network optimization approach to the merging problem. Contrasting the trade-off curves of the merging
Optimizing cost-efficiency in mean exposure assessment--cost functions reconsidered.
Mathiassen, Svend Erik; Bolin, Kristian
2011-05-21
Reliable exposure data is a vital concern in medical epidemiology and intervention studies. The present study addresses the needs of the medical researcher to spend monetary resources devoted to exposure assessment with an optimal cost-efficiency, i.e. obtain the best possible statistical performance at a specified budget. A few previous studies have suggested mathematical optimization procedures based on very simple cost models; this study extends the methodology to cover even non-linear cost scenarios. Statistical performance, i.e. efficiency, was assessed in terms of the precision of an exposure mean value, as determined in a hierarchical, nested measurement model with three stages. Total costs were assessed using a corresponding three-stage cost model, allowing costs at each stage to vary non-linearly with the number of measurements according to a power function. Using these models, procedures for identifying the optimally cost-efficient allocation of measurements under a constrained budget were developed, and applied on 225 scenarios combining different sizes of unit costs, cost function exponents, and exposure variance components. Explicit mathematical rules for identifying optimal allocation could be developed when cost functions were linear, while non-linear cost functions implied that parts of or the entire optimization procedure had to be carried out using numerical methods.For many of the 225 scenarios, the optimal strategy consisted in measuring on only one occasion from each of as many subjects as allowed by the budget. Significant deviations from this principle occurred if costs for recruiting subjects were large compared to costs for setting up measurement occasions, and, at the same time, the between-subjects to within-subject variance ratio was small. In these cases, non-linearities had a profound influence on the optimal allocation and on the eventual size of the exposure data set. The analysis procedures developed in the present study can be used
Geometric Design of Scalable Forward Scatterers for Optimally Efficient Solar Transformers.
Kim, Hye-Na; Vahidinia, Sanaz; Holt, Amanda L; Sweeney, Alison M; Yang, Shu
2017-11-01
It will be ideal to deliver equal, optimally efficient "doses" of sunlight to all cells in a photobioreactor system, while simultaneously utilizing the entire solar resource. Backed by the numerical scattering simulation and optimization, here, the design, synthesis, and characterization of the synthetic iridocytes that recapitulated the salient forward-scattering behavior of the Tridacnid clam system are reported, which presents the first geometric solution to allow narrow, precise forward redistribution of flux, utilizing the solar resource at the maximum quantum efficiency possible in living cells. The synthetic iridocytes are composed of silica nanoparticles in microspheres embedded in gelatin, both are low refractive index materials and inexpensive. They show wavelength selectivity, have little loss (the back-scattering intensity is reduced to less than ≈0.01% of the forward-scattered intensity), and narrow forward scattering cone similar to giant clams. Moreover, by comparing experiments and theoretical calculation, it is confirmed that the nonuniformity of the scatter sizes is a "feature not a bug" of the design, allowing for efficient, forward redistribution of solar flux in a micrometer-scaled paradigm. This method is environmentally benign, inexpensive, and scalable to produce optical components that will find uses in efficiency-limited solar conversion technologies, heat sinks, and biofuel production. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Lin, Wushao; Bi, Lei; Liu, Dong; Zhang, Kejun
2017-08-21
The extinction efficiencies of atmospheric particles are essential to determining radiation attenuation and thus are fundamentally related to atmospheric radiative transfer. The extinction efficiencies can also be used to retrieve particle sizes or refractive indices through particle characterization techniques. This study first uses the Debye series to improve the accuracy of high-frequency extinction formulae for spheroids in the context of Complex angular momentum theory by determining an optimal number of edge-effect terms. We show that the optimal edge-effect terms can be accurately obtained by comparing the results from the approximate formula with their counterparts computed from the invariant imbedding Debye series and T-matrix methods. An invariant imbedding T-matrix method is employed for particles with strong absorption, in which case the extinction efficiency is equivalent to two plus the edge-effect efficiency. For weakly absorptive or non-absorptive particles, the T-matrix results contain the interference between the diffraction and higher-order transmitted rays. Therefore, the Debye series was used to compute the edge-effect efficiency by separating the interference from the transmission on the extinction efficiency. We found that the optimal number strongly depends on the refractive index and is relatively insensitive to the particle geometry and size parameter. By building a table of optimal numbers of edge-effect terms, we developed an efficient and accurate extinction simulator that has been fully tested for randomly oriented spheroids with various aspect ratios and a wide range of refractive indices.
Extremely Efficient Design of Organic Thin Film Solar Cells via Learning-Based Optimization
Directory of Open Access Journals (Sweden)
Mine Kaya
2017-11-01
Full Text Available Design of efficient thin film photovoltaic (PV cells require optical power absorption to be computed inside a nano-scale structure of photovoltaics, dielectric and plasmonic materials. Calculating power absorption requires Maxwell’s electromagnetic equations which are solved using numerical methods, such as finite difference time domain (FDTD. The computational cost of thin film PV cell design and optimization is therefore cumbersome, due to successive FDTD simulations. This cost can be reduced using a surrogate-based optimization procedure. In this study, we deploy neural networks (NNs to model optical absorption in organic PV structures. We use the corresponding surrogate-based optimization procedure to maximize light trapping inside thin film organic cells infused with metallic particles. Metallic particles are known to induce plasmonic effects at the metal–semiconductor interface, thus increasing absorption. However, a rigorous design procedure is required to achieve the best performance within known design guidelines. As a result of using NNs to model thin film solar absorption, the required time to complete optimization is decreased by more than five times. The obtained NN model is found to be very reliable. The optimization procedure results in absorption enhancement greater than 200%. Furthermore, we demonstrate that once a reliable surrogate model such as the developed NN is available, it can be used for alternative analyses on the proposed design, such as uncertainty analysis (e.g., fabrication error.
Method of optimization onboard communication network
Platoshin, G. A.; Selvesuk, N. I.; Semenov, M. E.; Novikov, V. M.
2018-02-01
In this article the optimization levels of onboard communication network (OCN) are proposed. We defined the basic parameters, which are necessary for the evaluation and comparison of modern OCN, we identified also a set of initial data for possible modeling of the OCN. We also proposed a mathematical technique for implementing the OCN optimization procedure. This technique is based on the principles and ideas of binary programming. It is shown that the binary programming technique allows to obtain an inherently optimal solution for the avionics tasks. An example of the proposed approach implementation to the problem of devices assignment in OCN is considered.
Simplified method for calculating SNCR system efficiency
Directory of Open Access Journals (Sweden)
Pronobis Marek
2017-01-01
Full Text Available SNCR (Selective Non-Catalytic Reduction technology is aimed at reducing NOx emissions. SNCR efficiency is appropriately high only for the reaction temperature range called ‘the SNCR temperature window’. It is a narrow temperature range defined in various ways in the literature, which makes it difficult to evaluate the DeNOx system’s efficiency. Therefore, this study attempts to approximate the relationship between SNCR system efficiency and the flue gas temperature. The approximation was performed on the basis of literature data and verified using data from an experiment. Measurements were performed in a Polish boiler with a maximum continuous rating of 230 t/h. The verified, evaluated function could be used to forecast efficiency of SNCR systems in existing units that use urea or ammonia as a reagent. The approximation results are polynomial functions that depend on flue gas temperature, which fit the literature data with the coefficient of determination R2 = 0.83-0.86. Therefore, these equations could be used by the designer or operator of the boiler for preliminary determination of current SNCR system efficiency.
Efficient use of iterative solvers in nested topology optimization
DEFF Research Database (Denmark)
Amir, Oded; Stolpe, Mathias; Sigmund, Ole
2009-01-01
In the nested approach to structural optimization, most of the computational effort is invested in the solution of the finite element analysis equations. In this study, it is suggested to reduce this computational cost by using an approximation to the solution of the nested problem, generated...... measures. The approximation is shown to be sufficiently accurate for the practical purpose of optimization even though the nested equation system is not solved accurately. The approach is tested on several medium-scale topology optimization problems, including three dimensional minimum compliance problems...
Efficient use of iterative solvers in nested topology optimization
DEFF Research Database (Denmark)
Amir, Oded; Stolpe, Mathias; Sigmund, Ole
2010-01-01
In the nested approach to structural optimization, most of the computational effort is invested in the solution of the analysis equations. In this study, it is suggested to reduce this computational cost by using an approximation to the solution of the analysis problem, generated by a Krylov....... The approximation is computationally shown to be sufficiently accurate for the purpose of optimization though the nested equation system is not necessarily solved accurately. The approach is tested on several large-scale topology optimization problems, including minimum compliance problems and compliant mechanism...
A simple method to optimize HMC performance
Bussone, Andrea; Drach, Vincent; Hansen, Martin; Hietanen, Ari; Rantaharju, Jarno; Pica, Claudio
2016-01-01
We present a practical strategy to optimize a set of Hybrid Monte Carlo parameters in simulations of QCD and QCD-like theories. We specialize to the case of mass-preconditioning, with multiple time-step Omelyan integrators. Starting from properties of the shadow Hamiltonian we show how the optimal setup for the integrator can be chosen once the forces and their variances are measured, assuming that those only depend on the mass-preconditioning parameter.
ProxImaL: efficient image optimization using proximal algorithms
Heide, Felix; Diamond, Steven; Nieß ner, Matthias; Ragan-Kelley, Jonathan; Heidrich, Wolfgang; Wetzstein, Gordon
2016-01-01
domain-specific language and compiler for image optimization problems that makes it easy to experiment with different problem formulations and algorithm choices. The language uses proximal operators as the fundamental building blocks of a variety
An efficient method for model refinement in diffuse optical tomography
Zirak, A. R.; Khademi, M.
2007-11-01
Diffuse optical tomography (DOT) is a non-linear, ill-posed, boundary value and optimization problem which necessitates regularization. Also, Bayesian methods are suitable owing to measurements data are sparse and correlated. In such problems which are solved with iterative methods, for stabilization and better convergence, the solution space must be small. These constraints subject to extensive and overdetermined system of equations which model retrieving criteria specially total least squares (TLS) must to refine model error. Using TLS is limited to linear systems which is not achievable when applying traditional Bayesian methods. This paper presents an efficient method for model refinement using regularized total least squares (RTLS) for treating on linearized DOT problem, having maximum a posteriori (MAP) estimator and Tikhonov regulator. This is done with combination Bayesian and regularization tools as preconditioner matrices, applying them to equations and then using RTLS to the resulting linear equations. The preconditioning matrixes are guided by patient specific information as well as a priori knowledge gained from the training set. Simulation results illustrate that proposed method improves the image reconstruction performance and localize the abnormally well.
Spectral Analysis of Large Finite Element Problems by Optimization Methods
Directory of Open Access Journals (Sweden)
Luca Bergamaschi
1994-01-01
Full Text Available Recently an efficient method for the solution of the partial symmetric eigenproblem (DACG, deflated-accelerated conjugate gradient was developed, based on the conjugate gradient (CG minimization of successive Rayleigh quotients over deflated subspaces of decreasing size. In this article four different choices of the coefficient βk required at each DACG iteration for the computation of the new search direction Pk are discussed. The “optimal” choice is the one that yields the same asymptotic convergence rate as the CG scheme applied to the solution of linear systems. Numerical results point out that the optimal βk leads to a very cost effective algorithm in terms of CPU time in all the sample problems presented. Various preconditioners are also analyzed. It is found that DACG using the optimal βk and (LLT−1 as a preconditioner, L being the incomplete Cholesky factor of A, proves a very promising method for the partial eigensolution. It appears to be superior to the Lanczos method in the evaluation of the 40 leftmost eigenpairs of five finite element problems, and particularly for the largest problem, with size equal to 4560, for which the speed gain turns out to fall between 2.5 and 6.0, depending on the eigenpair level.
International Nuclear Information System (INIS)
Hayashi, Hiroaki; Nishihara, Sadamitsu; Taniuchi, Shou; Kamiya, Naotaka
2012-01-01
A visual image of the scattered X-ray distributions gives us useful information for beginners to study radiation physics. A pin-hole camera for X-rays can be made by use of simple materials as well as a two-dimensional X-ray detector (imaging plate: IP). In contrast with a pin-hole camera for the visible radiations, a pin-hole camera for X-rays uses a collimator, having a sufficient thickness to reduce X-rays. This design causes the following problem: in the case in which the X-rays are incident to the collimator from the diagonal direction, the some X-rays are absorbed by the wall of the collimator. Namely, the images in the surrounding part of the IP are underrepresented. The aim of this study is to suggest a correction method of the underrepresentation. We used a pin-hole camera (320 mm(long)×270 mm(wide)×300 mm(depth)) by means of the clinically applied IP (10×12 inch). In order to determine proper conditions for a size of collimators (pin-hole), experiments using medical X-ray equipments were carried out. The efficiencies and resolutions were experimentally determined for the collimator sizes of 2 to 8 mm φ . Then, images of scattered X-ray distributions were measured by the irradiation of a head phantom, and considerations were taken for a practical use of the pin-hole camera. Moreover, an exponential absorption of X-rays in the phantom was visualized by our camera in order to indicate a potential of quantitative analysis based on the image of scattered X-ray distributions. (author)
Three Essays on Robust Optimization of Efficient Portfolios
Liu, Hao
2013-01-01
The mean-variance approach was first proposed by Markowitz (1952), and laid the foundation of the modern portfolio theory. Despite its theoretical appeal, the practical implementation of optimized portfolios is strongly restricted by the fact that the two inputs, the means and the covariance matrix of asset returns, are unknown and have to be estimated by available historical information. Due to the estimation risk inherited from inputs, desired properties of estimated optimal portfolios are ...
Global optimization of silicon nanowires for efficient parametric processes
DEFF Research Database (Denmark)
Vukovic, Dragana; Xu, Jing; Mørk, Jesper
2013-01-01
We present a global optimization of silicon nanowires for parametric single-pump mixing. For the first time, the effect of surface roughness-induced loss is included in the analysis, significantly influencing the optimum waveguide dimensions.......We present a global optimization of silicon nanowires for parametric single-pump mixing. For the first time, the effect of surface roughness-induced loss is included in the analysis, significantly influencing the optimum waveguide dimensions....
New methods in efficient coal transportation
Energy Technology Data Exchange (ETDEWEB)
Monroe, C.O.; Wolach, D.G.; Alexander, A.B. [Savage Industries Inc., Salt Lake City, UT (United States)
1998-10-01
With the increasing trend towards railroad mergers in the USA, there is a growing awareness of competition and of the need for railroads to ensure a better value service. This paper discusses the concept of business process outsourcing and its potential to provide an efficient and integrated transport system for coal handling. Examples at US coal distribution facilities are given. 6 photos., 1 fig.
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.
Gekeler, Simon
2016-01-01
The book provides suggestions on how to start using bionic optimization methods, including pseudo-code examples of each of the important approaches and outlines of how to improve them. The most efficient methods for accelerating the studies are discussed. These include the selection of size and generations of a study’s parameters, modification of these driving parameters, switching to gradient methods when approaching local maxima, and the use of parallel working hardware. Bionic Optimization means finding the best solution to a problem using methods found in nature. As Evolutionary Strategies and Particle Swarm Optimization seem to be the most important methods for structural optimization, we primarily focus on them. Other methods such as neural nets or ant colonies are more suited to control or process studies, so their basic ideas are outlined in order to motivate readers to start using them. A set of sample applications shows how Bionic Optimization works in practice. From academic studies on simple fra...
