Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things

Directory of Open Access Journals (Sweden)

Kaiqi Ding

2017-10-01

Full Text Available In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT. Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii the network can rapidly converge to a collision-free transmission through each node’s learning ability in the process of the distributed channel allocation; and (iii the network throughput is further improved via the dynamic time slot optimization.

Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things.

Science.gov (United States)

Ding, Kaiqi; Zhao, Haitao; Hu, Xiping; Wei, Jibo

2017-10-28

In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node's learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.

Coupling slots without shunt impedance drop

International Nuclear Information System (INIS)

Balleyguier, P.

1996-01-01

It is well known that coupling slots between adjacent cells in a π-mode structure reduce shunt impedance per unit length with respect to single cell cavities. To design optimized coupling slots, one has to answer the following question: for a given coupling factor, what shape, dimension, position and number of slots lead to the lowest shunt impedance drop? A numerical study using the 3D code MAFIA has been carried out. The aim was to design the 352 MHz cavities for the high intensity proton accelerator of the TRISPAL project. The result is an unexpected set of four 'petal' slots. Such slots should lead to a quasi-negligible drop in shunt impedance: about -1% on average, for particle velocity from 0.4 c to 0.8 c. (author)

Slot Antenna for Wireless Temperature Measurement Systems

DEFF Research Database (Denmark)

Acar, Öncel; Jakobsen, Kaj Bjarne

2016-01-01

This paper presents a novel clover-slot antenna for a surface-acoustic-wave sensor based wireless temperature measurement system. The slot is described by a parametric locus curve that has the shape of a clover. The antenna is operated at high temperatures, in rough environments, and has a 43......% fractional bandwidth at the 2.4 GHz ISM-band. The slot antenna has been optimized for excitation by a passive chip soldered onto it. Measurement results are compared with simulation results and show good agreements....

Effects of geometry on slot-jet film cooling performance

Energy Technology Data Exchange (ETDEWEB)

Hyams, D.G.; McGovern, K.T.; Leylek, J.H. [Clemson Univ., SC (United States)

1995-10-01

The physics of the film cooling process for shaped, inclined slot-jets with realistic slot-length-to-width ratios (L/s) is studied for a range of blowing ratio (M) and density ratio (DR) parameters typical of gas turbine operations. For the first time in the open literature, the effect of inlet and exit shaping of the slot-jet on both flow and thermal field characteristics is isolated, and the dominant mechanisms responsible for differences in these characteristics are documented. A previously documented computational methodology was applied for the study of four distinct configurations: (1) slot with straight edges and sharp corners (reference case); (2) slot with shaped inlet region; (3) slot with shaped exit region; and (4) slot with both shaped inlet and exit regions. Detailed field results as well as surface phenomena involving adiabatic film effectiveness ({eta}) and heat transfer coefficient (h) are presented. It is demonstrated that both {eta} and h results are vital in the proper assessment of film cooling performance. All simulations were carried out using a multi-block, unstructured/adaptive grid, fully explicit, time-marching solver with multi-grid, local time stepping, and residual smoothing type acceleration techniques. Special attention was paid to and full documentation provided for: (1) proper modeling of the physical phenomena; (2) exact geometry and high quality grid generation techniques; (3) discretization schemes; and (4) turbulence modeling issues. The key parameters M and DR were varied from 1.0 to 2.0 and 1.5 to 2.0, respectively, to show their influence. Simulations were repeated for slot length-to-width ratio (L/s) of 3.0 and 4.5 in order to explain the effects of this important parameter. Additionally, the performance of two popular turbulence models, standard k-F, and RNG k-E, were studied to establish their ability to handle highly elliptic jet/crossflow interaction type processes.

A multi-slot surface coil for MRI of dual-rat imaging at 4 T

International Nuclear Information System (INIS)

Solis, S E; Rodriguez, A O; Wang, R; Tomasi, D

2011-01-01

A slotted surface coil inspired by the hole-and-slot cavity magnetron was developed for magnetic resonance imaging of obese rats at 4 T. Full-wave analysis of the magnetic field was carried out at 170 MHz for both the slotted and circular-shaped coils. The noise figure values of two coils were investigated via the numerical calculation of the quality factors. Fat simulated phantoms to mimic overweight rats were included in the analysis with weights ranging from 300 to 900 g. The noise figures were 1.2 dB for the slotted coil and 2.4 dB for the circular coil when loaded with 600 g of simulated phantom. A slotted surface coil with eight circular slots and a circular coil with similar dimensions were built and operated in the transceiver mode, and their performances were experimentally compared. The imaging tests in phantoms demonstrated that the slotted surface coil has a deeper RF-sensitivity and better field uniformity than the single-loop RF-coil. High quality images of two overweight Zucker rats were acquired simultaneously with the slotted surface coil using standard spin-echo pulse sequences. Experimental results showed that the slotted surface coil outperformed the circular coil for imaging considerably overweight rats. Thus, the slotted surface coil can be a good tool for MRI experiments in rats on a human whole-body 4 T scanner.

A multi-slot surface coil for MRI of dual-rat imaging at 4T

Energy Technology Data Exchange (ETDEWEB)

Solis, S.E.; Tomasi, D.; Solis, S.E.; Wang, R.; Tomasi, D.; Rodriguez, A.O.

2011-07-01

A slotted surface coil inspired by the hole-and-slot cavity magnetron was developed for magnetic resonance imaging of obese rats at 4 T. Full-wave analysis of the magnetic field was carried out at 170 MHz for both the slotted and circular-shaped coils. The noise figure values of two coils were investigated via the numerical calculation of the quality factors. Fat simulated phantoms to mimic overweight rats were included in the analysis with weights ranging from 300 to 900 g. The noise figures were 1.2 dB for the slotted coil and 2.4 dB for the circular coil when loaded with 600 g of simulated phantom. A slotted surface coil with eight circular slots and a circular coil with similar dimensions were built and operated in the transceiver mode, and their performances were experimentally compared. The imaging tests in phantoms demonstrated that the slotted surface coil has a deeper RF-sensitivity and better field uniformity than the single-loop RF-coil. High quality images of two overweight Zucker rats were acquired simultaneously with the slotted surface coil using standard spin-echo pulse sequences. Experimental results showed that the slotted surface coil outperformed the circular coil for imaging considerably overweight rats. Thus, the slotted surface coil can be a good tool for MRI experiments in rats on a human whole-body 4 T scanner.

A multi-slot surface coil for MRI of dual-rat imaging at 4 T

Energy Technology Data Exchange (ETDEWEB)

Solis, S E; Rodriguez, A O [Departamento de Ingenieria Electrica, Universidad Autonoma Metropolitana Iztapalapa, Mexico, DF 09340 (Mexico); Wang, R; Tomasi, D, E-mail: arog@xanum.uam.mx [Medical Department, Brookhaven National Laboratory, Upton, NY 11973 (United States)

2011-06-21

A slotted surface coil inspired by the hole-and-slot cavity magnetron was developed for magnetic resonance imaging of obese rats at 4 T. Full-wave analysis of the magnetic field was carried out at 170 MHz for both the slotted and circular-shaped coils. The noise figure values of two coils were investigated via the numerical calculation of the quality factors. Fat simulated phantoms to mimic overweight rats were included in the analysis with weights ranging from 300 to 900 g. The noise figures were 1.2 dB for the slotted coil and 2.4 dB for the circular coil when loaded with 600 g of simulated phantom. A slotted surface coil with eight circular slots and a circular coil with similar dimensions were built and operated in the transceiver mode, and their performances were experimentally compared. The imaging tests in phantoms demonstrated that the slotted surface coil has a deeper RF-sensitivity and better field uniformity than the single-loop RF-coil. High quality images of two overweight Zucker rats were acquired simultaneously with the slotted surface coil using standard spin-echo pulse sequences. Experimental results showed that the slotted surface coil outperformed the circular coil for imaging considerably overweight rats. Thus, the slotted surface coil can be a good tool for MRI experiments in rats on a human whole-body 4 T scanner.

Design of Ultra-Wideband Tapered Slot Antenna by Using Binomial Transformer with Corrugation

Science.gov (United States)

Chareonsiri, Yosita; Thaiwirot, Wanwisa; Akkaraekthalin, Prayoot

2017-05-01

In this paper, the tapered slot antenna (TSA) with corrugation is proposed for UWB applications. The multi-section binomial transformer is used to design taper profile of the proposed TSA that does not involve using time consuming optimization. A step-by-step procedure for synthesis of the step impedance values related with step slot widths of taper profile is presented. The smooth taper can be achieved by fitting the smoothing curve to the entire step slot. The design of TSA based on this method yields results with a quite flat gain and wide impedance bandwidth covering UWB spectrum from 3.1 GHz to 10.6 GHz. To further improve the radiation characteristics, the corrugation is added on the both edges of the proposed TSA. The effects of different corrugation shapes on the improvement of antenna gain and front-to-back ratio (F-to-B ratio) are investigated. To demonstrate the validity of the design, the prototypes of TSA without and with corrugation are fabricated and measured. The results show good agreement between simulation and measurement.

Congestion Pricing for Aircraft Pushback Slot Allocation

Science.gov (United States)

Zhang, Yaping

2017-01-01

In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the “external cost of surface congestion” is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm. PMID:28114429

Congestion Pricing for Aircraft Pushback Slot Allocation.