Optimizing efficiency on conventional transformer based low power AC/DC standby power supplies
DEFF Research Database (Denmark)
Nielsen, Nils
2004-01-01
This article describes the research results for simple and cheap methods to reduce the idle- and load-losses in very low power conventional transformer based power supplies intended for standby usage. In this case "very low power" means 50 Hz/230 V-AC to 5 V-DC@1 W. The efficiency is measured...... on two common power supply topologies designed for this power level. The two described topologies uses either a series (or linear) or a buck regulation approach. Common to the test power supplies is they either are using a standard cheap off-the-shelf transformer, or one, which are loss optimized by very...
Optimal Control for Bufferbloat Queue Management Using Indirect Method with Parametric Optimization
Directory of Open Access Journals (Sweden)
Amr Radwan
2016-01-01
Full Text Available Because memory buffers become larger and cheaper, they have been put into network devices to reduce the number of loss packets and improve network performance. However, the consequences of large buffers are long queues at network bottlenecks and throughput saturation, which has been recently noticed in research community as bufferbloat phenomenon. To address such issues, in this article, we design a forward-backward optimal control queue algorithm based on an indirect approach with parametric optimization. The cost function which we want to minimize represents a trade-off between queue length and packet loss rate performance. Through the integration of an indirect approach with parametric optimization, our proposal has advantages of scalability and accuracy compared to direct approaches, while still maintaining good throughput and shorter queue length than several existing queue management algorithms. All numerical analysis, simulation in ns-2, and experiment results are provided to solidify the efficiency of our proposal. In detailed comparisons to other conventional algorithms, the proposed procedure can run much faster than direct collocation methods while maintaining a desired short queue (≈40 packets in simulation and 80 (ms in experiment test.
DEFF Research Database (Denmark)
Meng, Lexuan; Dragicevic, Tomislav; Quintero, Juan Carlos Vasquez
2015-01-01
This paper proposes a hierarchical control scheme which applies optimization method into DC microgrids in order to improve the system overall efficiency while considering the State-of-Charge (SoC) balancing at the same time. Primary droop controller, secondary voltage restoration controller...... and tertiary optimization tool formulate the complete hierarchical control system. Virtual resistances are taken as the decision variables for achieving the objective. simulation results are presented to verify the proposed approach....
Optimization of ultrasonic array inspections using an efficient hybrid model and real crack shapes
Energy Technology Data Exchange (ETDEWEB)
Felice, Maria V., E-mail: maria.felice@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol, U.K. and NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom); Velichko, Alexander, E-mail: p.wilcox@bristol.ac.uk; Wilcox, Paul D., E-mail: p.wilcox@bristol.ac.uk [Department of Mechanical Engineering, University of Bristol, Bristol (United Kingdom); Barden, Tim; Dunhill, Tony [NDE Laboratory, Rolls-Royce plc., Bristol (United Kingdom)
2015-03-31
Models which simulate the interaction of ultrasound with cracks can be used to optimize ultrasonic array inspections, but this approach can be time-consuming. To overcome this issue an efficient hybrid model is implemented which includes a finite element method that requires only a single layer of elements around the crack shape. Scattering Matrices are used to capture the scattering behavior of the individual cracks and a discussion on the angular degrees of freedom of elastodynamic scatterers is included. Real crack shapes are obtained from X-ray Computed Tomography images of cracked parts and these shapes are inputted into the hybrid model. The effect of using real crack shapes instead of straight notch shapes is demonstrated. An array optimization methodology which incorporates the hybrid model, an approximate single-scattering relative noise model and the real crack shapes is then described.
Memory Efficient PCA Methods for Large Group ICA.
Rachakonda, Srinivas; Silva, Rogers F; Liu, Jingyu; Calhoun, Vince D
2016-01-01
Principal component analysis (PCA) is widely used for data reduction in group independent component analysis (ICA) of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimensional temporally concatenated datasets into its group PCA space. Existing randomized PCA methods can determine the PCA subspace with minimal memory requirements and, thus, are ideal for solving large PCA problems. Since the number of dataloads is not typically optimized, we extend one of these methods to compute PCA of very large datasets with a minimal number of dataloads. This method is coined multi power iteration (MPOWIT). The key idea behind MPOWIT is to estimate a subspace larger than the desired one, while checking for convergence of only the smaller subset of interest. The number of iterations is reduced considerably (as well as the number of dataloads), accelerating convergence without loss of accuracy. More importantly, in the proposed implementation of MPOWIT, the memory required for successful recovery of the group principal components becomes independent of the number of subjects analyzed. Highly efficient subsampled eigenvalue decomposition techniques are also introduced, furnishing excellent PCA subspace approximations that can be used for intelligent initialization of randomized methods such as MPOWIT. Together, these developments enable efficient estimation of accurate principal components, as we illustrate by solving a 1600-subject group-level PCA of fMRI with standard acquisition parameters, on a regular desktop computer with only 4 GB RAM, in just a few hours. MPOWIT is also highly scalable and could realistically solve group-level PCA of fMRI on thousands of subjects, or more, using standard hardware, limited only by time, not memory. Also, the MPOWIT algorithm is highly parallelizable, which would enable fast, distributed implementations ideal for big
Memory efficient PCA methods for large group ICA
Directory of Open Access Journals (Sweden)
Srinivas eRachakonda
2016-02-01
Full Text Available Principal component analysis (PCA is widely used for data reduction in group independent component analysis (ICA of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimensional temporally concatenated datasets into its group PCA space. Existing randomized PCA methods can determine the PCA subspace with minimal memory requirements and, thus, are ideal for solving large PCA problems. Since the number of dataloads is not typically optimized, we extend one of these methods to compute PCA of very large datasets with a minimal number of dataloads. This method is coined multi power iteration (MPOWIT. The key idea behind MPOWIT is to estimate a subspace larger than the desired one, while checking for convergence of only the smaller subset of interest. The number of iterations is reduced considerably (as well as the number of dataloads, accelerating convergence without loss of accuracy. More importantly, in the proposed implementation of MPOWIT, the memory required for successful recovery of the group principal components becomes independent of the number of subjects analyzed. Highly efficient subsampled eigenvalue decomposition techniques are also introduced, furnishing excellent PCA subspace approximations that can be used for intelligent initialization of randomized methods such as MPOWIT. Together, these developments enable efficient estimation of accurate principal components, as we illustrate by solving a 1600-subject group-level PCA of fMRI with standard acquisition parameters, on a regular desktop computer with only 4GB RAM, in just a few hours. MPOWIT is also highly scalable and could realistically solve group-level PCA of fMRI on thousands of subjects, or more, using standard hardware, limited only by time, not memory. Also, the MPOWIT algorithm is highly parallelizable, which would enable fast, distributed implementations
An Optimization Method of Passenger Assignment for Customized Bus
Yang Cao; Jian Wang
2017-01-01
This study proposes an optimization method of passenger assignment on customized buses (CB). Our proposed method guarantees benefits to passengers by balancing the elements of travel time, waiting time, delay, and economic cost. The optimization problem was solved using a Branch and Bound (B&B) algorithm based on the shortest path for the selected stations. A simulation-based evaluation of the proposed optimization method was conducted. We find that a CB service can save 38.33% in average tra...
EPA’s Travel Efficiency Method (TEAM) AMPO Presentation
Presentation describes EPA’s Travel Efficiency Assessment Method (TEAM) assessing potential travel efficiency strategies for reducing travel activity and emissions, includes reduction estimates in Vehicle Miles Traveled in four different geographic areas.
Optimal reload and depletion method for pressurized water reactors
International Nuclear Information System (INIS)
Ahn, D.H.
1984-01-01
A new method has been developed to automatically reload and deplete a PWR so that both the enriched inventory requirements during the reactor cycle and the cost of reloading the core are minimized. This is achieved through four stepwise optimization calculations: 1) determination of the minimum fuel requirement for an equivalent three-region core model, 2) optimal selection and allocation of fuel requirement for an equivalent three-region core model, 2) optimal selection and allocation of fuel assemblies for each of the three regions to minimize the cost of the fresh reload fuel, 3) optimal placement of fuel assemblies to conserve regionwise optimal conditions and 4) optimal control through poison management to deplete individual fuel assemblies to maximize EOC k/sub eff/. Optimizing the fuel cost of reloading and depleting a PWR reactor cycle requires solutions to two separate optimization calculations. One of these minimizes the enriched fuel inventory in the core by optimizing the EOC k/sub eff/. The other minimizes the cost of the fresh reload cost. Both of these optimization calculations have now been combined to provide a new method for performing an automatic optimal reload of PWR's. The new method differs from previous methods in that the optimization process performs all tasks required to reload and deplete a PWR
An efficient method of reducing glass dispersion tolerance sensitivity
Sparrold, Scott W.; Shepard, R. Hamilton
2014-12-01
Constraining the Seidel aberrations of optical surfaces is a common technique for relaxing tolerance sensitivities in the optimization process. We offer an observation that a lens's Abbe number tolerance is directly related to the magnitude by which its longitudinal and transverse color are permitted to vary in production. Based on this observation, we propose a computationally efficient and easy-to-use merit function constraint for relaxing dispersion tolerance sensitivity. Using the relationship between an element's chromatic aberration and dispersion sensitivity, we derive a fundamental limit for lens scale and power that is capable of achieving high production yield for a given performance specification, which provides insight on the point at which lens splitting or melt fitting becomes necessary. The theory is validated by comparing its predictions to a formal tolerance analysis of a Cooke Triplet, and then applied to the design of a 1.5x visible linescan lens to illustrate optimization for reduced dispersion sensitivity. A selection of lenses in high volume production is then used to corroborate the proposed method of dispersion tolerance allocation.
Efficient transportation for Vermont : optimal statewide transit networks.
2011-01-01
"Public transit systems are receiving increased attention as viable solutions to problems with : transportation system robustness, energy-efficiency and equity. The over-reliance on a single : mode, the automobile, is a threat to system robustness. I...
Augmented Lagrangian Method For Discretized Optimal Control ...
African Journals Online (AJOL)
In this paper, we are concerned with one-dimensional time invariant optimal control problem, whose objective function is quadratic and the dynamical system is a differential equation with initial condition .Since most real life problems are nonlinear and their analytical solutions are not readily available, we resolve to ...
METHOD FOR OPTIMIZING THE ENERGY OF PUMPS
Skovmose Kallesøe, Carsten; De Persis, Claudio
2013-01-01
The device for energy-optimization on operation of several centrifugal pumps controlled in rotational speed, in a hydraulic installation, begins firstly with determining which pumps as pilot pumps are assigned directly to a consumer and which pumps are hydraulically connected in series upstream of
State space Newton's method for topology optimization
DEFF Research Database (Denmark)
Evgrafov, Anton
2014-01-01
/10/1-type constraints on the design field through penalties in many topology optimization approaches. We test the algorithm on the benchmark problems of dissipated power minimization for Stokes flows, and in all cases the algorithm outperforms the traditional first order reduced space/nested approaches...
COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U
Energy Technology Data Exchange (ETDEWEB)
Sun, Y.; Borland, Michael
2017-06-25
Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.
Efficient Approximation of Optimal Control for Markov Games
DEFF Research Database (Denmark)
Fearnley, John; Rabe, Markus; Schewe, Sven
2011-01-01
We study the time-bounded reachability problem for continuous-time Markov decision processes (CTMDPs) and games (CTMGs). Existing techniques for this problem use discretisation techniques to break time into discrete intervals, and optimal control is approximated for each interval separately...
On multigrid-CG for efficient topology optimization
DEFF Research Database (Denmark)
Amir, Oded; Aage, Niels; Lazarov, Boyan Stefanov
2014-01-01
reduction is obtained by exploiting specific characteristics of a multigrid preconditioned conjugate gradients (MGCG) solver. In particular, the number of MGCG iterations is reduced by relating it to the geometric parameters of the problem. At the same time, accurate outcome of the optimization process...
Efficient amplification of photonic qubits by optimal quantum cloning
Czech Academy of Sciences Publication Activity Database
Bartkiewicz, K.; Černoch, A.; Lemr, K.; Soubusta, Jan; Stobińska, M.
2014-01-01
Roč. 89, č. 6 (2014), "062322-1"-"062322-10" ISSN 1050-2947 Institutional support: RVO:68378271 Keywords : optimal quantum cloning * cryptography * qubit * phase-independent quantum amplifier Subject RIV: BH - Optics, Masers, Lasers Impact factor: 2.808, year: 2014
Time-efficient multidimensional threshold tracking method
DEFF Research Database (Denmark)
Fereczkowski, Michal; Kowalewski, Borys; Dau, Torsten
2015-01-01
Traditionally, adaptive methods have been used to reduce the time it takes to estimate psychoacoustic thresholds. However, even with adaptive methods, there are many cases where the testing time is too long to be clinically feasible, particularly when estimating thresholds as a function of anothe...
Logic-based methods for optimization combining optimization and constraint satisfaction
Hooker, John
2011-01-01
A pioneering look at the fundamental role of logic in optimization and constraint satisfaction While recent efforts to combine optimization and constraint satisfaction have received considerable attention, little has been said about using logic in optimization as the key to unifying the two fields. Logic-Based Methods for Optimization develops for the first time a comprehensive conceptual framework for integrating optimization and constraint satisfaction, then goes a step further and shows how extending logical inference to optimization allows for more powerful as well as flexible
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.
Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks.
Zhang, Jing; Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho
2017-09-15
In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity.
A dynamic optimization on economic energy efficiency in development: A numerical case of China
International Nuclear Information System (INIS)
Wang, Dong
2014-01-01
This paper is based on dynamic optimization methodology to investigate the economic energy efficiency issues in developing countries. The paper introduces some definitions about energy efficiency both in economics and physics, and establishes a quantitative way for measuring the economic energy efficiency. The linkage between economic energy efficiency, energy consumption and other macroeconomic variables is demonstrated primarily. Using the methodology of dynamic optimization, a maximum problem of economic energy efficiency over time, which is subjected to the extended Solow growth model and instantaneous investment rate, is modelled. In this model, the energy consumption is set as a control variable and the capital is regarded as a state variable. The analytic solutions can be derived and the diagrammatic analysis provides saddle-point equilibrium. A numerical simulation based on China is also presented; meanwhile, the optimal paths of investment and energy consumption can be drawn. The dynamic optimization encourages governments in developing countries to pursue higher economic energy efficiency by controlling the energy consumption and regulating the investment state as it can conserve energy without influencing the achievement of steady state in terms of Solow model. If that, a sustainable development will be achieved. - Highlights: • A new definition on economic energy efficiency is proposed mathematically. • A dynamic optimization modelling links economic energy efficiency with other macroeconomic variables in long run. • Economic energy efficiency is determined by capital stock level and energy consumption. • Energy saving is a key solution for improving economic energy efficiency
Experimental evaluation of optimization method for developing ultraviolet barrier coatings
Gonome, Hiroki; Okajima, Junnosuke; Komiya, Atsuki; Maruyama, Shigenao
2014-01-01
Ultraviolet (UV) barrier coatings can be used to protect many industrial products from UV attack. This study introduces a method of optimizing UV barrier coatings using pigment particles. The radiative properties of the pigment particles were evaluated theoretically, and the optimum particle size was decided from the absorption efficiency and the back-scattering efficiency. UV barrier coatings were prepared with zinc oxide (ZnO) and titanium dioxide (TiO2). The transmittance of the UV barrier coating was calculated theoretically. The radiative transfer in the UV barrier coating was modeled using the radiation element method by ray emission model (REM2). In order to validate the calculated results, the transmittances of these coatings were measured by a spectrophotometer. A UV barrier coating with a low UV transmittance and high VIS transmittance could be achieved. The calculated transmittance showed a similar spectral tendency with the measured one. The use of appropriate particles with optimum size, coating thickness and volume fraction will result in effective UV barrier coatings. UV barrier coatings can be achieved by the application of optical engineering.
Performance indices and evaluation of algorithms in building energy efficient design optimization
International Nuclear Information System (INIS)
Si, Binghui; Tian, Zhichao; Jin, Xing; Zhou, Xin; Tang, Peng; Shi, Xing
2016-01-01
Building energy efficient design optimization is an emerging technique that is increasingly being used to design buildings with better overall performance and a particular emphasis on energy efficiency. To achieve building energy efficient design optimization, algorithms are vital to generate new designs and thus drive the design optimization process. Therefore, the performance of algorithms is crucial to achieving effective energy efficient design techniques. This study evaluates algorithms used for building energy efficient design optimization. A set of performance indices, namely, stability, robustness, validity, speed, coverage, and locality, is proposed to evaluate the overall performance of algorithms. A benchmark building and a design optimization problem are also developed. Hooke–Jeeves algorithm, Multi-Objective Genetic Algorithm II, and Multi-Objective Particle Swarm Optimization algorithm are evaluated by using the proposed performance indices and benchmark design problem. Results indicate that no algorithm performs best in all six areas. Therefore, when facing an energy efficient design problem, the algorithm must be carefully selected based on the nature of the problem and the performance indices that matter the most. - Highlights: • Six indices of algorithm performance in building energy optimization are developed. • For each index, its concept is defined and the calculation formulas are proposed. • A benchmark building and benchmark energy efficient design problem are proposed. • The performance of three selected algorithms are evaluated.
International Nuclear Information System (INIS)
Gao Gan
2015-01-01
Song [Song D 2004 Phys. Rev. A 69 034301] first proposed two key distribution schemes with the symmetry feature. We find that, in the schemes, the private channels which Alice and Bob publicly announce the initial Bell state or the measurement result through are not needed in discovering keys, and Song’s encoding methods do not arrive at the optimization. Here, an optimized encoding method is given so that the efficiencies of Song’s schemes are improved by 7/3 times. Interestingly, this optimized encoding method can be extended to the key distribution scheme composed of generalized Bell states. (paper)
Efficient pseudospectral methods for density functional calculations
International Nuclear Information System (INIS)
Murphy, R. B.; Cao, Y.; Beachy, M. D.; Ringnalda, M. N.; Friesner, R. A.
2000-01-01
Novel improvements of the pseudospectral method for assembling the Coulomb operator are discussed. These improvements consist of a fast atom centered multipole method and a variation of the Head-Gordan J-engine analytic integral evaluation. The details of the methodology are discussed and performance evaluations presented for larger molecules within the context of DFT energy and gradient calculations. (c) 2000 American Institute of Physics
On the efficiency of a randomized mirror descent algorithm in online optimization problems
Gasnikov, A. V.; Nesterov, Yu. E.; Spokoiny, V. G.
2015-04-01
A randomized online version of the mirror descent method is proposed. It differs from the existing versions by the randomization method. Randomization is performed at the stage of the projection of a subgradient of the function being optimized onto the unit simplex rather than at the stage of the computation of a subgradient, which is common practice. As a result, a componentwise subgradient descent with a randomly chosen component is obtained, which admits an online interpretation. This observation, for example, has made it possible to uniformly interpret results on weighting expert decisions and propose the most efficient method for searching for an equilibrium in a zero-sum two-person matrix game with sparse matrix.
Bloom, Guillaume; Larat, Christian; Lallier, Eric; Lee-Bouhours, Mane-Si Laure; Loiseaux, Brigitte; Huignard, Jean-Pierre
2011-02-10
We have designed a high-efficiency array generator composed of subwavelength grooves etched in a GaAs substrate for operation at 4.5 μm. The method used combines rigorous coupled wave analysis with an optimization algorithm. The optimized beam splitter has both a high efficiency (∼96%) and a good intensity uniformity (∼0.2%). The fabrication error tolerances are numerically calculated, and it is shown that this subwavelength array generator could be fabricated with current electron beam writers and inductively coupled plasma etching. Finally, we studied the effect of a simple and realistic antireflection coating on the performance of the beam splitter.
Evaluation of a proposed optimization method for discrete-event simulation models
Directory of Open Access Journals (Sweden)
Alexandre Ferreira de Pinho
2012-12-01
Full Text Available Optimization methods combined with computer-based simulation have been utilized in a wide range of manufacturing applications. However, in terms of current technology, these methods exhibit low performance levels which are only able to manipulate a single decision variable at a time. Thus, the objective of this article is to evaluate a proposed optimization method for discrete-event simulation models based on genetic algorithms which exhibits more efficiency in relation to computational time when compared to software packages on the market. It should be emphasized that the variable's response quality will not be altered; that is, the proposed method will maintain the solutions' effectiveness. Thus, the study draws a comparison between the proposed method and that of a simulation instrument already available on the market and has been examined in academic literature. Conclusions are presented, confirming the proposed optimization method's efficiency.
Methods of orbit correction system optimization
International Nuclear Information System (INIS)
Chao, Yu-Chiu.
1997-01-01
Extracting optimal performance out of an orbit correction system is an important component of accelerator design and evaluation. The question of effectiveness vs. economy, however, is not always easily tractable. This is especially true in cases where betatron function magnitude and phase advance do not have smooth or periodic dependencies on the physical distance. In this report a program is presented using linear algebraic techniques to address this problem. A systematic recipe is given, supported with quantitative criteria, for arriving at an orbit correction system design with the optimal balance between performance and economy. The orbit referred to in this context can be generalized to include angle, path length, orbit effects on the optical transfer matrix, and simultaneous effects on multiple pass orbits
Efficient Guiding Towards Cost-Optimality in UPPAAL
DEFF Research Database (Denmark)
Behrmann, Gerd; Fehnker, Ansgar; Hune, Thomas S.
2001-01-01
with prices on both locations and transitions. The presented algorithm is based on a symbolic semantics of UTPA, and an efficient representation and operations based on difference bound matrices. In analogy with Dijkstra’s shortest path algorithm, we show that the search order of the algorithm can be chosen......In this paper we present an algorithm for efficiently computing the minimum cost of reaching a goal state in the model of Uniformly Priced Timed Automata (UPTA). This model can be seen as a submodel of the recently suggested model of linearly priced timed automata, which extends timed automata...
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...
Primal Interior-Point Method for Large Sparse Minimax Optimization
Czech Academy of Sciences Publication Activity Database
Lukšan, Ladislav; Matonoha, Ctirad; Vlček, Jan
2009-01-01
Roč. 45, č. 5 (2009), s. 841-864 ISSN 0023-5954 R&D Projects: GA AV ČR IAA1030405; GA ČR GP201/06/P397 Institutional research plan: CEZ:AV0Z10300504 Keywords : unconstrained optimization * large-scale optimization * minimax optimization * nonsmooth optimization * interior-point methods * modified Newton methods * variable metric methods * computational experiments Subject RIV: BA - General Mathematics Impact factor: 0.445, year: 2009 http://dml.cz/handle/10338.dmlcz/140034
Numerical methods of mathematical optimization with Algol and Fortran programs
Künzi, Hans P; Zehnder, C A; Rheinboldt, Werner
1971-01-01
Numerical Methods of Mathematical Optimization: With ALGOL and FORTRAN Programs reviews the theory and the practical application of the numerical methods of mathematical optimization. An ALGOL and a FORTRAN program was developed for each one of the algorithms described in the theoretical section. This should result in easy access to the application of the different optimization methods.Comprised of four chapters, this volume begins with a discussion on the theory of linear and nonlinear optimization, with the main stress on an easily understood, mathematically precise presentation. In addition
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.
Energy Technology Data Exchange (ETDEWEB)
Sevcik, Petr
2009-07-01
The Kaplan turbine has the best theoretical efficiency chart in the total range of operation. In order to achieve these good properties, the turbine has to be adjusted optimally. In general, these settings are performed by the manufacturer of turbines during commissioning. In practice one often meets Kaplan turbines where the scenery does not correspond to the optimal control line. The author of the contribution under consideration reports on possible causes for these errors and also methods of how this scenery can be optimized cost-effectively and how to minimize power losses.
Design and Optimization Method of a Two-Disk Rotor System
Huang, Jingjing; Zheng, Longxi; Mei, Qing
2016-04-01
An integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.
Statistical methods towards more efficient infiltration measurements.
Franz, T; Krebs, P
2006-01-01
A comprehensive knowledge about the infiltration situation in a catchment is required for operation and maintenance. Due to the high expenditures, an optimisation of necessary measurement campaigns is essential. Methods based on multivariate statistics were developed to improve the information yield of measurements by identifying appropriate gauge locations. The methods have a high degree of freedom against data needs. They were successfully tested on real and artificial data. For suitable catchments, it is estimated that the optimisation potential amounts up to 30% accuracy improvement compared to nonoptimised gauge distributions. Beside this, a correlation between independent reach parameters and dependent infiltration rates could be identified, which is not dominated by the groundwater head.
Optimization of high-efficiency components; Optimieren auf hohem Niveau
Energy Technology Data Exchange (ETDEWEB)
Neumann, Eva
2009-07-01
High efficiency is a common feature of modern current inverters and is not a unique selling proposition. Other factors that influence the buyer's decision are cost reduction, reliability and service, optimum grid integration, and the challenges of the competitive thin film technology. (orig.)
Optimizing the efficiency of femtosecond-laser-written holograms
DEFF Research Database (Denmark)
Wædegaard, Kristian Juncher; Hansen, Henrik Dueholm; Balling, Peter
2013-01-01
Computer-generated binary holograms are written on a polished copper surface using single 800-nm, 120-fs pulses from a 1-kHz-repetition-rate laser system. The hologram efficiency (i.e. the power in the holographic reconstructed image relative to the incoming laser power) is investigated...
Efficient Guiding Towards Cost-Optimality in Uppaal
DEFF Research Database (Denmark)
Behrmann, Gerd; Fehnker, Ansgar; Hune, Thomas S.
2001-01-01
with prices on both locations and transitions. The presented algorithm is based on a symbolic semantics of UTPA, and an efficient representation and operations based on difference bound matrices. In analogy with Dijkstra’s shortest path algorithm, we show that the search order of the algorithm can be chosen...
Review of dynamic optimization methods in renewable natural resource management
Williams, B.K.
1989-01-01
In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. The applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.
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.
Online optimization of a multi-conversion-level DC home microgrid for system efficiency enhancement
DEFF Research Database (Denmark)
Boscaino, V.; Guerrero, J. M.; Ciornei, I.
2017-01-01
stages, three paralleled DC/DC converters are implemented. A Genetic Algorithm performs the on-line optimization of the DC network’s global efficiency, generating the optimal current sharing ratios of the concurrent power converters. The overall DC/DC conversion system including the optimization section......In this paper, an on-line management system for the optimal efficiency operation of a multi-bus DC home distribution system is proposed. The operation of the system is discussed with reference to a distribution system with two conversion stages and three voltage levels. In each of the conversion...
Rosić, Miroslav; Pešić, Dalibor; Kukić, Dragoslav; Antić, Boris; Božović, Milan
2017-01-01
Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine "real best performers". Need for composite road safety index is becoming dominant since road safety presents a complex system where more and more indicators are constantly being developed to describe it. Among wide variety of models and developed composite indexes, a decision maker can come to even bigger dilemma than choosing one adequate risk measure. As DEA and TOPSIS are well-known mathematical models and have recently been increasingly used for risk evaluation in road safety, we used efficiencies (composite indexes) obtained by different models, based on DEA and TOPSIS, to present PROMETHEE-RS model for selection of optimal method for composite index. Method for selection of optimal composite index is based on three parameters (average correlation, average rank variation and average cluster variation) inserted into a PROMETHEE MCDM method in order to choose the optimal one. The model is tested by comparing 27 police departments in Serbia. Copyright © 2016 Elsevier Ltd. All rights reserved.
Efficient protein structure search using indexing methods.
Kim, Sungchul; Sael, Lee; Yu, Hwanjo
2013-01-01
Understanding functions of proteins is one of the most important challenges in many studies of biological processes. The function of a protein can be predicted by analyzing the functions of structurally similar proteins, thus finding structurally similar proteins accurately and efficiently from a large set of proteins is crucial. A protein structure can be represented as a vector by 3D-Zernike Descriptor (3DZD) which compactly represents the surface shape of the protein tertiary structure. This simplified representation accelerates the searching process. However, computing the similarity of two protein structures is still computationally expensive, thus it is hard to efficiently process many simultaneous requests of structurally similar protein search. This paper proposes indexing techniques which substantially reduce the search time to find structurally similar proteins. In particular, we first exploit two indexing techniques, i.e., iDistance and iKernel, on the 3DZDs. After that, we extend the techniques to further improve the search speed for protein structures. The extended indexing techniques build and utilize an reduced index constructed from the first few attributes of 3DZDs of protein structures. To retrieve top-k similar structures, top-10 × k similar structures are first found using the reduced index, and top-k structures are selected among them. We also modify the indexing techniques to support θ-based nearest neighbor search, which returns data points less than θ to the query point. The results show that both iDistance and iKernel significantly enhance the searching speed. In top-k nearest neighbor search, the searching time is reduced 69.6%, 77%, 77.4% and 87.9%, respectively using iDistance, iKernel, the extended iDistance, and the extended iKernel. In θ-based nearest neighbor serach, the searching time is reduced 80%, 81%, 95.6% and 95.6% using iDistance, iKernel, the extended iDistance, and the extended iKernel, respectively.
Efficient Training Methods for Conditional Random Fields
2008-02-01
Learning (ICML), 2007. [63] Bruce G. Lindsay. Composite likelihood methods. Contemporary Mathematics, pages 221–239, 1988. 189 [64] Yan Liu, Jaime ...Conference on Machine Learning (ICML), pages 737–744, 2005. [107] Erik F. Tjong Kim Sang and Sabine Buchholz. Introduction to the CoNLL-2000 shared task
Computationally efficient methods for digital control
Guerreiro Tome Antunes, D.J.; Hespanha, J.P.; Silvestre, C.J.; Kataria, N.; Brewer, F.
2008-01-01
The problem of designing a digital controller is considered with the novelty of explicitly taking into account the computation cost of the controller implementation. A class of controller emulation methods inspired by numerical analysis is proposed. Through various examples it is shown that these
Efficient orbit integration by manifold correction methods.