Science.gov (United States)

Liu, Lihua; Zhang, Yaping; Liu, Lan; Xing, Zhiwei

2017-01-01

In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the "external cost of surface congestion" is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.

Congestion Pricing for Aircraft Pushback Slot Allocation.

Directory of Open Access Journals (Sweden)

Lihua Liu

Full Text Available In order to optimize aircraft pushback management during rush hour, aircraft pushback slot allocation based on congestion pricing is explored while considering monetary compensation based on the quality of the surface operations. First, the concept of the "external cost of surface congestion" is proposed, and a quantitative study on the external cost is performed. Then, an aircraft pushback slot allocation model for minimizing the total surface cost is established. An improved discrete differential evolution algorithm is also designed. Finally, a simulation is performed on Xinzheng International Airport using the proposed model. By comparing the pushback slot control strategy based on congestion pricing with other strategies, the advantages of the proposed model and algorithm are highlighted. In addition to reducing delays and optimizing the delay distribution, the model and algorithm are better suited for use for actual aircraft pushback management during rush hour. Further, it is also observed they do not result in significant increases in the surface cost. These results confirm the effectiveness and suitability of the proposed model and algorithm.

Non-convex multi-objective optimization

CERN Document Server

Pardalos, Panos M; Žilinskas, Julius

2017-01-01

Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions. Multi-objective optimization methods facilitate designers, engineers, and researchers to make decisions on appropriate trade-offs between various conflicting goals. A variety of deterministic and stochastic multi-objective optimization methods are developed in this book. Beginning with basic concepts and a review of non-convex single-objective optimization problems; this book moves on to cover multi-objective branch and bound algorithms, worst-case optimal algorithms (for Lipschitz functions and bi-objective problems), statistical models based algorithms, and probabilistic branch and bound approach. Detailed descriptions of new algorithms for non-convex multi-objective optimization, their theoretical substantiation, and examples for practical applications to the cell formation problem in manufacturing engineering, the process design in...

Transport Infrastructure Slot Allocation

NARCIS (Netherlands)

Koolstra, K.

2005-01-01

In this thesis, transport infrastructure slot allocation has been studied, focusing on selection slot allocation, i.e. on longer-term slot allocation decisions determining the traffic patterns served by infrastructure bottlenecks, rather than timetable-related slot allocation problems. The

Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

L. DJEROU,

2012-01-01

Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

Calculation of induced rotor current in induction motors using a slotted semi-analytical harmonic model

NARCIS (Netherlands)

Sprangers, R.L.J.; Gysen, B.L.J.; Paulides, J.J.H.; Waarma, J.; Lomonova, E.A.

2014-01-01

Recently, strong improvements have been made in the applicability of harmonic modeling techniques for electrical machines with slotted structures. Various implementations for permanent magnet motors and actuators have been investigated and applied in design and optimization tools. For the slotted

A design procedure for a slotted waveguide with probe-fed slots radiating into plasma

International Nuclear Information System (INIS)

Colborn, J.A.

1989-11-01

A design procedure is developed for slotted-waveguide antennas with probe-fed slots. Radiation into a gyrotropic, plane-stratified medium is considered, nonzero waveguide wall thickness is assumed, and noncosinusoidal slot fields and arbitrary slot length up to about one free-space wavelength are allowed. External mutual coupling is taken into account by matching the tangential fields at the antenna surface. The particular case of longitudinal slots in the broad face of rectangular guide is analyzed. The motivation for this work is the design of such radiators for plasma heating and current-drive on thermonuclear fusion experiments, but some of the analysis is applicable to the probeless slotted waveguide used for avionics and communications. 20 refs., 5 figs

Shape optimization of 3D curved slots and its application to the squirrel-cage elastic support design

Science.gov (United States)

Wang, Dan; Zhang, Weihong; Wang, Zhenpei; Zhu, Jihong

2010-10-01

The squirrel-cage elastic support is one of the most important components of an aero-engine rotor system. A proper structural design will favor the static and dynamic performances of the system. In view of the deficiency of the current shape optimization techniques, a new mapping approach is proposed to define shape design variables based on the parametric equations of 3D curves and surfaces. It is then applied for the slot shape optimization of a squirrel-cage elastic support. To this end, an automatic design procedure that integrates the Genetic Algorithm (GA) is developed to solve the problem. Two typical examples with different shape constraints are considered. Numerical results provide reasonable optimum designs for the improvement of stiffness and strength of the squirrel-cage elastic support.

Multi-Objective Optimal Design of Electro-Hydrostatic Actuator Driving Motors for Low Temperature Rise and High Power Weight Ratio

Directory of Open Access Journals (Sweden)

Guo Hong

2018-05-01

Full Text Available With the rapid development of technology, motors have drawn increasing attention in aviation applications, especially in the more electrical aircraft and all electrical aircraft concepts. Power weight ratio and reliability are key parameters for evaluating the performance of equipment applied in aircraft. The temperature rise of the motor is closely related to the reliability of the motor. Therefore, based on Taguchi, a novel multi-objective optimization method for the heat dissipation structural design of an electro-hydrostatic actuator (EHA drive motor was proposed in this paper. First, the thermal network model of the EHA drive motor was established. Second, a sensitivity analysis of the key parameters affecting the cooling performance of the motor was conducted, such as the thickness of fins, the height of fins, the space of fins, the potting materials and the slot fill factor. Third, taking the average temperature of the windings and the power weight ratio as the optimization goal, the multi-objective optimal design of the heat dissipation structure of the motor was carried out by applying Taguchi. Then, a 3-D finite element model of the motor was established and the steady state thermal analysis was carried out. Furthermore, a prototype of the optimal motor was manufactured, and the temperature rise under full load condition tested. The result indicated that the motor with the optimized heat dissipating structure presented a low temperature rise and high power weight ratio, therefore validating the proposed optimization method.

FEM Analysis of Brushless DC Servomotor with Fractional Number of Slots per Pole

Directory of Open Access Journals (Sweden)

BALUTA, G.

2014-02-01

Full Text Available The authors present in this paper the analysis with Finite Element Method (FEM of the magnetic circuit for a Brushless DC servomotor with fractional number of slots/pole (9 slots and 10 poles. For this purpose, FEMM 4.2 software package was used for the analysis. To obtain the waveforms of Back-ElectroMotive Forces (BEMFs, electromagnetic and cogging torque for servomotor a program in LUA scripting language (integrated into interactive shell of FEMM4.2 has been created. A comparation with a structure with integer number of slots/pole (18 slots and 6 poles was also realized. The analysis results prove that the structure chosen is an optimal solution: sinusoidal waveforms of BEMFs, improved electromagnetic torque and reduced cogging torque. Therefore, the operating characteristics of the servomotor with 9/10 slots/poles manufactured by Sistem Euroteh Company and included in an integrated electrical drives system are presented in this paper.

Structural damage detection-oriented multi-type sensor placement with multi-objective optimization

Science.gov (United States)

Lin, Jian-Fu; Xu, You-Lin; Law, Siu-Seong

2018-05-01

A structural damage detection-oriented multi-type sensor placement method with multi-objective optimization is developed in this study. The multi-type response covariance sensitivity-based damage detection method is first introduced. Two objective functions for optimal sensor placement are then introduced in terms of the response covariance sensitivity and the response independence. The multi-objective optimization problem is formed by using the two objective functions, and the non-dominated sorting genetic algorithm (NSGA)-II is adopted to find the solution for the optimal multi-type sensor placement to achieve the best structural damage detection. The proposed method is finally applied to a nine-bay three-dimensional frame structure. Numerical results show that the optimal multi-type sensor placement determined by the proposed method can avoid redundant sensors and provide satisfactory results for structural damage detection. The restriction on the number of each type of sensors in the optimization can reduce the searching space in the optimization to make the proposed method more effective. Moreover, how to select a most optimal sensor placement from the Pareto solutions via the utility function and the knee point method is demonstrated in the case study.

Multi-objective optimization of linear multi-state multiple sliding window system

International Nuclear Information System (INIS)

Konak, Abdullah; Kulturel-Konak, Sadan; Levitin, Gregory

2012-01-01

This paper considers the optimal element sequencing in a linear multi-state multiple sliding window system that consists of n linearly ordered multi-state elements. Each multi-state element can have different states: from complete failure up to perfect functioning. A performance rate is associated with each state. The failure of type i in the system occurs if for any i (1≤i≤I) the cumulative performance of any r i consecutive elements is lower than w i . The element sequence strongly affects the probability of any type of system failure. The sequence that minimizes the probability of certain type of failure can provide high probability of other types of failures. Therefore the optimization problem for the multiple sliding window system is essentially multi-objective. The paper formulates and solves the multi-objective optimization problem for the multiple sliding window systems. A multi-objective Genetic Algorithm is used as the optimization engine. Illustrative examples are presented.

Effects of optimism on gambling in the rat slot machine task.

Science.gov (United States)

Rafa, Dominik; Kregiel, Jakub; Popik, Piotr; Rygula, Rafal

2016-03-01

Although gambling disorder is a serious social problem in modern societies, information about the behavioral traits that could determine vulnerability to this psychopathology is still scarce. In this study, we used a recently developed ambiguous-cue interpretation ​(ACI)​ paradigm to investigate whether 'optimism' and 'pessimism' as behavioral traits may determine the gambling-like behavior of rodents. In a series of ACI tests (cognitive bias screening), we identified rats that displayed 'pessimistic' and 'optimistic' traits. Subsequently, using the rat slot machine task (rSMT), we investigated if the 'optimistic'/'pessimistic' traits could determine the crucial feature of gambling-like behavior that has been investigated in rats and humans: the ​interpretation of 'near-miss' outcomes as a positive (i.e., win) situation. We found that 'optimists' did not interpret 'near-miss', 'near loss', or 'clear win' as win trials more often than ​their 'pessimistic' ​conspecifics; however, the 'optimists' were statistically more likely to reach for a reward in the hopeless 'clear loss' situation. This agrees with human studies and provides a platform for modeling interactions between behavioral traits and gambling in animals. Copyright © 2015 Elsevier B.V. All rights reserved.

Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

Science.gov (United States)

Zhang, Jian; Gan, Yang

2018-04-01

The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

Wireless Sensor Network Optimization: Multi-Objective Paradigm.

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-07-20

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks.

Wireless Sensor Network Optimization: Multi-Objective Paradigm

Science.gov (United States)

Iqbal, Muhammad; Naeem, Muhammad; Anpalagan, Alagan; Ahmed, Ashfaq; Azam, Muhammad

2015-01-01

Optimization problems relating to wireless sensor network planning, design, deployment and operation often give rise to multi-objective optimization formulations where multiple desirable objectives compete with each other and the decision maker has to select one of the tradeoff solutions. These multiple objectives may or may not conflict with each other. Keeping in view the nature of the application, the sensing scenario and input/output of the problem, the type of optimization problem changes. To address different nature of optimization problems relating to wireless sensor network design, deployment, operation, planing and placement, there exist a plethora of optimization solution types. We review and analyze different desirable objectives to show whether they conflict with each other, support each other or they are design dependent. We also present a generic multi-objective optimization problem relating to wireless sensor network which consists of input variables, required output, objectives and constraints. A list of constraints is also presented to give an overview of different constraints which are considered while formulating the optimization problems in wireless sensor networks. Keeping in view the multi facet coverage of this article relating to multi-objective optimization, this will open up new avenues of research in the area of multi-objective optimization relating to wireless sensor networks. PMID:26205271

Compact SOI optimized slot microring coupled phase-shifted Bragg grating resonator for sensing

Science.gov (United States)

Zhao, Chao Ying; Zhang, Lei; Zhang, Cheng Mei

2018-05-01

We propose a novel sensor structure composed of a slot microring and a phase-shifted sidewall Bragg gratings in a slot waveguide. We first present a theoretical analysis of transmission by using the transfer matrix. Then, the mode-field distributions of transmission spectrum obtained from 3D simulations based on FDTD method demonstrates that our sensor exhibit theoretical sensitivity of 297 . 13 nm / RIU, a minimum detection limit of 1 . 1 × 10-4 RIU, the maximum extinction ratio of 20 dB, the quality factor of 2 × 103 and a compact dimension-theoretical structure of 15 μm × 8 . 5 μm. Finally, the sensor's performance is simulated for NaCl solution.

On-chip broadband ultra-compact optical couplers and polarization splitters based on off-centered and non-symmetric slotted Si-wire waveguides

Science.gov (United States)

Haldar, Raktim; Mishra, V.; Dutt, Avik; Varshney, Shailendra K.

2016-10-01

In this work, we propose novel schemes to design on-chip ultra-compact optical directional couplers (DC) and broadband polarization beam splitters (PBS) based on off-centered and asymmetric dielectric slot waveguides, respectively. Slot dimensions and positions are optimized to achieve maximum coupling coefficients between two symmetric and non-symmetric slotted Si wire waveguides through overlap integral method. We observe >88% of enhancement in the coupling coefficients when the size-optimized slots are placed in optimal positions, with respect to the same waveguides with no slot. When the waveguides are parallel, in that case, a coupling length as short as 1.73 μm is accomplished for TM mode with the off-centered and optimized slots. This scheme enables us to design optical DC with very small footprint, L c ∼ 0.9 μm in the presence of S-bends. We also report a compact (L c ∼ 1.1 μm) on-chip broadband PBS with hybrid slots. Extinction ratios of 13 dB and 22.3 dB are realized with very low insertion loss (0.055 dB and 0.008 dB) for TM and TE modes at 1.55 μm, respectively. The designed PBS exhibits a bandwidth of 78 nm for the TM mode (C-and partial L-bands) and >100 nm for the TE mode (S + C + L wavelength bands). Such on-chip devices can be used to design compact photonic interconnects and quantum information processing units efficiently. We have also investigated the fabrication tolerances of the proposed devices and described the fabrication steps to realize such hybrid devices. Our results are in good agreement with 3D FDTD simulations.

EFFECTS OF SLOTTED BLADING ON SECONDARY FLOW IN HIGHLY LOADED COMPRESSOR CASCADE

Directory of Open Access Journals (Sweden)

RAMZI MDOUKI

2013-10-01

Full Text Available With the aim to increase allowable blade loadings and enlarge stable operating range in highly loaded compressor, this work is carried out in order to explore the potential of passive control via slotted bladings in linear cascade configurations under both design and stall conditions. Through an extensive 2D-numerical study, the effects of location, width and slope of slots were analysed and the best configuration was identified. Based on the optimal slot, the 3D aerodynamic performances of cascade were studied and the influence of slotted blading to control endwall flow was investigated. Both 2D and 3D calculations are performed on steady RANS solver with standard k-epsilon turbulence model and low Mach number regime. The total loss coefficient, turning angle and flow visualizations on the blade and end-wall surfaces are adopted to describe the different configurations. The obtained results show, for 2D situation, that a maximum of 28.3% reduction in loss coefficient had been reached and the flow turning was increased with approximately 5°. Concerning 3D flow fields the slots marked their benefit at large incoming flow angles which delays the separation on both end wall and blade suction surface at mid span. However, at design conditions, the slotted blades are not able to control secondary flows near the wall and so, lose their potential.

A piezoelectric ultrasonic linear micromotor using a slotted stator.

Science.gov (United States)

Yun, Cheol-Ho; Watson, Brett; Friend, James; Yeo, Leslie

2010-08-01

A novel ultrasonic micro linear motor that uses 1st longitudinal and 2nd bending modes, derived from a bartype stator with a rectangular slot cut through the stator length, has been proposed and designed for end-effect devices of microrobotics and bio-medical applications. The slot structure plays an important role in the motor design, and can be used not only to tune the resonance frequency of the two vibration modes but also to reduce the undesirable longitudinal coupling displacement caused by bending vibration at the end of the stator. By using finite element analysis, the optimal slot dimension to improve the driving tip motion was determined, resulting in the improvement of the motor performance. The trial linear motor, with a weight of 1.6 g, gave a maximum driving velocity of 1.12 m/s and a maximum driving force of 3.4 N. A maximum mechanical output power of 1.1 W was obtained at force of 1.63 N and velocity of 0.68 m/s. The output mechanical power per unit weight was 688 W/kg.

Optimization of multi-branch switched diversity systems

KAUST Repository

Nam, Haewoon; Alouini, Mohamed-Slim

2009-01-01

A performance optimization based on the optimal switching threshold(s) for a multi-branch switched diversity system is discussed in this paper. For the conventional multi-branch switched diversity system with a single switching threshold

An analysis of switching and non-switching slot machine player behaviour.

Science.gov (United States)

Coates, Ewan; Blaszczynski, Alex

2013-12-01

Learning theory predicts that, given the repeated choice to bet between two concurrently available slot machines, gamblers will learn to bet more money on the machine with higher expected return (payback percentage) or higher win probability per spin (volatility). The purpose of this study was to investigate whether this occurs when the two machines vary orthogonally on payback percentage and volatility. The sample comprised 52 first year psychology students (mean age = 20.3 years, 20 females, 32 males) who had played a gaming machine at least once in the previous 12 months. Participants were administered a battery of questionnaires designed to assess level of knowledge on the characteristics and operation of poker machines, frequency of poker machine play in the past 12 months, personality traits of impulsivity and capacity for cognitive reflection, and gambling beliefs. For the experimental task, participants were instructed to play on two PC-simulated electronic gaming machines (EGMs or slot machines) that differed on payback percentage and volatility, with the option of freely switching between EGMs after a practice phase. Results indicated that participants were able to easily discriminate between machines and manifested a preference to play machines offering higher payback or volatility. These findings diverged from previous findings of no preference for play on higher payback/volatility machines, potentially due to of the current study's absence of the option to make multi-line and multi-credit bets. It was concluded that return rate parameters like payback percentage and volatility strongly influenced slot machine preference in the absence of betting options like multi-line bets, though more research is needed to determine the effects of such betting options on player distribution of money between multiple EGMs.

Revisiting Street Intersections Using Slot-Based Systems.