Fukushima, Toshio
2005-12-01
Triggered by a desire to investigate, numerically, the planetary precession through a long-term numerical integration of the solar system, we developed a new formulation of numerical integration of orbital motion named manifold correct on methods. The main trick is to rigorously retain the consistency of physical relations, such as the orbital energy, the orbital angular momentum, or the Laplace integral, of a binary subsystem. This maintenance is done by applying a correction to the integrated variables at each integration step. Typical methods of correction are certain geometric transformations, such as spatial scaling and spatial rotation, which are commonly used in the comparison of reference frames, or mathematically reasonable operations, such as modularization of angle variables into the standard domain [-pi, pi). The form of the manifold correction methods finally evolved are the orbital longitude methods, which enable us to conduct an extremely precise integration of orbital motions. In unperturbed orbits, the integration errors are suppressed at the machine epsilon level for an indefinitely long period. In perturbed cases, on the other hand, the errors initially grow in proportion to the square root of time and then increase more rapidly, the onset of which depends on the type and magnitude of the perturbations. This feature is also realized for highly eccentric orbits by applying the same idea as used in KS-regularization. In particular, the introduction of time elements greatly enhances the performance of numerical integration of KS-regularized orbits, whether the scaling is applied or not.
Optimization and control methods in industrial engineering and construction
Wang, Xiangyu
2014-01-01
This book presents recent advances in optimization and control methods with applications to industrial engineering and construction management. It consists of 15 chapters authored by recognized experts in a variety of fields including control and operation research, industrial engineering, and project management. Topics include numerical methods in unconstrained optimization, robust optimal control problems, set splitting problems, optimum confidence interval analysis, a monitoring networks optimization survey, distributed fault detection, nonferrous industrial optimization approaches, neural networks in traffic flows, economic scheduling of CCHP systems, a project scheduling optimization survey, lean and agile construction project management, practical construction projects in Hong Kong, dynamic project management, production control in PC4P, and target contracts optimization. The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and c...
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.
Development of an optimal velocity selection method with velocity obstacle
Energy Technology Data Exchange (ETDEWEB)
Kim, Min Geuk; Oh, Jun Ho [KAIST, Daejeon (Korea, Republic of)
2015-08-15
The Velocity obstacle (VO) method is one of the most well-known methods for local path planning, allowing consideration of dynamic obstacles and unexpected obstacles. Typical VO methods separate a velocity map into a collision area and a collision-free area. A robot can avoid collisions by selecting its velocity from within the collision-free area. However, if there are numerous obstacles near a robot, the robot will have very few velocity candidates. In this paper, a method for choosing optimal velocity components using the concept of pass-time and vertical clearance is proposed for the efficient movement of a robot. The pass-time is the time required for a robot to pass by an obstacle. By generating a latticized available velocity map for a robot, each velocity component can be evaluated using a cost function that considers the pass-time and other aspects. From the output of the cost function, even a velocity component that will cause a collision in the future can be chosen as a final velocity if the pass-time is sufficiently long enough.
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.
Najafi, Amir Abbas; Pourahmadi, Zahra
2016-04-01
Selecting the optimal combination of assets in a portfolio is one of the most important decisions in investment management. As investment is a long term concept, looking into a portfolio optimization problem just in a single period may cause loss of some opportunities that could be exploited in a long term view. Hence, it is tried to extend the problem from single to multi-period model. We include trading costs and uncertain conditions to this model which made it more realistic and complex. Hence, we propose an efficient heuristic method to tackle this problem. The efficiency of the method is examined and compared with the results of the rolling single-period optimization and the buy and hold method which shows the superiority of the proposed method.
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.
FEM Optimal Design of Energy Efficient Induction Machines
Directory of Open Access Journals (Sweden)
TUDORACHE, T.
2009-06-01
Full Text Available This paper deals with a comparative numerical analysis of performances of several design solutions of induction machines with improved energy efficiency. Starting from a typical cast aluminum cage induction machine this study highlights the benefit of replacing the classical cast aluminum cage with a cast copper cage in the manufacture of future generation of high efficiency induction machines used as motors or generators. Then the advantage of replacement of standard electrical steel with higher grade steel with smaller losses is pointed out. The numerical analysis carried out in the paper is based on 2D plane-parallel finite element approach of the induction machine, the numerical results being discussed and compared with experimental measurements.
An efficient global energy optimization approach for robust 3D plane segmentation of point clouds
Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian
2018-03-01
Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)
QoE Power-Efficient Multimedia Delivery Method for LTE-A
Mushtaq, M. Sajid; Mellouk, Abdelhamid; Augustin, Brice; Fowler, Scott
2016-01-01
The fastest growing of multimedia services overfuture wireless communication system demand more networkresources, efficient delivery of multimedia service with highusers satisfaction, and power optimization of User Equipments(UEs). The resources and power optimization are significant infuture mobile computing systems, because emerging multimediaservices consume more resources and power. The 4G standard ofLTE-A wireless system has adopted the Discontinuous Reception(DRX) method to extend and o...
Probabilistic methods for maintenance program optimization
International Nuclear Information System (INIS)
Liming, J.K.; Smith, M.J.; Gekler, W.C.
1989-01-01
In today's regulatory and economic environments, it is more important than ever that managers, engineers, and plant staff join together in developing and implementing effective management plans for safety and economic risk. This need applied to both power generating stations and other process facilities. One of the most critical parts of these management plans is the development and continuous enhancement of a maintenance program that optimizes plant or facility safety and profitability. The ultimate objective is to maximize the potential for station or facility success, usually measured in terms of projected financial profitability, while meeting or exceeding meaningful and reasonable safety goals, usually measured in terms of projected damage or consequence frequencies. This paper describes the use of the latest concepts in developing and evaluating maintenance programs to achieve maintenance program optimization (MPO). These concepts are based on significant field experience gained through the integration and application of fundamentals developed for industry and Electric Power Research Institute (EPRI)-sponsored projects on preventive maintenance (PM) program development and reliability-centered maintenance (RCM)
Directory of Open Access Journals (Sweden)
Tunjo Perić
2017-09-01
Full Text Available This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained results indicate a high efficiency of the applied methods in solving the problem.
An assessment of diagnostic efficiency by Taguchi/DEA methods.
Taner, Mehmet Tolga; Sezen, Bulent
2009-01-01
The aim of this paper is to propose a new, objective and consistent method for the calculation of the diagnostic efficiency in medical applications. In this study, a hybrid method of Taguchi and DEA is proposed. This method reflects the diversity of inputs and outputs by incorporating the stepwise application of sensitivity, specificity, leveling threshold, and efficiency score. A hypothetical case study is given which involves eight readers of X-ray films in clinical radiology. The selected pairs of sensitivity and specificity yielded two efficient readers. After super efficiency analysis, Reader 6 is found to be the most efficient reader. The paper presents a new, objective and consistent method for the calculation of the diagnostic efficiency in medical applications.
Optimal Energy-Efficient Sensing and Power Allocation in Cognitive Radio Networks
Directory of Open Access Journals (Sweden)
Xia Wu
2014-01-01
Full Text Available We consider a joint optimization of sensing parameter and power allocation for an energy-efficient cognitive radio network (CRN in which the primary user (PU is protected. The optimization problem to maximize the energy efficiency of CRN is formulated as a function of two variables, which are sensing time and transmit power, subject to the average interference power to the PU and the target detection probability. During the optimizing process, the quality of service parameter (the minimum rate acceptable to secondary users (SUs has also been taken into consideration. The optimal solutions are analyzed and an algorithm combined with fractional programming that maximizes the energy efficiency for CRN is presented. Numerical results show that the performance improvement is achieved by the joint optimization of sensing time and power allocation.
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):1031â€“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...
Complex Method Mixed with PSO Applying to Optimization Design of Bridge Crane Girder
Directory of Open Access Journals (Sweden)
He Yan
2017-01-01
Full Text Available In engineer design, basic complex method has not enough global search ability for the nonlinear optimization problem, so it mixed with particle swarm optimization (PSO has been presented in the paper,that is the optimal particle evaluated from fitness function of particle swarm displacement complex vertex in order to realize optimal principle of the largest complex central distance.This method is applied to optimization design problems of box girder of bridge crane with constraint conditions.At first a mathematical model of the girder optimization has been set up,in which box girder cross section area of bridge crane is taken as the objective function, and its four sizes parameters as design variables, girder mechanics performance, manufacturing process, border sizes and so on requirements as constraint conditions. Then complex method mixed with PSO is used to solve optimization design problem of cane box girder from constrained optimization studying approach, and its optimal results have achieved the goal of lightweight design and reducing the crane manufacturing cost . The method is reliable, practical and efficient by the practical engineer calculation and comparative analysis with basic complex method.
Nacelle Chine Installation Based on Wind-Tunnel Test Using Efficient Global Optimization
Kanazaki, Masahiro; Yokokawa, Yuzuru; Murayama, Mitsuhiro; Ito, Takeshi; Jeong, Shinkyu; Yamamoto, Kazuomi
Design exploration of a nacelle chine installation was carried out. The nacelle chine improves stall performance when deploying multi-element high-lift devices. This study proposes an efficient design process using a Kriging surrogate model to determine the nacelle chine installation point in wind-tunnel tests. The design exploration was conducted in a wind-tunnel using the JAXA high-lift aircraft model at the JAXA Large-scale Low-speed Wind Tunnel. The objective was to maximize the maximum lift. The chine installation points were designed on the engine nacelle in the axial and chord-wise direction, while the geometry of the chine was fixed. In the design process, efficient global optimization (EGO) which includes Kriging model and genetic algorithm (GA) was employed. This method makes it possible both to improve the accuracy of the response surface and to explore the global optimum efficiently. Detailed observations of flowfields using the Particle Image Velocimetry method confirmed the chine effect and design results.
Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition
Directory of Open Access Journals (Sweden)
Vito Janko
2017-12-01
Full Text Available The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy.
Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition.
Janko, Vito; Luštrek, Mitja
2017-12-29
The recognition of the user's context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system's energy expenditure and the system's accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy.
Using Markov Chains and Multi-Objective Optimization for Energy-Efficient Context Recognition †
Janko, Vito
2017-01-01
The recognition of the user’s context with wearable sensing systems is a common problem in ubiquitous computing. However, the typically small battery of such systems often makes continuous recognition impractical. The strain on the battery can be reduced if the sensor setting is adapted to each context. We propose a method that efficiently finds near-optimal sensor settings for each context. It uses Markov chains to simulate the behavior of the system in different configurations and the multi-objective genetic algorithm to find a set of good non-dominated configurations. The method was evaluated on three real-life datasets and found good trade-offs between the system’s energy expenditure and the system’s accuracy. One of the solutions, for example, consumed five-times less energy than the default one, while sacrificing only two percentage points of accuracy. PMID:29286301
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.
Control Methods Utilizing Energy Optimizing Schemes in Refrigeration Systems
DEFF Research Database (Denmark)
Larsen, L.S; Thybo, C.; Stoustrup, Jakob
2003-01-01
The potential energy savings in refrigeration systems using energy optimal control has been proved to be substantial. This however requires an intelligent control that drives the refrigeration systems towards the energy optimal state. This paper proposes an approach for a control, which drives th...... the condenser pressure towards an optimal state. The objective of this is to present a feasible method that can be used for energy optimizing control. A simulation model of a simple refrigeration system will be used as basis for testing the control method....
New efficient methods for calculating watersheds
International Nuclear Information System (INIS)
Fehr, E; Andrade, J S Jr; Herrmann, H J; Kadau, D; Moukarzel, C F; Da Cunha, S D; Da Silva, L R; Oliveira, E A
2009-01-01
We present an advanced algorithm for the determination of watershed lines on digital elevation models (DEMs) which is based on the iterative application of invasion percolation (IP). The main advantage of our method over previously proposed ones is that it has a sub-linear time-complexity. This enables us to process systems comprising up to 10 8 sites in a few CPU seconds. Using our algorithm we are able to demonstrate, convincingly and with high accuracy, the fractal character of watershed lines. We find the fractal dimension of watersheds to be D f = 1.211 ± 0.001 for artificial landscapes, D f = 1.10 ± 0.01 for the Alps and D f = 1.11 ± 0.01 for the Himalayas
International Nuclear Information System (INIS)
Nabavi-Pelesaraei, Ashkan; Hosseinzadeh-Bandbafha, Homa; Qasemi-Kordkheili, Peyman; Kouchaki-Penchah, Hamed; Riahi-Dorcheh, Farshid
2016-01-01
In this study a non-parametric method of DEA (Data Envelopment Analysis) and MOGA (Multi-Objective Genetic Algorithm) were used to estimate the energy efficiency and greenhouse gas emissions reduction of wheat farmers in Ahvaz county of Iran. Data were collected using a face-to-face questionnaire method from 39 farmers. The results showed that based on constant returns to scale model, 41.02% of wheat farms were efficient, though based on variable returns to scale model it was 53.23%. The average of technical, pure technical and scale efficiency of wheat farms were 0.94, 0.95 and 0.98, respectively. By following the recommendations of this study, 3640.90 MJ ha"−"1 could be saved (9.13% of total input energy). Moreover, 42 optimal units were found by MOGA. The total energy required and GHG (greenhouse gas) emissions of the best generation of MOGA were about 23105 MJ ha"−"1 and 340 kgCO_2_e_q_. ha"−"1, respectively. The results revealed that the total energy required of MOGA was less than DEA, significantly. Also, the GHG emissions of present, DEA and MOGA farms were about 903, 837 and 340 kgCO_2_e_q_. ha"−"1, respectively. - Highlights: • We analyze the energy efficiency and GHG emissions of wheat production in Iran. • The technical and pure technical efficiencies were 0.94 and 0.95 respectively. • DEA can be saved total energy and GHG emissions 9.13% and 7.28% respectively. • MOGA can be reduced total energy and GHG emissions more than DEA significantly.
Zhang, Minliang; Chen, Qian; Tao, Tianyang; Feng, Shijie; Hu, Yan; Li, Hui; Zuo, Chao
2017-08-21
Temporal phase unwrapping (TPU) is an essential algorithm in fringe projection profilometry (FPP), especially when measuring complex objects with discontinuities and isolated surfaces. Among others, the multi-frequency TPU has been proven to be the most reliable algorithm in the presence of noise. For a practical FPP system, in order to achieve an accurate, efficient, and reliable measurement, one needs to make wise choices about three key experimental parameters: the highest fringe frequency, the phase-shifting steps, and the fringe pattern sequence. However, there was very little research on how to optimize these parameters quantitatively, especially considering all three aspects from a theoretical and analytical perspective simultaneously. In this work, we propose a new scheme to determine simultaneously the optimal fringe frequency, phase-shifting steps and pattern sequence under multi-frequency TPU, robustly achieving high accuracy measurement by a minimum number of fringe frames. Firstly, noise models regarding phase-shifting algorithms as well as 3-D coordinates are established under a projector defocusing condition, which leads to the optimal highest fringe frequency for a FPP system. Then, a new concept termed frequency-to-frame ratio (FFR) that evaluates the magnitude of the contribution of each frame for TPU is defined, on which an optimal phase-shifting combination scheme is proposed. Finally, a judgment criterion is established, which can be used to judge whether the ratio between adjacent fringe frequencies is conducive to stably and efficiently unwrapping the phase. The proposed method provides a simple and effective theoretical framework to improve the accuracy, efficiency, and robustness of a practical FPP system in actual measurement conditions. The correctness of the derived models as well as the validity of the proposed schemes have been verified through extensive simulations and experiments. Based on a normal monocular 3-D FPP hardware system
Efficient computation of optimal oligo-RNA binding.