Directory of Open Access Journals (Sweden)

Remi Tachet

Full Text Available Since their appearance at the end of the 19th century, traffic lights have been the primary mode of granting access to road intersections. Today, this centuries-old technology is challenged by advances in intelligent transportation, which are opening the way to new solutions built upon slot-based systems similar to those commonly used in aerial traffic: what we call Slot-based Intersections (SIs. Despite simulation-based evidence of the potential benefits of SIs, a comprehensive, analytical framework to compare their relative performance with traffic lights is still lacking. Here, we develop such a framework. We approach the problem in a novel way, by generalizing classical queuing theory. Having defined safety conditions, we characterize capacity and delay of SIs. In the 2-road crossing configuration, we provide a capacity-optimal SI management system. For arbitrary intersection configurations, near-optimal solutions are developed. Results theoretically show that transitioning from a traffic light system to SI has the potential of doubling capacity and significantly reducing delays. This suggests a reduction of non-linear dynamics induced by intersection bottlenecks, with positive impact on the road network. Such findings can provide transportation engineers and planners with crucial insights as they prepare to manage the transition towards a more intelligent transportation infrastructure in cities.

A new method for the design of slot antenna arrays: Theory and experiment

KAUST Repository

Clauzier, Sebastien

2016-04-10

The present paper proposes and validates a new general design methodology that can be used to automatically find proper positions and orientations of waveguide-based radiating slots capable of realizing any given radiation beam profile. The new technique combines basic radiation theory and waveguide propagation theory in a novel analytical model that allows the prediction of the radiation characteristics of generic slots without the need to perform full-wave numerical solution. The analytical model is then used to implement a low-cost objective function within a global optimization scheme (here genetic algorithm.) The algorithm is then deployed to find optimum positions and orientations of clusters of radiating slots cut into the waveguide surface such that any desired beam pattern can be obtained. The method is verified using both full-wave numerical solution and experiment.

Slot-Coupled Barbel Antenna

DEFF Research Database (Denmark)

Jørgensen, Kasper Lüthje; Jakobsen, Kaj Bjarne

2016-01-01

A novel slot-coupled barbel antenna is designed and analyzed. A sensitivity analysis performed in order to improve the bandwidth, while the center frequency is kept constant.......A novel slot-coupled barbel antenna is designed and analyzed. A sensitivity analysis performed in order to improve the bandwidth, while the center frequency is kept constant....

G-Tunnel pressurized slot-testing preparations

International Nuclear Information System (INIS)

Zimmerman, R.M.; Sifre-Soto, C.; Mann, K.L.; Bellman, R.A. Jr.; Luker, S.; Dodds, D.J.

1992-04-01

Designers and analysts of radioactive waste repositories must be able to predict the mechanical behavior of the host rock. Sandia National laboratories elected to conduct a development program on pressurized slot testing and featured (1) development of an improved method to cut slots using a chain saw with diamond-tipped cutters, (2) measurements useful for determining in situ stresses normal to slots, (3) measurements applicable for determining the in situ modulus of deformation parallel to a drift surface, and (4) evaluations of the potentials of pressurized slot strength testing. This report describes the preparations leading to the measurements and evaluations

Multiphysics modelling and simulation of dry laser cleaning of micro-slots with particle contaminants

International Nuclear Information System (INIS)

Yue Liyang; Wang Zengbo; Li Lin

2012-01-01

Light could interact differently with thin-film contaminants and particle contaminates because of their different surface morphologies. In the case of dry laser cleaning of small transparent particles, it is well known that particles could function like mini-lenses, causing a localized near-field hot spot effect on the cleaning process. This paper looks into a special, yet important, phenomenon of dry laser cleaning of particles trapped in micro-sized slots. The effects of slot size, particle size and particle aggregate states in the cleaning process have been theoretically investigated, based on a coupled electromagnetic-thermal-mechanical multiphysics modelling and simulation approach. The study is important for the development and optimization of laser cleaning processes for contamination removal from cracks and slots. (paper)

Multi-objective design optimization of the transverse gaseous jet in supersonic flows

Science.gov (United States)

Huang, Wei; Yang, Jun; Yan, Li

2014-01-01

The mixing process between the injectant and the supersonic crossflow is one of the important issues for the design of the scramjet engine, and the efficiency mixing has a great impact on the improvement of the combustion efficiency. A hovering vortex is formed between the separation region and the barrel shock wave, and this may be induced by the large negative density gradient. The separation region provides a good mixing area for the injectant and the subsonic boundary layer. In the current study, the transverse injection flow field with a freestream Mach number of 3.5 has been optimized by the non-dominated sorting genetic algorithm (NSGA II) coupled with the Kriging surrogate model; and the variance analysis method and the extreme difference analysis method have been employed to evaluate the values of the objective functions. The obtained results show that the jet-to-crossflow pressure ratio is the most important design variable for the transverse injection flow field, and the injectant molecular weight and the slot width should be considered for the mixing process between the injectant and the supersonic crossflow. There exists an optimal penetration height for the mixing efficiency, and its value is about 14.3 mm in the range considered in the current study. The larger penetration height provides a larger total pressure loss, and there must be a tradeoff between these two objection functions. In addition, this study demonstrates that the multi-objective design optimization method with the data mining technique can be used efficiently to explore the relationship between the design variables and the objective functions.

Airflow and Heat Transfer in the Slot-Vented Room with Radiant Floor Heating Unit

Directory of Open Access Journals (Sweden)

Xiang-Long Liu

2012-01-01

Full Text Available Radiant floor heating has received increasing attention due to its diverse advantages, especially the energy saving as compared to the conventional dwelling heating system. This paper presents a numerical investigation of airflow and heat transfer in the slot-vented room with the radiant floor heating unit. Combination of fluid convection and thermal radiation has been implemented through the thermal boundary conditions. Spatial distributions of indoor air temperature and velocity, as well as the heat transfer rates along the radiant floor and the outer wall, have been presented and analyzed covering the domains from complete natural convection to forced convection dominated flows. The numerical results demonstrate that the levels of average temperature in the room with lateral slot-ventilation are higher than those without slot-ventilation, but lower than those in the room with ceiling slot-ventilation. Overall, the slot-ventilation room with radiant floor heating unit could offer better indoor air quality through increasing the indoor air temperature and fresh air exchanging rate simultaneously. Concerning the airborne pollutant transports and moisture condensations, the performance of radiant floor heating unit will be further optimized in our future researches.

Optical Slot-Waveguide Based Biochemical Sensors

Directory of Open Access Journals (Sweden)

Carlos Angulo Barrios

2009-06-01

Full Text Available Slot-waveguides allow light to be guided and strongly confined inside a nanometer-scale region of low refractive index. Thus stronger light-analyte interaction can be obtained as compared to that achievable by a conventional waveguide, in which the propagating beam is confined to the high-refractive-index core of the waveguide. In addition, slot-waveguides can be fabricated by employing CMOS compatible materials and technology, enabling miniaturization, integration with electronic, photonic and fluidic components in a chip, and mass production. These advantages have made the use of slot-waveguides for highly sensitive biochemical optical integrated sensors an emerging field. In this paper, recent achievements in slot-waveguide based biochemical sensing will be reviewed. These include slot-waveguide ring resonator based refractometric label-free biosensors, label-based optical sensing, and nano-opto-mechanical sensors.

Optimization of multi-branch switched diversity systems

KAUST Repository

Nam, Haewoon

2009-10-01

A performance optimization based on the optimal switching threshold(s) for a multi-branch switched diversity system is discussed in this paper. For the conventional multi-branch switched diversity system with a single switching threshold, the optimal switching threshold is a function of both the average channel SNR and the number of diversity branches, where computing the optimal switching threshold is not a simple task when the number of diversity branches is high. The newly proposed multi-branch switched diversity system is based on a sequence of switching thresholds, instead of a single switching threshold, where a different diversity branch uses a different switching threshold for signal comparison. Thanks to the fact that each switching threshold in the sequence can be optimized only based on the number of the remaining diversity branches, the proposed system makes it easy to find these switching thresholds. Furthermore, some selected numerical and simulation results show that the proposed switched diversity system with the sequence of optimal switching thresholds outperforms the conventional system with the single optimal switching threshold. © 2009 IEEE.

Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

Directory of Open Access Journals (Sweden)

Yan Sun

2015-09-01

Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

Multi-net optimization of VLSI interconnect

CERN Document Server

Moiseev, Konstantin; Wimer, Shmuel

2015-01-01

This book covers layout design and layout migration methodologies for optimizing multi-net wire structures in advanced VLSI interconnects. Scaling-dependent models for interconnect power, interconnect delay and crosstalk noise are covered in depth, and several design optimization problems are addressed, such as minimization of interconnect power under delay constraints, or design for minimal delay in wire bundles within a given routing area. A handy reference or a guide for design methodologies and layout automation techniques, this book provides a foundation for physical design challenges of interconnect in advanced integrated circuits.  • Describes the evolution of interconnect scaling and provides new techniques for layout migration and optimization, focusing on multi-net optimization; • Presents research results that provide a level of design optimization which does not exist in commercially-available design automation software tools; • Includes mathematical properties and conditions for optimal...

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan

2016-12-29

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan; Tsang, Ivor Wai-Hung; Cui, Xuefeng; Lu, Zhiwu; Gao, Xin

2016-01-01

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Optimization of nanoparticulate indium tin oxide slurries for the manufacture of ultra-thin indium tin oxide coatings with the slot-die coating process

International Nuclear Information System (INIS)

Wegener, M.; Riess, K.; Roosen, A.