Hodas, Nathan O; Aalberts, Daniel P
2004-01-01
We present an algorithm that calculates the optimal binding conformation and free energy of two RNA molecules, one or both oligomeric. This algorithm has applications to modeling DNA microarrays, RNA splice-site recognitions and other antisense problems. Although other recent algorithms perform the same calculation in time proportional to the sum of the lengths cubed, O((N1 + N2)3), our oligomer binding algorithm, called bindigo, scales as the product of the sequence lengths, O(N1*N2). The algorithm performs well in practice with the aid of a heuristic for large asymmetric loops. To demonstrate its speed and utility, we use bindigo to investigate the binding proclivities of U1 snRNA to mRNA donor splice sites.
Combustion Model and Control Parameter Optimization Methods for Single Cylinder Diesel Engine
Directory of Open Access Journals (Sweden)
Bambang Wahono
2014-01-01
Full Text Available This research presents a method to construct a combustion model and a method to optimize some control parameters of diesel engine in order to develop a model-based control system. The construction purpose of the model is to appropriately manage some control parameters to obtain the values of fuel consumption and emission as the engine output objectives. Stepwise method considering multicollinearity was applied to construct combustion model with the polynomial model. Using the experimental data of a single cylinder diesel engine, the model of power, BSFC, NOx, and soot on multiple injection diesel engines was built. The proposed method succesfully developed the model that describes control parameters in relation to the engine outputs. Although many control devices can be mounted to diesel engine, optimization technique is required to utilize this method in finding optimal engine operating conditions efficiently beside the existing development of individual emission control methods. Particle swarm optimization (PSO was used to calculate control parameters to optimize fuel consumption and emission based on the model. The proposed method is able to calculate control parameters efficiently to optimize evaluation item based on the model. Finally, the model which added PSO then was compiled in a microcontroller.
Efficient 3D multi-region prostate MRI segmentation using dual optimization.
Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron
2013-01-01
Efficient and accurate extraction of the prostate, in particular its clinically meaningful sub-regions from 3D MR images, is of great interest in image-guided prostate interventions and diagnosis of prostate cancer. In this work, we propose a novel multi-region segmentation approach to simultaneously locating the boundaries of the prostate and its two major sub-regions: the central gland and the peripheral zone. The proposed method utilizes the prior knowledge of the spatial region consistency and employs a customized prostate appearance model to simultaneously segment multiple clinically meaningful regions. We solve the resulted challenging combinatorial optimization problem by means of convex relaxation, for which we introduce a novel spatially continuous flow-maximization model and demonstrate its duality to the investigated convex relaxed optimization problem with the region consistency constraint. Moreover, the proposed continuous max-flow model naturally leads to a new and efficient continuous max-flow based algorithm, which enjoys great advantages in numerics and can be readily implemented on GPUs. Experiments using 15 T2-weighted 3D prostate MR images, by inter- and intra-operator variability, demonstrate the promising performance of the proposed approach.
Directory of Open Access Journals (Sweden)
Xiaoxiao Xu
2012-03-01
Full Text Available The subcritical Organic Rankine Cycle (ORC with 28 working fluids for waste heat recovery is discussed in this paper. The effects of the temperature of the waste heat, the critical temperature of working fluids and the pinch temperature difference in the evaporator on the optimal evaporation temperature (OET of the ORC have been investigated. The second law efficiency of the system is regarded as the objective function and the evaporation temperature is optimized by using the quadratic approximations method. The results show that the OET will appear for the temperature ranges investigated when the critical temperatures of working fluids are lower than the waste heat temperatures by 18 ± 5 K under the pinch temperature difference of 5 K in the evaporator. Additionally, the ORC always exhibits the OET when the pinch temperature difference in the evaporator is raised under the fixed waste heat temperature. The maximum second law efficiency will decrease with the increase of pinch temperature difference in the evaporator.
Energy Technology Data Exchange (ETDEWEB)
Andriushchenko, A.I.
1981-01-01
The problems of increasing the efficiency and optimizing the operational conditions of a thermoelectric power plant and providing efficient operational conditions of the primary and auxillary equipment at a thermoelectric power plant are examined. Methodologies and designs for optimizing the primary parameters of the power-generating equipment based on economic factors are given. A number of recommendations for designing equipment based on the research results are given.
Efficiency profile method to study the hit efficiency of drift chambers
International Nuclear Information System (INIS)
Abyzov, A.; Bel'kov, A.; Lanev, A.; Spiridonov, A.; Walter, M.; Hulsbergen, W.
2002-01-01
A method based on the usage of efficiency profile is proposed to estimate the hit efficiency of drift chambers with a large number of channels. The performance of the method under real conditions of the detector operation has been tested analysing the experimental data from the HERA-B drift chambers
Directory of Open Access Journals (Sweden)
Peng Wang
2013-01-01
Full Text Available This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO. The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions.
Directory of Open Access Journals (Sweden)
Ricardo Soto
2016-01-01
Full Text Available The Machine-Part Cell Formation Problem (MPCFP is a NP-Hard optimization problem that consists in grouping machines and parts in a set of cells, so that each cell can operate independently and the intercell movements are minimized. This problem has largely been tackled in the literature by using different techniques ranging from classic methods such as linear programming to more modern nature-inspired metaheuristics. In this paper, we present an efficient parallel version of the Migrating Birds Optimization metaheuristic for solving the MPCFP. Migrating Birds Optimization is a population metaheuristic based on the V-Flight formation of the migrating birds, which is proven to be an effective formation in energy saving. This approach is enhanced by the smart incorporation of parallel procedures that notably improve performance of the several sorting processes performed by the metaheuristic. We perform computational experiments on 1080 benchmarks resulting from the combination of 90 well-known MPCFP instances with 12 sorting configurations with and without threads. We illustrate promising results where the proposal is able to reach the global optimum in all instances, while the solving time with respect to a nonparallel approach is notably reduced.
Active load sharing technique for on-line efficiency optimization in DC microgrids
DEFF Research Database (Denmark)
Sanseverino, E. Riva; Zizzo, G.; Boscaino, V.
2017-01-01
Recently, DC power distribution is gaining more and more importance over its AC counterpart achieving increased efficiency, greater flexibility, reduced volumes and capital cost. In this paper, a 24-120-325V two-level DC distribution system for home appliances, each including three parallel DC......-DC converters, is modeled. An active load sharing technique is proposed for the on-line optimization of the global efficiency of the DC distribution network. The algorithm aims at the instantaneous efficiency optimization of the whole DC network, based on the on-line load current sampling. A Look Up Table......, is created to store the real efficiencies of the converters taking into account components tolerances. A MATLAB/Simulink model of the DC distribution network has been set up and a Genetic Algorithm has been employed for the global efficiency optimization. Simulation results are shown to validate the proposed...
A Method for Solving Combinatoral Optimization Problems
National Research Council Canada - National Science Library
Ruffa, Anthony A
2008-01-01
.... The method discloses that when the boundaries create zones with boundary vertices confined to the adjacent zones, the sets of candidate HPs are found by advancing one zone at a time, considering...
Fast Generation of Near-Optimal Plans for Eco-Efficient Stowage of Large Container Vessels
DEFF Research Database (Denmark)
Pacino, Dario; Delgado, Alberto; Jensen, Rune Møller
2011-01-01
Eco-efficient stowage plans that are both competitive and sustainable have become a priority for the shipping industry. Stowage planning is NP-hard and is a challenging optimization problem in practice. We propose a new 2-phase approach that generates near-optimal stowage plans and fulfills indus...
An efficient cost function for the optimization of an n-layered isotropic cloaked cylinder
International Nuclear Information System (INIS)
Paul, Jason V; Collins, Peter J; Coutu, Ronald A Jr
2013-01-01
In this paper, we present an efficient cost function for optimizing n-layered isotropic cloaked cylinders. Cost function efficiency is achieved by extracting the expression for the angle independent scatterer contribution of an associated Green's function. Therefore, since this cost function is not a function of angle, accounting for every bistatic angle is not necessary and thus more efficient than other cost functions. With this general and efficient cost function, isotropic cloaked cylinders can be optimized for many layers and material parameters. To demonstrate this, optimized cloaked cylinders made of 10, 20 and 30 equal thickness layers are presented for TE and TM incidence. Furthermore, we study the effect layer thickness has on optimized cloaks by optimizing a 10 layer cloaked cylinder over the material parameters and individual layer thicknesses. The optimized material parameters in this effort do not exhibit the dual nature that is evident in the ideal transformation optics design. This indicates that the inevitable field penetration and subsequent PEC boundary condition at the cylinder must be taken into account for an optimal cloaked cylinder design. Furthermore, a more effective cloaked cylinder can be designed by optimizing both layer thickness and material parameters than by additional layers alone. (paper)
OPTIMIZATION METHODS FOR HYDROECOLOGICAL MONITORING SYSTEMS
Directory of Open Access Journals (Sweden)
Inna Pivovarova
2016-09-01
Full Text Available The paper describes current approaches to the rational distribution of monitoring stations. A short review and the organization of the system of hydro-geological observations in different countries are presented. On the basis of real data we propose a solution to the problem of how to calculate the average area per one hydrological station, which is the main indicator of the efficiency and performance of the monitoring system in general. We conclude that a comprehensive approach to the monitoring system organization is important, because only hydrometric and hydrochemical activities coordinated in time provide possibilities needed to analyse the underline causes of the observed pollutants content dynamics in water bodies in the long term.
Methodical Approach to Diagnostics of Efficiency of Production Economic Activity of an Enterprise
Directory of Open Access Journals (Sweden)
Zhukov Andrii V.
2014-03-01
Full Text Available The article offers developments of a methodical approach to diagnostics of efficiency of production economic activity of an enterprise, which, unlike the existing ones, is realised through the following stages: analysis of the enterprise external environment; analysis of the enterprise internal environment; identification of components of efficiency of production economic activity for carrying out complex diagnostics by the following directions: efficiency of subsystems of the enterprise production economic activity, efficiency of use of separate types of resources and socio-economic efficiency; scorecard formation; study of tendencies of change of indicators; identification of cause-effect dependencies between the main components of efficiency for diagnosing reasons of its level; diagnosing deviations of indicator values from their optimal values; development of a managerial decision on preserving and increasing efficiency of production economic activity of the enterprise.
Salcedo-Sanz, S.; Del Ser, J.; Landa-Torres, I.; Gil-López, S.; Portilla-Figueras, J. A.
2014-01-01
This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. PMID:25147860
Optimization of photovoltaic energy production through an efficient switching matrix
Directory of Open Access Journals (Sweden)
Pietro Romano
2013-09-01
Full Text Available This work presents a preliminary study on the implementation of a new system for power output maximization of photovoltaic generators under non-homogeneous conditions. The study evaluates the performance of an efficient switching matrix and the relevant automatic reconfiguration control algorithms. The switching matrix is installed between the PV generator and the inverter, allowing a large number of possible module configurations. PV generator, switching matrix and the intelligent controller have been simulated in Simulink. The proposed reconfiguration system improved the energy extracted by the PV generator under non-uniform solar irradiation conditions. Short calculation times of the proposed control algorithms allow its use in real time applications even where a higher number of PV modules is required.
Optimizing link efficiency for gated DPCCH transmission on HSUPA
DEFF Research Database (Denmark)
Zarco, Carlos Ruben Delgado; Wigard, Jeroen; Kolding, T. E.
2007-01-01
consider the E-DCH performance degradation caused by gating on other radio procedures relying on the DPCCH, such as inner and outer loop power control. Our studies show that gating is beneficial for both for 2 and 10 ms transmission time intervals. The gains in terms of LE with a Vehicular A 30 kmph......To minimize the terminal's transmission power in bursty uplink traffic conditions, the evolved High-Speed Uplink Packet Access (HSUPA) concept in 3GPP WCDMA includes a feature known as Dedicated Physical Control Channel (DPCCH) gating. We present here a detailed link level study of gating from...... a link efficiency (LE) perspective; LE being expressed in bits per second per Watt. While the overall gain mechanisms of gating are well known, we show how special challenges related to discontinuous Enhanced Dedicated Channel (E-DCH) transmission can be addressed for high link and system performance. We...
Optimization Models and Methods Developed at the Energy Systems Institute
N.I. Voropai; V.I. Zorkaltsev
2013-01-01
The paper presents shortly some optimization models of energy system operation and expansion that have been created at the Energy Systems Institute of the Siberian Branch of the Russian Academy of Sciences. Consideration is given to the optimization models of energy development in Russia, a software package intended for analysis of power system reliability, and model of flow distribution in hydraulic systems. A general idea of the optimization methods developed at the Energy Systems Institute...
An optimization method for parameters in reactor nuclear physics
International Nuclear Information System (INIS)
Jachic, J.
1982-01-01
An optimization method for two basic problems of Reactor Physics was developed. The first is the optimization of a plutonium critical mass and the bruding ratio for fast reactors in function of the radial enrichment distribution of the fuel used as control parameter. The second is the maximization of the generation and the plutonium burnup by an optimization of power temporal distribution. (E.G.) [pt
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_{wea}k 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.
Fast optimization of binary clusters using a novel dynamic lattice searching method
International Nuclear Information System (INIS)
Wu, Xia; Cheng, Wen
2014-01-01
Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd) 79 clusters with DFT-fit parameters of Gupta potential
Efficient distribution of toy products using ant colony optimization algorithm
Hidayat, S.; Nurpraja, C. A.
2017-12-01
CV Atham Toys (CVAT) produces wooden toys and furniture, comprises 13 small and medium industries. CVAT always attempt to deliver customer orders on time but delivery costs are high. This is because of inadequate infrastructure such that delivery routes are long, car maintenance costs are high, while fuel subsidy by the government is still temporary. This study seeks to minimize the cost of product distribution based on the shortest route using one of five Ant Colony Optimization (ACO) algorithms to solve the Vehicle Routing Problem (VRP). This study concludes that the best of the five is the Ant Colony System (ACS) algorithm. The best route in 1st week gave a total distance of 124.11 km at a cost of Rp 66,703.75. The 2nd week route gave a total distance of 132.27 km at a cost of Rp 71,095.13. The 3rd week best route gave a total distance of 122.70 km with a cost of Rp 65,951.25. While the 4th week gave a total distance of 132.27 km at a cost of Rp 74,083.63. Prior to this study there was no effort to calculate these figures.
GMG: A Guaranteed, Efficient Global Optimization Algorithm for Remote Sensing.
Energy Technology Data Exchange (ETDEWEB)
D' Helon, CD
2004-08-18
The monocular passive ranging (MPR) problem in remote sensing consists of identifying the precise range of an airborne target (missile, plane, etc.) from its observed radiance. This inverse problem may be set as a global optimization problem (GOP) whereby the difference between the observed and model predicted radiances is minimized over the possible ranges and atmospheric conditions. Using additional information about the error function between the predicted and observed radiances of the target, we developed GMG, a new algorithm to find the Global Minimum with a Guarantee. The new algorithm transforms the original continuous GOP into a discrete search problem, thereby guaranteeing to find the position of the global minimum in a reasonably short time. The algorithm is first applied to the golf course problem, which serves as a litmus test for its performance in the presence of both complete and degraded additional information. GMG is further assessed on a set of standard benchmark functions and then applied to various realizations of the MPR problem.