2016-01-01

This paper deals with the optimization of colloidal processing to achieve suitable nanoparticulate indium tin oxide (ITO) slurries for the production of sub-μm-thin ITO coatings with the slot die coating process. For application in printed electronics these ITO coatings, which are composite films consisting of nanoparticulate ITO and a polymeric binder, should offer high flexibility, transparency and electrical conductivity. To preserve their flexibility, the composite films are not subject to any heat treatment, instead they are used as deposited and dried. To achieve very good transparency and electrical conductivity at the same time, the slurries must exhibit excellent dispersivity to result in a dense particle packing during film formation and drying. To reduce materials costs, films with thicknesses of several 100 nm are of interest. Therefore, the slot-die technique was applied as a fast, pre-dosing technique to produce sub-μm-thin ITO/binder composite films. The resulting ITO/binder films were characterized with regard to their key properties such as total transmission and specific electrical resistance. With the colloidal optimization of ethanol- and water-based nanoparticulate ITO slurries using PVP and PVB as binders, it was possible to achieve films of 250 nm in thickness exhibiting high total transmission of ∝ 93 % and a low specific electrical resistance of ∝ 10 Ω.cm.

Optimization of nanoparticulate indium tin oxide slurries for the manufacture of ultra-thin indium tin oxide coatings with the slot-die coating process

Energy Technology Data Exchange (ETDEWEB)

Wegener, M.; Riess, K.; Roosen, A. [Erlangen-Nuremberg Univ., Erlangen (Germany). Dept. of Materials Science, Glass and Ceramics

2016-07-01

This paper deals with the optimization of colloidal processing to achieve suitable nanoparticulate indium tin oxide (ITO) slurries for the production of sub-μm-thin ITO coatings with the slot die coating process. For application in printed electronics these ITO coatings, which are composite films consisting of nanoparticulate ITO and a polymeric binder, should offer high flexibility, transparency and electrical conductivity. To preserve their flexibility, the composite films are not subject to any heat treatment, instead they are used as deposited and dried. To achieve very good transparency and electrical conductivity at the same time, the slurries must exhibit excellent dispersivity to result in a dense particle packing during film formation and drying. To reduce materials costs, films with thicknesses of several 100 nm are of interest. Therefore, the slot-die technique was applied as a fast, pre-dosing technique to produce sub-μm-thin ITO/binder composite films. The resulting ITO/binder films were characterized with regard to their key properties such as total transmission and specific electrical resistance. With the colloidal optimization of ethanol- and water-based nanoparticulate ITO slurries using PVP and PVB as binders, it was possible to achieve films of 250 nm in thickness exhibiting high total transmission of ∝ 93 % and a low specific electrical resistance of ∝ 10 Ω.cm.

CMS readiness for multi-core workload scheduling

Science.gov (United States)

Perez-Calero Yzquierdo, A.; Balcas, J.; Hernandez, J.; Aftab Khan, F.; Letts, J.; Mason, D.; Verguilov, V.

2017-10-01

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.

CMS Readiness for Multi-Core Workload Scheduling

Energy Technology Data Exchange (ETDEWEB)

Perez-Calero Yzquierdo, A. [Madrid, CIEMAT; Balcas, J. [Caltech; Hernandez, J. [Madrid, CIEMAT; Aftab Khan, F. [NCP, Islamabad; Letts, J. [UC, San Diego; Mason, D. [Fermilab; Verguilov, V. [CLMI, Sofia

2017-11-22

In the present run of the LHC, CMS data reconstruction and simulation algorithms benefit greatly from being executed as multiple threads running on several processor cores. The complexity of the Run 2 events requires parallelization of the code to reduce the memory-per- core footprint constraining serial execution programs, thus optimizing the exploitation of present multi-core processor architectures. The allocation of computing resources for multi-core tasks, however, becomes a complex problem in itself. The CMS workload submission infrastructure employs multi-slot partitionable pilots, built on HTCondor and GlideinWMS native features, to enable scheduling of single and multi-core jobs simultaneously. This provides a solution for the scheduling problem in a uniform way across grid sites running a diversity of gateways to compute resources and batch system technologies. This paper presents this strategy and the tools on which it has been implemented. The experience of managing multi-core resources at the Tier-0 and Tier-1 sites during 2015, along with the deployment phase to Tier-2 sites during early 2016 is reported. The process of performance monitoring and optimization to achieve efficient and flexible use of the resources is also described.

Research on TIG weld machine of the upper side ring slot of Gd-rod technology reconstruct

International Nuclear Information System (INIS)

Fang Shixiang; Lan Zhibing; Cui Quhu

2010-01-01

The research on TIG weld machine of the upper side ring slot of Gd-rod existent matter: seal electrical source got up difficulty; control system had graveness aging; space between was adjusted precision lowness; welding torch lay mode and structure were not in reason. carried through all around technology reconstruct: had chosen the best of TIG weld machine; designed ignite arc device, designed optics imaging device, designed tungsten mighty axis direction auto conditioning, was provided with arc slot, adopted PLC to control the whole system and realization auto control. After TIG weld machine of the upper side ring slot of Gd-rod technology reconstruct research , provided with arc slot the first time in the Gd-rod of nuclear fuel, optimized the weld technics, improved welding line melt width and deep equality, stability, and great breadth advanced nuclear fuel product line technology and throughput. (authors)

MHD-flow in slotted channels with conducting walls

International Nuclear Information System (INIS)

Evtushenko, I.A.; Kirillov, I.R.; Reed, C.B.

1994-07-01

A review of experimental results is presented for magnetohydrodynamic (MHD) flow in rectangular channels with conducting walls and high aspect ratios (longer side parallel to the applied magnetic field), which are called slotted channels. The slotted channel concept was conceived at Efremov Institute as a method for reducing MHD pressure drop in liquid metal cooled blanket design. The experiments conducted by the authors were aimed at studying both fully developed MHD-flow, and the effect of a magnetic field on the hydrodynamics of 3-D flows in slotted channels. Tests were carried out on five models of the slotted geometry. A good agreement between test and theoretical results for the pressure drop in slotted channels was demonstrated. Application of a open-quotes one-electrode movable probeclose quotes for velocity measurement permitted measurement of the M-shape velocity profiles in the slotted channels. Suppression of 3-D inertial effects in slotted channels of complex geometry was demonstrated based on potential distribution data

Pumping slots: impedances and power losses

Energy Technology Data Exchange (ETDEWEB)

Kurennoy, S [Maryland Univ., College Park, MD (United States). Dept. of Physics

1996-08-01

Contributions of pumping slots to the beam coupling impedances and power losses in a B-factory ring are considered. While their leading contribution is to the inductive impedance, for high-intensity machines with short bunches like e{sup +}e{sup -} B-factories the real part of the impedance and related loss factors are also important. Using an analytical approach we calculate the coupling impedances and loss factors due to slots in a ring with an arbitrary cross section of the vacuum chamber. Effects of the slot tilt on the beam impedance are also considered, and restrictions on the tilt angle are derived from limitations on the impedance increase. The power leakage through the slots is discussed briefly. The results are applied to the KEK B-factory. (author)

Optimization strategies for discrete multi-material stiffness optimization

DEFF Research Database (Denmark)

Hvejsel, Christian Frier; Lund, Erik; Stolpe, Mathias

2011-01-01

Design of composite laminated lay-ups are formulated as discrete multi-material selection problems. The design problem can be modeled as a non-convex mixed-integer optimization problem. Such problems are in general only solvable to global optimality for small to moderate sized problems. To attack...... which numerically confirm the sought properties of the new scheme in terms of convergence to a discrete solution....

A procedure for multi-objective optimization of tire design parameters

Directory of Open Access Journals (Sweden)

Nikola Korunović

2015-04-01

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

Investigation of a 7-pole/6-slot Halbach-magnetized permanent-magnet linear alternator used for free-piston stirling engines

Science.gov (United States)

Zheng, Ping; Tong, Chengde; Zhao, Jing; Yu, Bin; Li, Lin; Bai, Jingang; Zhang, Lu

2012-04-01

This paper investigates a 7-pole/6-slot Halbach-magnetized permanent-magnet linear alternator used for free piston Stirling engines (FPSEs). Taking the advantages of Halbach array, a 1 kW prototype alternator is designed. Considering the rms value of electromotive force (EMF) and harmonic distortion, the optimal length ratio of the axial- and radial-magnetized permanent magnets and thicknesses of the permanent magnets are optimized by 2D finite element method. The alternator detent force, which is an important factor for smooth operation of FPSEs, is studied by optimizing slot tip and end tooth. The load and thermal performances of the final design are simulated. A prototype alternator was designed, built and tested. Experimental data indicated satisfactory design.

Aerodynamic multi-objective integrated optimization based on principal component analysis

Directory of Open Access Journals (Sweden)

Jiangtao HUANG

2017-08-01

Full Text Available Based on improved multi-objective particle swarm optimization (MOPSO algorithm with principal component analysis (PCA methodology, an efficient high-dimension multi-objective optimization method is proposed, which, as the purpose of this paper, aims to improve the convergence of Pareto front in multi-objective optimization design. The mathematical efficiency, the physical reasonableness and the reliability in dealing with redundant objectives of PCA are verified by typical DTLZ5 test function and multi-objective correlation analysis of supercritical airfoil, and the proposed method is integrated into aircraft multi-disciplinary design (AMDEsign platform, which contains aerodynamics, stealth and structure weight analysis and optimization module. Then the proposed method is used for the multi-point integrated aerodynamic optimization of a wide-body passenger aircraft, in which the redundant objectives identified by PCA are transformed to optimization constraints, and several design methods are compared. The design results illustrate that the strategy used in this paper is sufficient and multi-point design requirements of the passenger aircraft are reached. The visualization level of non-dominant Pareto set is improved by effectively reducing the dimension without losing the primary feature of the problem.