Optimization of offshore wind turbine support structures using analytical gradient-based method
Chew, Kok Hon; Tai, Kang; Ng, E.Y.K.; Muskulus, Michael
2015-01-01
Design optimization of the offshore wind turbine support structure is an expensive task; due to the highly-constrained, non-convex and non-linear nature of the design problem. This report presents an analytical gradient-based method to solve this problem in an efficient and effective way. The design sensitivities of the objective and constraint functions are evaluated analytically while the optimization of the structure is performed, subject to sizing, eigenfrequency, extreme load an...
Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission
Directory of Open Access Journals (Sweden)
Sandeep Sachdeva
2011-01-01
reduce the error of load forecasting, fuzzy method has been used with Artificial Neural Network (ANN and OFDM transmission is used to get data from outer world and send outputs to outer world accurately and quickly. The error has been reduced to a considerable level in the range of 2-3%. For further reducing the error, Orthogonal Frequency Division Multiplexing (OFDM can be used with Reed-Solomon (RS encoding. Further studies are going on with Fuzzy Regression methods to reduce the error more.
Imani, Rana; Emami, Shahriar Hojjati; Faghihi, Shahab
2015-02-01
A method for carboxylation of graphene oxide (GO) with chloroacetic acid that precisely optimizes and controls the efficacy of the process for bioconjugation applications is proposed. Quantification of COOH groups on nano-graphene oxide sheets (NGOS) is performed by novel colorimetric methylene blue (MB) assay. The GO is synthesized and carboxylated by chloroacetic acid treatment under strong basic condition. The size and morphology of the as-prepared NGOS are characterized by scanning electron microscopy, transmission electron microscopy (TEM), and atomic force microscopy (AFM). The effect of acid to base molar ratio on the physical, chemical, and morphological properties of NGOS is analyzed by Fourier-transformed infrared spectrometry (FTIR), UV-Vis spectroscopy, X-ray diffraction (XRD), AFM, and zeta potential. For evaluation of bioconjugation efficacy, the synthesized nano-carriers with different carboxylation ratios are functionalized by octaarginine peptide sequence (R8) as a biomolecule model containing amine groups. The quantification of attached R8 peptides to graphene nano-sheets' surface is performed with a colorimetric-based assay which includes the application of 2,4,6-Trinitrobenzene sulfonic acid (TNBS). The results show that the thickness and lateral size of nano-sheets are dramatically decreased to 0.8 nm and 50-100 nm after carboxylation process, respectively. X-ray analysis shows the nano-sheets interlaying space is affected by the alteration of chloroacetic acid to base ratio. The MB assay reveals that the COOH groups on the surface of NGOS are maximized at the acid to base ratio of 2 which is confirmed by FTIR, XRD, and zeta potential. The TNBS assay also shows that bioconjugation of the optimized carboxylated NGOS sample with octaarginine peptide is 2.5 times more efficient compared to bare NGOS. The present work provides evidence that treatment of GO by chloroacetic acid under an optimized condition would create a functionalized high surface
Exact and useful optimization methods for microeconomics
Balder, E.J.
2011-01-01
This paper points out that the treatment of utility maximization in current textbooks on microeconomic theory is deficient in at least three respects: breadth of coverage, completeness-cum-coherence of solution methods and mathematical correctness. Improvements are suggested in the form of a
Process control and optimization with simple interval calculation method
DEFF Research Database (Denmark)
Pomerantsev, A.; Rodionova, O.; Høskuldsson, Agnar
2006-01-01
for the quality improvement in the course of production. The latter is an active quality optimization, which takes into account the actual history of the process. The advocate approach is allied to the conventional method of multivariate statistical process control (MSPC) as it also employs the historical process......Methods of process control and optimization are presented and illustrated with a real world example. The optimization methods are based on the PLS block modeling as well as on the simple interval calculation methods of interval prediction and object status classification. It is proposed to employ...... the series of expanding PLS/SIC models in order to support the on-line process improvements. This method helps to predict the effect of planned actions on the product quality and thus enables passive quality control. We have also considered an optimization approach that proposes the correcting actions...
Laser: a Tool for Optimization and Enhancement of Analytical Methods
Energy Technology Data Exchange (ETDEWEB)
Preisler, Jan [Iowa State Univ., Ames, IA (United States)
1997-01-01
In this work, we use lasers to enhance possibilities of laser desorption methods and to optimize coating procedure for capillary electrophoresis (CE). We use several different instrumental arrangements to characterize matrix-assisted laser desorption (MALD) at atmospheric pressure and in vacuum. In imaging mode, 488-nm argon-ion laser beam is deflected by two acousto-optic deflectors to scan plumes desorbed at atmospheric pressure via absorption. All absorbing species, including neutral molecules, are monitored. Interesting features, e.g. differences between the initial plume and subsequent plumes desorbed from the same spot, or the formation of two plumes from one laser shot are observed. Total plume absorbance can be correlated with the acoustic signal generated by the desorption event. A model equation for the plume velocity as a function of time is proposed. Alternatively, the use of a static laser beam for observation enables reliable determination of plume velocities even when they are very high. Static scattering detection reveals negative influence of particle spallation on MS signal. Ion formation during MALD was monitored using 193-nm light to photodissociate a portion of insulin ion plume. These results define the optimal conditions for desorbing analytes from matrices, as opposed to achieving a compromise between efficient desorption and efficient ionization as is practiced in mass spectrometry. In CE experiment, we examined changes in a poly(ethylene oxide) (PEO) coating by continuously monitoring the electroosmotic flow (EOF) in a fused-silica capillary during electrophoresis. An imaging CCD camera was used to follow the motion of a fluorescent neutral marker zone along the length of the capillary excited by 488-nm Ar-ion laser. The PEO coating was shown to reduce the velocity of EOF by more than an order of magnitude compared to a bare capillary at pH 7.0. The coating protocol was important, especially at an intermediate pH of 7.7. The increase of p
METHODS FOR IMPROVING AVAILABILITY AND EFFICIENCY OF COMPUTER INFRASTRUCTURE IN SMART CITIES
Directory of Open Access Journals (Sweden)
Jerzy Balicki
2017-09-01
Full Text Available This paper discusses methods for increasing the availability and efficiency of information infrastructure in smart cities. Two criteria have been formulated to assign some key resources in smart city system. The process of finding some compromise solutions from Pareto-optimal solutions has been illustrated. Metaheuristics of collective intelligence, including particle swarm optimization PSO, ant colony optimization ACO, algorithm of bee colony ABC, and differential evolution DE have been described due to smart city infrastructure improving. Other application of above metaheuristics in smart city have been also presented.
Eukaryotic transcriptomics in silico: Optimizing cDNA-AFLP efficiency
Stölting, K.N.; Gort, G.; Wüst, C.; Wilson, A.B.
2009-01-01
Background - Complementary-DNA based amplified fragment length polymorphism (cDNA-AFLP) is a commonly used tool for assessing the genetic regulation of traits through the correlation of trait expression with cDNA expression profiles. In spite of the frequent application of this method, studies on
Efficient optimal joint channel estimation and data detection for massive MIMO systems
Alshamary, Haider Ali Jasim
2016-08-15
In this paper, we propose an efficient optimal joint channel estimation and data detection algorithm for massive MIMO wireless systems. Our algorithm is optimal in terms of the generalized likelihood ratio test (GLRT). For massive MIMO systems, we show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best of our knowledge, this is the first algorithm which efficiently achieves GLRT-optimal non-coherent detections for massive MIMO systems with general constellations.
DEFF Research Database (Denmark)
Thummala, Prasanth; Schneider, Henrik; Zhang, Zhe
2015-01-01
.The energy efficiency is optimized using a proposed new automatic winding layout (AWL) technique and a comprehensive loss model.The AWL technique generates a large number of transformer winding layouts.The transformer parasitics such as dc resistance, leakage inductance and self-capacitance are calculated...... for each winding layout.An optimization technique is formulated to minimize the sum of energy losses during charge and discharge operations.The efficiency and energy loss distribution results from the optimization routine provide a deep insight into the high voltage transformer designand its impact...
International Nuclear Information System (INIS)
Li, Ruijie; Grosu, Lavinia; Queiros-Conde, Diogo
2016-01-01
Highlights: • A gamma Stirling engine has been optimized using FPDT method by multi-objective criteria. • Genetic algorithm and decision making methods were used to get Pareto frontier and optimum points. • It shows: total thermal conductance, hot temperature, stroke and diameter ratios can be improved. - Abstract: In this paper, a solar energy powered gamma type SE has been optimized using Finite Physical Dimensions Thermodynamics (FPDT) method by multi-objective criteria. Genetic algorithm was used to get the Pareto frontier, and optimum points were obtained using the decision making methods of LINMAP and TOPSIS. The optimization results have been compared with those obtained using the ecological method. It was shown that the multi-objective optimization in this paper has a better balance among the optimizing criteria (maximum mechanical power, maximum thermal efficiency and minimum entropy generation flow). The effects of the hot source temperature and the total thermal conductance of the engine on the Pareto frontier have been also studied. This sensibility study shows that an increase in the hot reservoir temperature can increase the output mechanical power, the thermal efficiency of the engine, but also the entropy generation rate. In addition to this, an increase of the total thermal conductance of the engine can strongly increase the output mechanical power and only slightly increase the thermal efficiency. These results allow us to improve the engine performance after some modifications as geometrical dimensions (diameter, stroke, heat exchange surface, etc.) and physical parameters (temperature, thermal conductivity).
Model-Based Energy Efficiency Optimization of a Low-Temperature Adsorption Dryer
Atuonwu, J.C.; Straten, G. van; Deventer, H.C. van; Boxtel, A.J.B. van
2011-01-01
Low-temperature drying is important for heat-sensitive products, but at these temperatures conventional convective dryers have low energy efficiencies. To overcome this challenge, an energy efficiency optimization procedure is applied to a zeolite adsorption dryer subject to product quality. The
Haseli, Y.
2013-01-01
The idea is to find out whether 2nd law efficiency optimization may be a suitable trade-off between maximum work output and maximum 1st law efficiency designs for a regenerative gas turbine engine operating on the basis of an open Brayton cycle. The primary emphasis is placed on analyzing the ideal
FUZZY-LOGIC-BASED CONTROLLERS FOR EFFICIENCY OPTIMIZATION OF INVERTER-FED INDUCTION MOTOR DRIVES
This paper describes a fuzzy-logic-based energy optimizing controller to improve the efficiency of induction motor/drives operating at various load (torque) and speed conditions. Improvement of induction motor efficiency is important not only from the considerations of energy sav...
New sensorless, efficient optimized and stabilized v/f control for pmsm machines
Jafari, Seyed Hesam
With the rapid advances in power electronics and motor drive technologies in recent decades, permanent magnet synchronous machines (PMSM) have found extensive applications in a variety of industrial systems due to its many desirable features such as high power density, high efficiency, and high torque to current ratio, low noise, and robustness. In low dynamic applications like pumps, fans and compressors where the motor speed is nearly constant, usage of a simple control algorithm that can be implemented with least number of the costly external hardware can be highly desirable for industry. In recent published works, for low power PMSMs, a new sensorless volts-per-hertz (V/f) controlling method has been proposed which can be used for PMSM drive applications where the motor speed is constant. Moreover, to minimize the cost of motor implementation, the expensive rotor damper winding was eliminated. By removing the damper winding, however, instability problems normally occur inside of the motor which in some cases can be harmful for a PMSM drive. As a result, to address the instability issue, a stabilizing loop was developed and added to the conventional V/f. By further studying the proposed sensorless stabilized V/f, and calculating power loss, it became known that overall motor efficiency still is needed to be improved and optimized. This thesis suggests a new V/f control method for PMSMs, where both efficiency and stability problems are addressed. Also, although in nearly all recent related research, methods have been applied to low power PMSM, for the first time, in this thesis, the suggested method is implemented for a medium power 15 kW PMSM. A C2000 F2833x Digital Signal Processor (DSP) is used as controller part for the student custom built PMSM drive, but instead of programming the DSP in Assembly or C, the main control algorithm was developed in a rapid prototype software environment which here Matlab Simulink embedded code library is used.
Zeng, Xueqiang; Luo, Gang
2017-12-01
Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.
Directory of Open Access Journals (Sweden)
Sie Long Kek
2015-01-01
Full Text Available A computational approach is proposed for solving the discrete time nonlinear stochastic optimal control problem. Our aim is to obtain the optimal output solution of the original optimal control problem through solving the simplified model-based optimal control problem iteratively. In our approach, the adjusted parameters are introduced into the model used such that the differences between the real system and the model used can be computed. Particularly, system optimization and parameter estimation are integrated interactively. On the other hand, the output is measured from the real plant and is fed back into the parameter estimation problem to establish a matching scheme. During the calculation procedure, the iterative solution is updated in order to approximate the true optimal solution of the original optimal control problem despite model-reality differences. For illustration, a wastewater treatment problem is studied and the results show the efficiency of the approach proposed.
International Nuclear Information System (INIS)
Kamalzare, Mahmoud; Johnson, Erik A; Wojtkiewicz, Steven F
2014-01-01
Designing control strategies for smart structures, such as those with semiactive devices, is complicated by the nonlinear nature of the feedback control, secondary clipping control and other additional requirements such as device saturation. The usual design approach resorts to large-scale simulation parameter studies that are computationally expensive. The authors have previously developed an approach for state-feedback semiactive clipped-optimal control design, based on a nonlinear Volterra integral equation that provides for the computationally efficient simulation of such systems. This paper expands the applicability of the approach by demonstrating that it can also be adapted to accommodate more realistic cases when, instead of full state feedback, only a limited set of noisy response measurements is available to the controller. This extension requires incorporating a Kalman filter (KF) estimator, which is linear, into the nominal model of the uncontrolled system. The efficacy of the approach is demonstrated by a numerical study of a 100-degree-of-freedom frame model, excited by a filtered Gaussian random excitation, with noisy acceleration sensor measurements to determine the semiactive control commands. The results show that the proposed method can improve computational efficiency by more than two orders of magnitude relative to a conventional solver, while retaining a comparable level of accuracy. Further, the proposed approach is shown to be similarly efficient for an extensive Monte Carlo simulation to evaluate the effects of sensor noise levels and KF tuning on the accuracy of the response. (paper)
A genetic algorithm applied to a PWR turbine extraction optimization to increase cycle efficiency
International Nuclear Information System (INIS)
Sacco, Wagner F.; Schirru, Roberto
2002-01-01
In nuclear power plants feedwater heaters are used to heat feedwater from its temperature leaving the condenser to final feedwater temperature using steam extracted from various stages of the turbines. The purpose of this process is to increase cycle efficiency. The determination of the optimal fraction of mass flow rate to be extracted from each stage of the turbines is a complex optimization problem. This kind of problem has been efficiently solved by means of evolutionary computation techniques, such as Genetic Algorithms (GAs). GAs, which are systems based upon principles from biological genetics, have been successfully applied to several combinatorial optimization problems in nuclear engineering, as the nuclear fuel reload optimization problem. We introduce the use of GAs in cycle efficiency optimization by finding an optimal combination of turbine extractions. In order to demonstrate the effectiveness of our approach, we have chosen a typical PWR as case study. The secondary side of the PWR was simulated using PEPSE, which is a modeling tool used to perform integrated heat balances for power plants. The results indicate that the GA is a quite promising tool for cycle efficiency optimization. (author)
National Aeronautics and Space Administration — SynGenics Corporation proposes a program that unites mathematical and statistical processes, Response Surface Methodology, and multicriterial optimization methods to...
Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.
Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V
2016-01-01
Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.
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.
Wei, Xiuyan; Song, Xinyue; Dong, Dong; Keyhani, Nemat O; Yao, Lindan; Zang, Xiangyun; Dong, Lili; Gu, Zijian; Fu, Delai; Liu, Xingzhong; Qiu, Junzhi; Guan, Xiong
2016-07-01
The insect pathogenic fungus Aschersonia placenta is a highly effective pathogen of whiteflies and scale insects. However, few genetic tools are currently available for studying this organism. Here we report on the conditions for the production of transformable A. placenta protoplasts using an optimized protocol based on the response surface method (RSM). Critical parameters for protoplast production were modelled by using a Box-Behnken design (BBD) involving 3 levels of 3 variables that was subsequently tested to verify its ability to predict protoplast production (R(2) = 0.9465). The optimized conditions resulted in the highest yield of protoplasts ((4.41 ± 0.02) × 10(7) cells/mL of culture, mean ± SE) when fungal cells were treated with 26.1 mg/mL of lywallzyme for 4 h of digestion, and subsequently allowed to recover for 64.6 h in 0.7 mol/L NaCl-Tris buffer. The latter was used as an osmotic stabilizer. The yield of protoplasts was approximately 10-fold higher than that of the nonoptimized conditions. Generated protoplasts were transformed with vector PbarGPE containing the bar gene as the selection marker. Transformation efficiency was 300 colonies/(μg DNA·10(7) protoplasts), and integration of the vector DNA was confirmed by PCR. The results show that rational design strategies (RSM and BBD methods) are useful to increase the production of fungal protoplasts for a variety of downstream applications.
DEFF Research Database (Denmark)
Li, Qingnan; Andersen, Michael A. E.; Thomsen, Ole Cornelius
2011-01-01
Nowadays, efficiency and power density are the most important issues for Power Factor Correction (PFC) converters development. However, it is a challenge to reach both high efficiency and power density in a system at the same time. In this paper, taking a Bridgeless PFC (BPFC) as an example......, a useful compromise between efficiency and power density of the Boost inductors on 3.2kW is achieved using an optimized design procedure. The experimental verifications based on the optimized inductor are carried out from 300W to 3.2kW at 220Vac input....
Optimization of large-scale industrial systems : an emerging method
Energy Technology Data Exchange (ETDEWEB)
Hammache, A.; Aube, F.; Benali, M.; Cantave, R. [Natural Resources Canada, Varennes, PQ (Canada). CANMET Energy Technology Centre
2006-07-01
This paper reviewed optimization methods of large-scale industrial production systems and presented a novel systematic multi-objective and multi-scale optimization methodology. The methodology was based on a combined local optimality search with global optimality determination, and advanced system decomposition and constraint handling. The proposed method focused on the simultaneous optimization of the energy, economy and ecology aspects of industrial systems (E{sup 3}-ISO). The aim of the methodology was to provide guidelines for decision-making strategies. The approach was based on evolutionary algorithms (EA) with specifications including hybridization of global optimality determination with a local optimality search; a self-adaptive algorithm to account for the dynamic changes of operating parameters and design variables occurring during the optimization process; interactive optimization; advanced constraint handling and decomposition strategy; and object-oriented programming and parallelization techniques. Flowcharts of the working principles of the basic EA were presented. It was concluded that the EA uses a novel decomposition and constraint handling technique to enhance the Pareto solution search procedure for multi-objective problems. 6 refs., 9 figs.
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 SIGNAL PROCESSING METHODS IN GPR
Directory of Open Access Journals (Sweden)
Saeid Karamzadeh
2014-01-01
Full Text Available In the past three decades, a lot of various applications of Ground Penetrating Radar (GPR took place in real life. There are important challenges of this radar in civil applications and also in military applications. In this paper, the fundamentals of GPR systems will be covered and three important signal processing methods (Wavelet Transform, Matched Filter and Hilbert Huang will be compared to each other in order to get most accurate information about objects which are in subsurface or behind the wall.
Optimization Methods for Supply Chain Activities
Directory of Open Access Journals (Sweden)
Balasescu S.
2014-12-01
Full Text Available This paper approach the theme of supply chain activities for medium and large companies which run many operations and need many facilities. The first goal is to analyse the influence of optimisation methods of supply chain activities on the success rate for a business. The second goal is to compare some logistic strategies applied by companies with the same profile to see which is the most effective. The final goal is to show which is the necessity of strategic optimum for a company and how can be achieved the considering the demand uncertainty.
Application of improved AHP method to radiation protection optimization
International Nuclear Information System (INIS)
Wang Chuan; Zhang Jianguo; Yu Lei
2014-01-01
Aimed at the deficiency of traditional AHP method, a hierarchy model for optimum project selection of radiation protection was established with the improved AHP method. The result of comparison between the improved AHP method and the traditional AHP method shows that the improved AHP method can reduce personal judgment subjectivity, and its calculation process is compact and reasonable. The improved AHP method can provide scientific basis for radiation protection optimization. (authors)
Proposal of Evolutionary Simplex Method for Global Optimization Problem
Shimizu, Yoshiaki
To make an agile decision in a rational manner, role of optimization engineering has been notified increasingly under diversified customer demand. With this point of view, in this paper, we have proposed a new evolutionary method serving as an optimization technique in the paradigm of optimization engineering. The developed method has prospects to solve globally various complicated problem appearing in real world applications. It is evolved from the conventional method known as Nelder and Mead’s Simplex method by virtue of idea borrowed from recent meta-heuristic method such as PSO. Mentioning an algorithm to handle linear inequality constraints effectively, we have validated effectiveness of the proposed method through comparison with other methods using several benchmark problems.
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
A dynamic lattice searching method with rotation operation for optimization of large clusters
International Nuclear Information System (INIS)
Wu Xia; Cai Wensheng; Shao Xueguang
2009-01-01
Global optimization of large clusters has been a difficult task, though much effort has been paid and many efficient methods have been proposed. During our works, a rotation operation (RO) is designed to realize the structural transformation from decahedra to icosahedra for the optimization of large clusters, by rotating the atoms below the center atom with a definite degree around the fivefold axis. Based on the RO, a development of the previous dynamic lattice searching with constructed core (DLSc), named as DLSc-RO, is presented. With an investigation of the method for the optimization of Lennard-Jones (LJ) clusters, i.e., LJ 500 , LJ 561 , LJ 600 , LJ 665-667 , LJ 670 , LJ 685 , and LJ 923 , Morse clusters, silver clusters by Gupta potential, and aluminum clusters by NP-B potential, it was found that both the global minima with icosahedral and decahedral motifs can be obtained, and the method is proved to be efficient and universal.
Xu, Zheng; Wang, Sheng; Li, Yeqing; Zhu, Feiyun; Huang, Junzhou
2018-02-08
The most recent history of parallel Magnetic Resonance Imaging (pMRI) has in large part been devoted to finding ways to reduce acquisition time. While joint total variation (JTV) regularized model has been demonstrated as a powerful tool in increasing sampling speed for pMRI, however, the major bottleneck is the inefficiency of the optimization method. While all present state-of-the-art optimizations for the JTV model could only reach a sublinear convergence rate, in this paper, we squeeze the performance by proposing a linear-convergent optimization method for the JTV model. The proposed method is based on the Iterative Reweighted Least Squares algorithm. Due to the complexity of the tangled JTV objective, we design a novel preconditioner to further accelerate the proposed method. Extensive experiments demonstrate the superior performance of the proposed algorithm for pMRI regarding both accuracy and efficiency compared with state-of-the-art methods.
Research on optimization of combustion efficiency of thermal power unit based on genetic algorithm
Zhou, Qiongyang
2018-04-01
In order to improve the economic performance and reduce pollutant emissions of thermal power units, the characteristics of neural network in establishing boiler combustion model are analyzed based on the analysis of the main factors affecting boiler efficiency by using orthogonal method. In addition, on the basis of this model, the genetic algorithm is used to find the best control amount of the furnace combustion in a certain working condition. Through the genetic algorithm based on real number encoding and roulette selection is concluded: the best control quantity at a condition of furnace combustion can be combined with the boiler combustion system model for neural network training. The precision of the neural network model is further improved, and the basic work is laid for the research of the whole boiler combustion optimization system.
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...
Distributed optimization for systems design : an augmented Lagrangian coordination method
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
Game-Theoretic Rate-Distortion-Complexity Optimization of High Efficiency Video Coding
DEFF Research Database (Denmark)
Ukhanova, Ann; Milani, Simone; Forchhammer, Søren
2013-01-01
profiles in order to tailor the computational load to the different hardware and power-supply resources of devices. In this work, we focus on optimizing the quantization parameter and partition depth in HEVC via a game-theoretic approach. The proposed rate control strategy alone provides 0.2 dB improvement......This paper presents an algorithm for rate-distortioncomplexity optimization for the emerging High Efficiency Video Coding (HEVC) standard, whose high computational requirements urge the need for low-complexity optimization algorithms. Optimization approaches need to specify different complexity...
Optimal PMU Placement with Uncertainty Using Pareto Method
Directory of Open Access Journals (Sweden)
A. Ketabi
2012-01-01
Full Text Available This paper proposes a method for optimal placement of Phasor Measurement Units (PMUs in state estimation considering uncertainty. State estimation has first been turned into an optimization exercise in which the objective function is selected to be the number of unobservable buses which is determined based on Singular Value Decomposition (SVD. For the normal condition, Differential Evolution (DE algorithm is used to find the optimal placement of PMUs. By considering uncertainty, a multiobjective optimization exercise is hence formulated. To achieve this, DE algorithm based on Pareto optimum method has been proposed here. The suggested strategy is applied on the IEEE 30-bus test system in several case studies to evaluate the optimal PMUs placement.
Directory of Open Access Journals (Sweden)
A. P. Karpenko
2014-01-01
Full Text Available We consider a class of stochastic search algorithms of global optimization which in various publications are called behavioural, intellectual, metaheuristic, inspired by the nature, swarm, multi-agent, population, etc. We use the last term.Experience in using the population algorithms to solve challenges of global optimization shows that application of one such algorithm may not always effective. Therefore now great attention is paid to hybridization of population algorithms of global optimization. Hybrid algorithms unite various algorithms or identical algorithms, but with various values of free parameters. Thus efficiency of one algorithm can compensate weakness of another.The purposes of the work are development of hybrid algorithm of global optimization based on known algorithms of harmony search (HS and swarm of particles (PSO, software implementation of algorithm, study of its efficiency using a number of known benchmark problems, and a problem of dimensional optimization of truss structure.We set a problem of global optimization, consider basic algorithms of HS and PSO, give a flow chart of the offered hybrid algorithm called PSO HS , present results of computing experiments with developed algorithm and software, formulate main results of work and prospects of its development.
A loading pattern optimization method for nuclear fuel management
International Nuclear Information System (INIS)
Argaud, J.P.
1997-01-01
Nuclear fuel reload of PWR core leads to the search of an optimal nuclear fuel assemblies distribution, namely of loading pattern. This large discrete optimization problem is here expressed as a cost function minimization. To deal with this problem, an approach based on gradient information is used to direct the search in the patterns discrete space. A method using an adjoint state formulation is then developed, and final results of complete patterns search tests by this method are presented. (author)
An Evaluation of the Efficiency of Different Hygienisation Methods
Zrubková, M.
2017-10-01
The aim of this study is to evaluate the efficiency of hygienisation by pasteurisation, temperature-phased anaerobic digestion and sludge liming. A summary of the legislation concerning sludge treatment, disposal and recycling is included. The hygienisation methods are compared not only in terms of hygienisation efficiency but a comparison of other criteria is also included.
Directory of Open Access Journals (Sweden)
Yukai Yao
2015-01-01
Full Text Available We propose an optimized Support Vector Machine classifier, named PMSVM, in which System Normalization, PCA, and Multilevel Grid Search methods are comprehensively considered for data preprocessing and parameters optimization, respectively. The main goals of this study are to improve the classification efficiency and accuracy of SVM. Sensitivity, Specificity, Precision, and ROC curve, and so forth, are adopted to appraise the performances of PMSVM. Experimental results show that PMSVM has relatively better accuracy and remarkable higher efficiency compared with traditional SVM algorithms.
Comparison of optimal design methods in inverse problems
International Nuclear Information System (INIS)
Banks, H T; Holm, K; Kappel, F
2011-01-01
Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst–Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667–77; De Gaetano A and Arino O 2000 J. Math. Biol. 40 136–68; Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979–90)
Comparison of optimal design methods in inverse problems
Banks, H. T.; Holm, K.; Kappel, F.
2011-07-01
Typical optimal design methods for inverse or parameter estimation problems are designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates. It is hoped that the inverse problem will produce parameter estimates with increased accuracy using data collected according to the optimal sampling distribution. Here we formulate the classical optimal design problem in the context of general optimization problems over distributions of sampling times. We present a new Prohorov metric-based theoretical framework that permits one to treat succinctly and rigorously any optimal design criteria based on the Fisher information matrix. A fundamental approximation theory is also included in this framework. A new optimal design, SE-optimal design (standard error optimal design), is then introduced in the context of this framework. We compare this new design criterion with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; the standard errors for parameters are computed using asymptotic theory or bootstrapping and the optimal mesh. We use three examples to illustrate ideas: the Verhulst-Pearl logistic population model (Banks H T and Tran H T 2009 Mathematical and Experimental Modeling of Physical and Biological Processes (Boca Raton, FL: Chapman and Hall/CRC)), the standard harmonic oscillator model (Banks H T and Tran H T 2009) and a popular glucose regulation model (Bergman R N, Ider Y Z, Bowden C R and Cobelli C 1979 Am. J. Physiol. 236 E667-77 De Gaetano A and Arino O 2000 J. Math. Biol. 40 136-68 Toffolo G, Bergman R N, Finegood D T, Bowden C R and Cobelli C 1980 Diabetes 29 979-90).
International Nuclear Information System (INIS)
Gimelli, A.; Luongo, A.; Muccillo, M.