Student-Led Objective Tutorial (SLOT) in Medical Education.

Science.gov (United States)

Sivagnanam, Gurusamy; Saraswathi, Simansalam; Rajasekaran, Aiyalu

2006-12-01

Purpose - To assess an innovative tutoring program named 'Student-Led Objective Tutorial' (SLOT) among undergraduate medical students. Method - The program was conceptualized by the Pharmacology Unit of Faculty of Medicine and Health Sciences, Asian Institute of Medicine Science & Technology (AIMST), Malaysia and implemented in the middle of 2005. A cohort of 246 medical undergraduate students (spread across 5 consecutive batches) participated. Following a brief explanation on the purpose and nature of SLOT, each batch was divided into small groups and was given a reading assignment on 4 previously delivered lecture topics. Each group was asked to prepare 3-5 multiple choice questions (MCQs) of their own in PowerPoint format to be presented, in turns, to the whole class on the day of SLOT. The proceedings were facilitated by 2 lecturers. Student feedback on the efficacy and benefits were assessed through an anonymous self administered questionnaire. Results - About 76% (188) of the students favored SLOT. The acceptance rate of SLOT was higher among males. There was no significant difference between batches in their opinions on whether to pursue SLOT in future. The most prevalent positive comment was that SLOT enhanced learning skills, and the negative comment being, it consumed more time. Conclusions - SLOT is a novel tutorial method which can offset faculty shortage with advantages like enhanced interest among teachers and learners, uniform reach of content, opportunities for group learning, and involvement of visual aids as teaching-learning (T-L) method. SLOT unraveled the students' potential of peer tutoring both inside as well as outside the classroom. Consumer tutors (students) can be tapped as a resource for SLOT for all subjects and courses in healthcare teaching.

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

Science.gov (United States)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Design and multi-physics optimization of rotary MRF brakes

Science.gov (United States)

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

2018-03-01

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

Slotting allowances to coordinate manufacturers’ retail sales effort

OpenAIRE

Foros, Øystein; Kind, Hans Jarle; Sand, Jan Yngve

2007-01-01

Slotting allowances are fees paid by manufacturers to get access to retailers’ shelf space. Although the main attention towards slotting allowances has been within the grocery industry, slotting allowances have also been applied within e.g. e-commerce and mobile telephony. In these industries we observe that distributors have large market power due to their control of access to customers. We analyse how shifting bargaining power from manufacturers to retailers and the use of slotting allowanc...

Multi objective multi refinery optimization with environmental and catastrophic failure effects objectives

Science.gov (United States)

Khogeer, Ahmed Sirag

2005-11-01

Petroleum refining is a capital-intensive business. With stringent environmental regulations on the processing industry and declining refining margins, political instability, increased risk of war and terrorist attacks in which refineries and fuel transportation grids may be targeted, higher pressures are exerted on refiners to optimize performance and find the best combination of feed and processes to produce salable products that meet stricter product specifications, while at the same time meeting refinery supply commitments and of course making profit. This is done through multi objective optimization. For corporate refining companies and at the national level, Intea-Refinery and Inter-Refinery optimization is the second step in optimizing the operation of the whole refining chain as a single system. Most refinery-wide optimization methods do not cover multiple objectives such as minimizing environmental impact, avoiding catastrophic failures, or enhancing product spec upgrade effects. This work starts by carrying out a refinery-wide, single objective optimization, and then moves to multi objective-single refinery optimization. The last step is multi objective-multi refinery optimization, the objectives of which are analysis of the effects of economic, environmental, product spec, strategic, and catastrophic failure. Simulation runs were carried out using both MATLAB and ASPEN PIMS utilizing nonlinear techniques to solve the optimization problem. The results addressed the need to debottleneck some refineries or transportation media in order to meet the demand for essential products under partial or total failure scenarios. They also addressed how importing some high spec products can help recover some of the losses and what is needed in order to accomplish this. In addition, the results showed nonlinear relations among local and global objectives for some refineries. The results demonstrate that refineries can have a local multi objective optimum that does not

Strength Pareto particle swarm optimization and hybrid EA-PSO for multi-objective optimization.

Science.gov (United States)

Elhossini, Ahmed; Areibi, Shawki; Dony, Robert

2010-01-01

This paper proposes an efficient particle swarm optimization (PSO) technique that can handle multi-objective optimization problems. It is based on the strength Pareto approach originally used in evolutionary algorithms (EA). The proposed modified particle swarm algorithm is used to build three hybrid EA-PSO algorithms to solve different multi-objective optimization problems. This algorithm and its hybrid forms are tested using seven benchmarks from the literature and the results are compared to the strength Pareto evolutionary algorithm (SPEA2) and a competitive multi-objective PSO using several metrics. The proposed algorithm shows a slower convergence, compared to the other algorithms, but requires less CPU time. Combining PSO and evolutionary algorithms leads to superior hybrid algorithms that outperform SPEA2, the competitive multi-objective PSO (MO-PSO), and the proposed strength Pareto PSO based on different metrics.

Band structures in two-dimensional phononic crystals with periodic Jerusalem cross slot

Science.gov (United States)

Li, Yinggang; Chen, Tianning; Wang, Xiaopeng; Yu, Kunpeng; Song, Ruifang

2015-01-01

In this paper, a novel two-dimensional phononic crystal composed of periodic Jerusalem cross slot in air matrix with a square lattice is presented. The dispersion relations and the transmission coefficient spectra are calculated by using the finite element method based on the Bloch theorem. The formation mechanisms of the band gaps are analyzed based on the acoustic mode analysis. Numerical results show that the proposed phononic crystal structure can yield large band gaps in the low-frequency range. The formation mechanism of opening the acoustic band gaps is mainly attributed to the resonance modes of the cavities inside the Jerusalem cross slot structure. Furthermore, the effects of the geometrical parameters on the band gaps are further explored numerically. Results show that the band gaps can be modulated in an extremely large frequency range by the geometry parameters such as the slot length and width. These properties of acoustic waves in the proposed phononic crystals can potentially be applied to optimize band gaps and generate low-frequency filters and waveguides.

Multi-Fidelity Multi-Strategy and Multi-Disciplinary Design Optimization Environment, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Multidisciplinary design and optimization (MDO) tools developed to perform multi-disciplinary analysis based on low fidelity computation methods have been used in...

Multi-objective optimization of inverse planning for accurate radiotherapy

International Nuclear Information System (INIS)

Cao Ruifen; Pei Xi; Cheng Mengyun; Li Gui; Hu Liqin; Wu Yican; Jing Jia; Li Guoli

2011-01-01

The multi-objective optimization of inverse planning based on the Pareto solution set, according to the multi-objective character of inverse planning in accurate radiotherapy, was studied in this paper. Firstly, the clinical requirements of a treatment plan were transformed into a multi-objective optimization problem with multiple constraints. Then, the fast and elitist multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) was introduced to optimize the problem. A clinical example was tested using this method. The results show that an obtained set of non-dominated solutions were uniformly distributed and the corresponding dose distribution of each solution not only approached the expected dose distribution, but also met the dose-volume constraints. It was indicated that the clinical requirements were better satisfied using the method and the planner could select the optimal treatment plan from the non-dominated solution set. (authors)

Recent advances in evolutionary multi-objective optimization

CERN Document Server

Datta, Rituparna; Gupta, Abhishek

2017-01-01

This book covers the most recent advances in the field of evolutionary multiobjective optimization. With the aim of drawing the attention of up-andcoming scientists towards exciting prospects at the forefront of computational intelligence, the authors have made an effort to ensure that the ideas conveyed herein are accessible to the widest audience. The book begins with a summary of the basic concepts in multi-objective optimization. This is followed by brief discussions on various algorithms that have been proposed over the years for solving such problems, ranging from classical (mathematical) approaches to sophisticated evolutionary ones that are capable of seamlessly tackling practical challenges such as non-convexity, multi-modality, the presence of multiple constraints, etc. Thereafter, some of the key emerging aspects that are likely to shape future research directions in the field are presented. These include:< optimization in dynamic environments, multi-objective bilevel programming, handling high ...

Dual Mode Slotted Monopole Antenna

Science.gov (United States)

2017-01-05

May 2017 The below identified patent application is available for licensing. Requests for information should be addressed to: TECHNOLOGY...REFERENCE TO OTHER PATENT APPLICATIONS [0002] None. BACKGROUND OF THE INVENTION (1) Field of the Invention [0003] The present invention is directed...to connect across slot 14. [0005] In United States Patent No. 6,127,983 to Rivera and Josypenko, it has been shown that the slotted cylinder

S-parameters for weakly excited slots

DEFF Research Database (Denmark)

Albertsen, Niels Christian

1999-01-01

A simple approach to account for parasitic effects in weakly excited slots cut in the broad wall of a rectangular waveguide is proposed......A simple approach to account for parasitic effects in weakly excited slots cut in the broad wall of a rectangular waveguide is proposed...