2017-01-01
Highlights: • Multi-objective optimization method for ORC design has been addressed. • Trade-off between electric efficiency and overall heat exchangers area is evaluated. • The heat exchangers area was used as objective function to minimize the plant cost. • MDM was considered as organic working fluid for the thermodynamic cycle. • Electric efficiency: 14.1–18.9%. Overall heat exchangers area: 446–1079 m 2 . - Abstract: Multi-objective optimization could be, in the industrial sector, a fundamental strategic approach for defining the target design specifications and operating parameters of new competitive products for the market, especially in renewable energy and energy savings fields. Vector optimization mostly enabled the determination of a set of optimal solutions characterized by different costs, sizes, efficiencies and other key features. The designer can subsequently select the solution with the best compromise between the objective functions for the specific application and constraints. In this paper, a multi-objective optimization problem addressing an Organic Rankine Cycle system is solved with consideration for the electric efficiency and overall heat exchangers area as quantities that should be optimized. In fact, considering that the overall capital cost of the ORC system is dominated by the cost of the heat exchangers rather than that of the pump and turbine, this area is related to the cost of the plant and so it was used to indirectly optimize the economic system performance. For this reason, although cost data have not been used, the heat exchangers area was used as a second objective function to minimize the plant cost. Pareto optimal solutions highlighted a trade-off between the two conflicting objective functions. Octamethyltrisiloxane (MDM) was considered organic working fluid, while the following input parameters were used as decision variables: minimum and maximum pressure of the thermodynamic cycle; superheating and subcooling
Multi-objective optimization design method of radiation shielding
International Nuclear Information System (INIS)
Yang Shouhai; Wang Weijin; Lu Daogang; Chen Yixue
2012-01-01
Due to the shielding design goals of diversification and uncertain process of many factors, it is necessary to develop an optimization design method of intelligent shielding by which the shielding scheme selection will be achieved automatically and the uncertainties of human impact will be reduced. For economical feasibility to achieve a radiation shielding design for automation, the multi-objective genetic algorithm optimization of screening code which combines the genetic algorithm and discrete-ordinate method was developed to minimize the costs, size, weight, and so on. This work has some practical significance for gaining the optimization design of shielding. (authors)
A discrete optimization method for nuclear fuel management
International Nuclear Information System (INIS)
Argaud, J.P.
1993-01-01
Nuclear fuel management can be seen as a large discrete optimization problem under constraints, and optimization methods on such problems are numerically costly. After an introduction of the main aspects of nuclear fuel management, this paper presents a new way to treat the combinatorial problem by using information included in the gradient of optimized cost function. A new search process idea is to choose, by direct observation of the gradient, the more interesting changes in fuel loading patterns. An example is then developed to illustrate an operating mode of the method. Finally, connections with classical simulated annealing and genetic algorithms are described as an attempt to improve search processes. 16 refs., 2 figs
Ullah, Hakeem; Islam, Saeed; Khan, Ilyas; Shafie, Sharidan; Fiza, Mehreen
2015-01-01
In this paper we applied a new analytic approximate technique Optimal Homotopy Asymptotic Method (OHAM) for treatment of coupled differential- difference equations (DDEs). To see the efficiency and reliability of the method, we consider Relativistic Toda coupled nonlinear differential-difference equation. It provides us a convenient way to control the convergence of approximate solutions when it is compared with other methods of solution found in the literature. The obtained solutions show that OHAM is effective, simpler, easier and explicit. PMID:25874457
Ullah, Hakeem; Islam, Saeed; Khan, Ilyas; Shafie, Sharidan; Fiza, Mehreen
2015-01-01
In this paper we applied a new analytic approximate technique Optimal Homotopy Asymptotic Method (OHAM) for treatment of coupled differential-difference equations (DDEs). To see the efficiency and reliability of the method, we consider Relativistic Toda coupled nonlinear differential-difference equation. It provides us a convenient way to control the convergence of approximate solutions when it is compared with other methods of solution found in the literature. The obtained solutions show that OHAM is effective, simpler, easier and explicit.
Energy-Efficient Optimization for HARQ Schemes over Time-Correlated Fading Channels
Shi, Zheng
2018-03-19
Energy efficiency of three common hybrid automatic repeat request (HARQ) schemes including Type I HARQ, HARQ with chase combining (HARQ-CC) and HARQ with incremental redundancy (HARQ-IR), is analyzed and joint power allocation and rate selection to maximize the energy efficiency is investigated in this paper. Unlike prior literature, time-correlated fading channels is considered and two widely concerned quality of service (QoS) constraints, i.e., outage and goodput constraints, are also considered in the optimization, which further differentiates this work from prior ones. Using a unified expression of asymptotic outage probabilities, optimal transmission powers and optimal rate are derived in closed-forms to maximize the energy efficiency while satisfying the QoS constraints. These closed-form solutions then enable a thorough analysis of the maximal energy efficiencies of various HARQ schemes. It is revealed that with low outage constraint, the maximal energy efficiency achieved by Type I HARQ is
A method of segment weight optimization for intensity modulated radiation therapy
International Nuclear Information System (INIS)
Pei Xi; Cao Ruifen; Jing Jia; Cheng Mengyun; Zheng Huaqing; Li Jia; Huang Shanqing; Li Gui; Song Gang; Wang Weihua; Wu Yican; FDS Team
2011-01-01
The error caused by leaf sequencing often leads to planning of Intensity-Modulated Radiation Therapy (IMRT) arrange system couldn't meet clinical demand. The optimization approach in this paper can reduce this error and improve efficiency of plan-making effectively. Conjugate Gradient algorithm was used to optimize segment weight and readjust segment shape, which could minimize the error anterior-posterior leaf sequencing eventually. Frequent clinical cases were tasted by precise radiotherapy system, and then compared Dose-Volume histogram between target area and organ at risk as well as isodose line in computed tomography (CT) film, we found that the effect was improved significantly after optimizing segment weight. Segment weight optimizing approach based on Conjugate Gradient method can make treatment planning meet clinical request more efficiently, so that has extensive application perspective. (authors)
Local Approximation and Hierarchical Methods for Stochastic Optimization
Cheng, Bolong
In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the
Ananiev, Sergey
2006-01-01
The paper demonstrates the equivalence between the optimality criteria (OC) method, initially proposed by Bendsoe & Kikuchi for topology optimization problem, and the projected gradient method. The equivalence is shown using Hestenes definition of Lagrange multipliers. Based on this development, an alternative formulation of the Karush-Kuhn-Tucker (KKT) condition is suggested. Such reformulation has some advantages, which will be also discussed in the paper. For verification purposes the modi...
DEFF Research Database (Denmark)
Sørensen, Søren Nørgaard; Lund, Erik
2012-01-01
This work concerns a novel large-scale multi-material topology optimization method for simultaneous determination of the optimum variable integer thickness and fiber orientation throughout laminate structures with fixed outer geometries while adhering to certain manufacturing constraints....... The conceptual combinatorial/integer problem is relaxed to a continuous problem and solved on basis of the so-called Discrete Material Optimization method, explicitly including the manufacturing constraints as linear constraints....
New Efficient Fourth Order Method for Solving Nonlinear Equations
Directory of Open Access Journals (Sweden)
Farooq Ahmad
2013-12-01
Full Text Available In a paper [Appl. Math. Comput., 188 (2 (2007 1587--1591], authors have suggested and analyzed a method for solving nonlinear equations. In the present work, we modified this method by using the finite difference scheme, which has a quintic convergence. We have compared this modified Halley method with some other iterative of fifth-orders convergence methods, which shows that this new method having convergence of fourth order, is efficient.
Efficient numerical method for district heating system hydraulics
International Nuclear Information System (INIS)
Stevanovic, Vladimir D.; Prica, Sanja; Maslovaric, Blazenka; Zivkovic, Branislav; Nikodijevic, Srdjan
2007-01-01
An efficient method for numerical simulation and analyses of the steady state hydraulics of complex pipeline networks is presented. It is based on the loop model of the network and the method of square roots for solving the system of linear equations. The procedure is presented in the comprehensive mathematical form that could be straightforwardly programmed into a computer code. An application of the method to energy efficiency analyses of a real complex district heating system is demonstrated. The obtained results show a potential for electricity savings in pumps operation. It is shown that the method is considerably more effective than the standard Hardy Cross method still widely used in engineering practice. Because of the ease of implementation and high efficiency, the method presented in this paper is recommended for hydraulic steady state calculations of complex networks
An historical survey of computational methods in optimal control.
Polak, E.
1973-01-01
Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.
International Nuclear Information System (INIS)
Xu, Yun-Chao; Chen, Qun
2013-01-01
The vapor-compression refrigeration systems have been one of the essential energy conversion systems for humankind and exhausting huge amounts of energy nowadays. Surrounding the energy efficiency promotion of the systems, there are lots of effectual optimization methods but mainly relied on engineering experience and computer simulations rather than theoretical analysis due to the complex and vague physical essence. We attempt to propose a theoretical global optimization method based on in-depth physical analysis for the involved physical processes, i.e. heat transfer analysis for condenser and evaporator, through introducing the entransy theory and thermodynamic analysis for compressor and expansion valve. The integration of heat transfer and thermodynamic analyses forms the overall physical optimization model for the systems to describe the relation between all the unknown parameters and known conditions, which makes theoretical global optimization possible. With the aid of the mathematical conditional extremum solutions, an optimization equation group and the optimal configuration of all the unknown parameters are analytically obtained. Eventually, via the optimization of a typical vapor-compression refrigeration system with various working conditions to minimize the total heat transfer area of heat exchangers, the validity and superior of the newly proposed optimization method is proved. - Highlights: • A global optimization method for vapor-compression systems is proposed. • Integrating heat transfer and thermodynamic analyses forms the optimization model. • A mathematical relation between design parameters and requirements is derived. • Entransy dissipation is introduced into heat transfer analysis. • The validity of the method is proved via optimization of practical cases
International Nuclear Information System (INIS)
Kempf, Nicholas; Zhang, Yanliang
2016-01-01
Highlights: • A three-dimensional automotive thermoelectric generator (TEG) model is developed. • Heat exchanger design and TEG configuration are optimized for maximum fuel efficiency increase. • Heat exchanger conductivity has a strong influence on maximum fuel efficiency increase. • TEG aspect ratio and fin height increase with heat exchanger thermal conductivity. • A 2.5% fuel efficiency increase is attainable with nanostructured half-Heusler modules. - Abstract: Automotive fuel efficiency can be increased by thermoelectric power generation using exhaust waste heat. A high-temperature thermoelectric generator (TEG) that converts engine exhaust waste heat into electricity is simulated based on a light-duty passenger vehicle with a 4-cylinder gasoline engine. Strategies to optimize TEG configuration and heat exchanger design for maximum fuel efficiency improvement are provided. Through comparison of stainless steel and silicon carbide heat exchangers, it is found that both the optimal TEG design and the maximum fuel efficiency increase are highly dependent on the thermal conductivity of the heat exchanger material. Significantly higher fuel efficiency increase can be obtained using silicon carbide heat exchangers at taller fins and a longer TEG along the exhaust flow direction when compared to stainless steel heat exchangers. Accounting for major parasitic losses, a maximum fuel efficiency increase of 2.5% is achievable using newly developed nanostructured bulk half-Heusler thermoelectric modules.
Method for calculating annual energy efficiency improvement of TV sets
International Nuclear Information System (INIS)
Varman, M.; Mahlia, T.M.I.; Masjuki, H.H.
2006-01-01
The popularization of 24 h pay-TV, interactive video games, web-TV, VCD and DVD are poised to have a large impact on overall TV electricity consumption in the Malaysia. Following this increased consumption, energy efficiency standard present a highly effective measure for decreasing electricity consumption in the residential sector. The main problem in setting energy efficiency standard is identifying annual efficiency improvement, due to the lack of time series statistical data available in developing countries. This study attempts to present a method of calculating annual energy efficiency improvement for TV set, which can be used for implementing energy efficiency standard for TV sets in Malaysia and other developing countries. Although the presented result is only an approximation, definitely it is one of the ways of accomplishing energy standard. Furthermore, the method can be used for other appliances without any major modification
Method for calculating annual energy efficiency improvement of TV sets
Energy Technology Data Exchange (ETDEWEB)
Varman, M. [Department of Mechanical Engineering, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur (Malaysia); Mahlia, T.M.I. [Department of Mechanical Engineering, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur (Malaysia)]. E-mail: indra@um.edu.my; Masjuki, H.H. [Department of Mechanical Engineering, University of Malaya, Lembah Pantai, 50603 Kuala Lumpur (Malaysia)
2006-10-15
The popularization of 24 h pay-TV, interactive video games, web-TV, VCD and DVD are poised to have a large impact on overall TV electricity consumption in the Malaysia. Following this increased consumption, energy efficiency standard present a highly effective measure for decreasing electricity consumption in the residential sector. The main problem in setting energy efficiency standard is identifying annual efficiency improvement, due to the lack of time series statistical data available in developing countries. This study attempts to present a method of calculating annual energy efficiency improvement for TV set, which can be used for implementing energy efficiency standard for TV sets in Malaysia and other developing countries. Although the presented result is only an approximation, definitely it is one of the ways of accomplishing energy standard. Furthermore, the method can be used for other appliances without any major modification.
Optimized Audio Classification and Segmentation Algorithm by Using Ensemble Methods
Directory of Open Access Journals (Sweden)
Saadia Zahid
2015-01-01
Full Text Available Audio segmentation is a basis for multimedia content analysis which is the most important and widely used application nowadays. An optimized audio classification and segmentation algorithm is presented in this paper that segments a superimposed audio stream on the basis of its content into four main audio types: pure-speech, music, environment sound, and silence. An algorithm is proposed that preserves important audio content and reduces the misclassification rate without using large amount of training data, which handles noise and is suitable for use for real-time applications. Noise in an audio stream is segmented out as environment sound. A hybrid classification approach is used, bagged support vector machines (SVMs with artificial neural networks (ANNs. Audio stream is classified, firstly, into speech and nonspeech segment by using bagged support vector machines; nonspeech segment is further classified into music and environment sound by using artificial neural networks and lastly, speech segment is classified into silence and pure-speech segments on the basis of rule-based classifier. Minimum data is used for training classifier; ensemble methods are used for minimizing misclassification rate and approximately 98% accurate segments are obtained. A fast and efficient algorithm is designed that can be used with real-time multimedia applications.
Energy Technology Data Exchange (ETDEWEB)
Tung, Wu-Hsiung, E-mail: wstong@iner.gov.tw; Lee, Tien-Tso; Kuo, Weng-Sheng; Yaur, Shung-Jung
2017-03-15
objective function evaluation (OFV) in the exhausted search is 8707, and the number of OFV in the search using the optimization method is 41. The reduction in OFV shows the efficiency of the optimization method. The optimization designs with more than 4 enriched axial segments were also performed to see if better objective function values can be achieved by having more axial segments.
GLOBAL OPTIMIZATION METHODS FOR GRAVITATIONAL LENS SYSTEMS WITH REGULARIZED SOURCES
International Nuclear Information System (INIS)
Rogers, Adam; Fiege, Jason D.
2012-01-01
Several approaches exist to model gravitational lens systems. In this study, we apply global optimization methods to find the optimal set of lens parameters using a genetic algorithm. We treat the full optimization procedure as a two-step process: an analytical description of the source plane intensity distribution is used to find an initial approximation to the optimal lens parameters; the second stage of the optimization uses a pixelated source plane with the semilinear method to determine an optimal source. Regularization is handled by means of an iterative method and the generalized cross validation (GCV) and unbiased predictive risk estimator (UPRE) functions that are commonly used in standard image deconvolution problems. This approach simultaneously estimates the optimal regularization parameter and the number of degrees of freedom in the source. Using the GCV and UPRE functions, we are able to justify an estimation of the number of source degrees of freedom found in previous work. We test our approach by applying our code to a subset of the lens systems included in the SLACS survey.
Review: Optimization methods for groundwater modeling and management
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.