Slot Machine Response Frequency Predicts Pathological Gambling

DEFF Research Database (Denmark)

Linnet, Jakob; Rømer Thomsen, Kristine; Møller, Arne

2013-01-01

Slot machines are among the most addictive forms of gambling, and pathological gambling slot machine players represent the largest group of treatment seekers, accounting for 35% to 93% of the population. Pathological gambling sufferers have significantly higher response frequency (games / time......) on slot machines compared with non-problem gamblers, which may suggest increased reinforcement of the gambling behavior in pathological gambling. However, to date it is unknown whether or not the increased response frequency in pathological gambling is associated with symptom severity of the disorder....... This study tested the hypothesis that response frequency is associated with symptom severity in pathological gambling. We tested response frequency among twenty-two pathological gambling sufferers and twenty-one non-problem gamblers on a commercially available slot machine, and screened for pathological...

Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

Science.gov (United States)

Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

2016-11-01

A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

Multi-objective optimization in computer networks using metaheuristics

CERN Document Server

Donoso, Yezid

2007-01-01

Metaheuristics are widely used to solve important practical combinatorial optimization problems. Many new multicast applications emerging from the Internet-such as TV over the Internet, radio over the Internet, and multipoint video streaming-require reduced bandwidth consumption, end-to-end delay, and packet loss ratio. It is necessary to design and to provide for these kinds of applications as well as for those resources necessary for functionality. Multi-Objective Optimization in Computer Networks Using Metaheuristics provides a solution to the multi-objective problem in routing computer networks. It analyzes layer 3 (IP), layer 2 (MPLS), and layer 1 (GMPLS and wireless functions). In particular, it assesses basic optimization concepts, as well as several techniques and algorithms for the search of minimals; examines the basic multi-objective optimization concepts and the way to solve them through traditional techniques and through several metaheuristics; and demonstrates how to analytically model the compu...

A Comparative Study on Fatigue Life Optimization of the Intersection between a Longitudinal and a Webframe

DEFF Research Database (Denmark)

Birk-Sørensen, Martin

1996-01-01

to improve the design. A new improved slot for the longitudinal intersection in the web plate is found on the basis of a shape optimization of the conventional slot. The new slot has an unique shape (tongue form) resulting in a stress relaxation around the slot. Both the conventional and the new slot...... structure were analyzed by FEM followed by fatigue life calculations and subsequently compared. The overall expected fatigue life for the shape optimized slot will increase by approximately 12 %. The results were compared with an another study concerning a slot for a T-longitudinal....

[Multi-mathematical modelings for compatibility optimization of Jiangzhi granules].

Science.gov (United States)

Yang, Ming; Zhang, Li; Ge, Yingli; Lu, Yanliu; Ji, Guang

2011-12-01

To investigate into the method of "multi activity index evaluation and combination optimized of mult-component" for Chinese herbal formulas. According to the scheme of uniform experimental design, efficacy experiment, multi index evaluation, least absolute shrinkage, selection operator (LASSO) modeling, evolutionary optimization algorithm, validation experiment, we optimized the combination of Jiangzhi granules based on the activity indexes of blood serum ALT, ALT, AST, TG, TC, HDL, LDL and TG level of liver tissues, ratio of liver tissue to body. Analytic hierarchy process (AHP) combining with criteria importance through intercriteria correlation (CRITIC) for multi activity index evaluation was more reasonable and objective, it reflected the information of activity index's order and objective sample data. LASSO algorithm modeling could accurately reflect the relationship between different combination of Jiangzhi granule and the activity comprehensive indexes. The optimized combination of Jiangzhi granule showed better values of the activity comprehensive indexed than the original formula after the validation experiment. AHP combining with CRITIC can be used for multi activity index evaluation and LASSO algorithm, it is suitable for combination optimized of Chinese herbal formulas.

Enhanced Multi-Objective Energy Optimization by a Signaling Method

OpenAIRE

Soares, João; Borges, Nuno; Vale, Zita; Oliveira, P.B.

2016-01-01

In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization (W-PSO), multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II). The performance of these methods with the use of multi-dimensi...

Multi-objective optimization of Stirling engine systems using Front-based Yin-Yang-Pair Optimization

International Nuclear Information System (INIS)

Punnathanam, Varun; Kotecha, Prakash

2017-01-01

Highlights: • Efficient multi-objective optimization algorithm F-YYPO demonstrated. • Three Stirling engine applications with a total of eight cases. • Improvements in the objective function values of up to 30%. • Superior to the popularly used gamultiobj of MATLAB. • F-YYPO has extremely low time complexity. - Abstract: In this work, we demonstrate the performance of Front-based Yin-Yang-Pair Optimization (F-YYPO) to solve multi-objective problems related to Stirling engine systems. The performance of F-YYPO is compared with that of (i) a recently proposed multi-objective optimization algorithm (Multi-Objective Grey Wolf Optimizer) and (ii) an algorithm popularly employed in literature due to its easy accessibility (MATLAB’s inbuilt multi-objective Genetic Algorithm function: gamultiobj). We consider three Stirling engine based optimization problems: (i) the solar-dish Stirling engine system which considers objectives of output power, thermal efficiency and rate of entropy generation; (ii) Stirling engine thermal model which considers the associated irreversibility of the cycle with objectives of output power, thermal efficiency and pressure drop; and finally (iii) an experimentally validated polytropic finite speed thermodynamics based Stirling engine model also with objectives of output power and pressure drop. We observe F-YYPO to be significantly more effective as compared to its competitors in solving the problems, while requiring only a fraction of the computational time required by the other algorithms.

Slotted Circularly Polarized Microstrip Antenna for RFID Application

Directory of Open Access Journals (Sweden)

S. Kumar

2017-12-01

Full Text Available A single layer coaxial fed rectangular microstrip slotted antenna for circular polarization (CP is proposed for radio frequency identification (RFID application. Two triangular shaped slots and one rectangular slot along the diagonal axis of a square patch have been embedded. Due to slotted structure along the diagonal axis and less surface area, good quality of circular polarization has been obtained with the reduction in the size of microstrip antenna by 4.04 %. Circular polarization radiation performance has been studied by size and angle variation of diagonally slotted structures. The experimental result found for 10-dB return loss is 44 MHz with 10MHz of 3dB Axial Ratio (AR bandwidth respectively at the resonant frequency 910 MHz. The overall proposed antenna size including the ground plane is 80 mm x 80 mm x 4.572 mm.

Influence of Closed Stator Slots on Cogging Torque

DEFF Research Database (Denmark)

Ion, Trifu; Leban, Krisztina Monika; Ritchie, Ewen

2013-01-01

Cogging torque results due interaction of magnetic field of magnets and stator slots, and have negative effects on permanent magnet machines such as vibrations, noise, torque ripples and problems during turbine start-up and cut-in. In order to reduce cogging torque this paper presents a study...... of influence of closed stator slots on cogging torque using magnetic slot wedges....

Optimization of multi-layered metallic shield

International Nuclear Information System (INIS)

Ben-Dor, G.; Dubinsky, A.; Elperin, T.

2011-01-01

Research highlights: → We investigated the problem of optimization of a multi-layered metallic shield. → The maximum ballistic limit velocity is a criterion of optimization. → The sequence of materials and the thicknesses of layers in the shield are varied. → The general problem is reduced to the problem of Geometric Programming. → Analytical solutions are obtained for two- and three-layered shields. - Abstract: We investigate the problem of optimization of multi-layered metallic shield whereby the goal is to determine the sequence of materials and the thicknesses of the layers that provide the maximum ballistic limit velocity of the shield. Optimization is performed under the following constraints: fixed areal density of the shield, the upper bound on the total thickness of the shield and the bounds on the thicknesses of the plates manufactured from every material. The problem is reduced to the problem of Geometric Programming which can be solved numerically using known methods. For the most interesting in practice cases of two-layered and three-layered shields the solution is obtained in the explicit analytical form.

Vertically Polarized Omnidirectional Printed Slot Loop Antenna

DEFF Research Database (Denmark)

Kammersgaard, Nikolaj Peter Iversen; Kvist, Søren H.; Thaysen, Jesper

2015-01-01

A novel vertically polarized omnidirectional printed slot loop antenna has been designed, simulated, fabricated and measured. The slot loop works as a magnetic loop. The loop is loaded with inductors to insure uniform and in-phase fields in the slot in order to obtain an omnidirectional radiation...... pattern. The antenna is designed for the 2.45 GHz Industrial, Scientific and Medical band. Applications of the antenna are many. One is for on-body applications since it is ideal for launching a creeping waves due to the polarization....

A procedure for multi-objective optimization of tire design parameters

OpenAIRE

Nikola Korunović; Miloš Madić; Miroslav Trajanović; Miroslav Radovanović

2015-01-01

The identification of optimal tire design parameters for satisfying different requirements, i.e. tire performance characteristics, plays an essential role in tire design. In order to improve tire performance characteristics, formulation and solving of multi-objective optimization problem must be performed. This paper presents a multi-objective optimization procedure for determination of optimal tire design parameters for simultaneous minimization of strain energy density at two distinctive zo...

G-tunnel pressurized slot-testing evaluations

International Nuclear Information System (INIS)

Zimmerman, R.M.; Sifre-Soto, C.; Mann, K.L.; Bellman, R.A. Jr.; Luker, S.; Dodds, D.J.

1992-04-01

Designers and analysts of radioactive waste repositories must be able to predict the mechanical behavior of the host rock. Sandia National Laboratories elected to conduct a development program to enhance mechanical-type measurements. The program was focused on pressurized slot testing and featured (1) development of an improved method to cut slots using a chain saw with diamond-tipped cutters, (2) measurements useful for determining in situ stresses normal to slots, (3) measurements applicable for determining the in situ modulus of deformation parallel to a drift surface, and (4) evaluations of pressurized slot strength testing results and methods. This report contains data interpretation and evaluations. Included are recommendations for future efforts. This third report contains the interpretations of the testing with emphasis on the measurement results as they apply to describing rock behavior. In particular, emphases are placed on (1) normal stress determinations using the flatjack cancellation (FC) method, (2) modulus of deformation determinations, and (3) high pressure investigations. Most of the material in the first two reports is not repeated here. Appropriate data are repeated in tabular form

Energy dissipation of slot-type flip buckets

Science.gov (United States)

Wu, Jian-hua; Li, Shu-fang; Ma, Fei

2018-03-01

The energy dissipation is a key index in the evaluation of energy dissipation elements. In the present work, a flip bucket with a slot, called the slot-type flip bucket, is theoretically and experimentally investigated by the method of estimating the energy dissipation. The theoretical analysis shows that, in order to have the energy dissipation, it is necessary to determine the sequent flow depth h 1 and the flow speed V 1 at the corresponding position through the flow depth h 2 after the hydraulic jump. The relative flow depth h 2 / h 。 is a function of the approach flow Froude number Fr 。, the relative slot width b/B 。, and the relative slot angle θ/β. The expression for estimating the energy dissipation is developed, and the maximum error is not larger than 9.21%.

Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units

Directory of Open Access Journals (Sweden)

Jinjiao Hou

2018-05-01

Full Text Available This paper proposes a multi-objective optimization method for the start-up strategy of pumped storage units (PSU for the first time. In the multi-objective optimization method, the speed rise time and the overshoot during the process of the start-up are taken as the objectives. A precise simulation platform is built for simulating the transient process of start-up, and for calculating the objectives based on the process. The Multi-objective Particle Swarm Optimization algorithm (MOPSO is adopted to optimize the widely applied start-up strategies based on one-stage direct guide vane control (DGVC, and two-stage DGVC. Based on the Pareto Front obtained, a multi-objective decision-making method based on the relative objective proximity is used to sort the solutions in the Pareto Front. Start-up strategy optimization for a PSU of a pumped storage power station in Jiangxi Province in China is conducted in experiments. The results show that: (1 compared with the single objective optimization, the proposed multi-objective optimization of start-up strategy not only greatly shortens the speed rise time and the speed overshoot, but also makes the speed curve quickly stabilize; (2 multi-objective optimization of strategy based on two-stage DGVC achieves better solution for a quick and smooth start-up of PSU than that of the strategy based on one-stage DGVC.

Deterministic methods for multi-control fuel loading optimization

Science.gov (United States)

Rahman, Fariz B. Abdul

We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.

49 CFR 236.809 - Signal, slotted mechanical.

Science.gov (United States)

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Signal, slotted mechanical. 236.809 Section 236.809 Transportation Other Regulations Relating to Transportation (Continued) FEDERAL RAILROAD... § 236.809 Signal, slotted mechanical. A mechanically operated signal with an electromagnetic device...

A Waveguide Transverse Broad Wall Slot Radiating Between Baffles

DEFF Research Database (Denmark)

Dich, Mikael; Rengarajan, S.R.

1997-01-01

An analysis of the self impedance of waveguide-fed transverse slots radiating between baffles is presented. The region exterior to the slot is treated as a parallel plate (PP) waveguide which radiates into half space through an aperture in an infinite ground plane. The slot problem is analyzed...

Multi-level iteration optimization for diffusive critical calculation

International Nuclear Information System (INIS)

Li Yunzhao; Wu Hongchun; Cao Liangzhi; Zheng Youqi

2013-01-01

In nuclear reactor core neutron diffusion calculation, there are usually at least three levels of iterations, namely the fission source iteration, the multi-group scattering source iteration and the within-group iteration. Unnecessary calculations occur if the inner iterations are converged extremely tight. But the convergence of the outer iteration may be affected if the inner ones are converged insufficiently tight. Thus, a common scheme suit for most of the problems was proposed in this work to automatically find the optimized settings. The basic idea is to optimize the relative error tolerance of the inner iteration based on the corresponding convergence rate of the outer iteration. Numerical results of a typical thermal neutron reactor core problem and a fast neutron reactor core problem demonstrate the effectiveness of this algorithm in the variational nodal method code NODAL with the Gauss-Seidel left preconditioned multi-group GMRES algorithm. The multi-level iteration optimization scheme reduces the number of multi-group and within-group iterations respectively by a factor of about 1-2 and 5-21. (authors)

Multi-Period Trading via Convex Optimization

DEFF Research Database (Denmark)

Boyd, Stephen; Busseti, Enzo; Diamond, Steve

2017-01-01

We consider a basic model of multi-period trading, which can be used to evaluate the performance of a trading strategy. We describe a framework for single-period optimization, where the trades in each period are found by solving a convex optimization problem that trades off expected return, risk......, transaction cost and holding cost such as the borrowing cost for shorting assets. We then describe a multi-period version of the trading method, where optimization is used to plan a sequence of trades, with only the first one executed, using estimates of future quantities that are unknown when the trades....... In this paper, we do not address a critical component in a trading algorithm, the predictions or forecasts of future quantities. The methods we describe in this paper can be thought of as good ways to exploit predictions, no matter how they are made. We have also developed a companion open-source software...

Rectangular-cladding silicon slot waveguide with improved nonlinear performance

Science.gov (United States)

Huang, Zengzhi; Huang, Qingzhong; Wang, Yi; Xia, Jinsong

2018-04-01

Silicon slot waveguides have great potential in hybrid silicon integration to realize nonlinear optical applications. We propose a rectangular-cladding hybrid silicon slot waveguide. Simulation result shows that, with a rectangular-cladding, the slot waveguide can be formed by narrower silicon strips, so the two-photon absorption (TPA) loss in silicon is decreased. When the cladding material is a nonlinear polymer, the calculated TPA figure of merit (FOMTPA) is 4.4, close to the value of bulk nonlinear polymer of 5.0. This value confirms the good nonlinear performance of rectangular-cladding silicon slot waveguides.

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

Science.gov (United States)

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

2002-06-01

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

Optimal unit sizing for small-scale integrated energy systems using multi-objective interval optimization and evidential reasoning approach

International Nuclear Information System (INIS)

Wei, F.; Wu, Q.H.; Jing, Z.X.; Chen, J.J.; Zhou, X.X.

2016-01-01

This paper proposes a comprehensive framework including a multi-objective interval optimization model and evidential reasoning (ER) approach to solve the unit sizing problem of small-scale integrated energy systems, with uncertain wind and solar energies integrated. In the multi-objective interval optimization model, interval variables are introduced to tackle the uncertainties of the optimization problem. Aiming at simultaneously considering the cost and risk of a business investment, the average and deviation of life cycle cost (LCC) of the integrated energy system are formulated. In order to solve the problem, a novel multi-objective optimization algorithm, MGSOACC (multi-objective group search optimizer with adaptive covariance matrix and chaotic search), is developed, employing adaptive covariance matrix to make the search strategy adaptive and applying chaotic search to maintain the diversity of group. Furthermore, ER approach is applied to deal with multiple interests of an investor at the business decision making stage and to determine the final unit sizing solution from the Pareto-optimal solutions. This paper reports on the simulation results obtained using a small-scale direct district heating system (DH) and a small-scale district heating and cooling system (DHC) optimized by the proposed framework. The results demonstrate the superiority of the multi-objective interval optimization model and ER approach in tackling the unit sizing problem of integrated energy systems considering the integration of uncertian wind and solar energies. - Highlights: • Cost and risk of investment in small-scale integrated energy systems are considered. • A multi-objective interval optimization model is presented. • A novel multi-objective optimization algorithm (MGSOACC) is proposed. • The evidential reasoning (ER) approach is used to obtain the final optimal solution. • The MGSOACC and ER can tackle the unit sizing problem efficiently.

Crest Level Optimization of the Multi Level Overtopping based Wave Energy Converter Seawave Slot-Cone Generator

DEFF Research Database (Denmark)

Kofoed, Jens Peter; Osaland, E.

2005-01-01

The paper describes the optimization of the crest levels and geometrical layout of the SSG structure, focusing on maximizing the obtained potential energy in the overtopping water. During wave tank testing at AAU average overtopping rates into the individual reservoirs have been measured. The ini......The paper describes the optimization of the crest levels and geometrical layout of the SSG structure, focusing on maximizing the obtained potential energy in the overtopping water. During wave tank testing at AAU average overtopping rates into the individual reservoirs have been measured....... The initial tests led to an expression describing the derivative of the overtopping rate with respect to the vertical distance. Based on this, numerical optimizations of the crest levels, for a number of combinations of wave conditions, have been performed. The hereby found optimal crest levels have been...

The Role of Auditory Features Within Slot-Themed Social Casino Games and Online Slot Machine Games.

Science.gov (United States)

Bramley, Stephanie; Gainsbury, Sally M

2015-12-01

Over the last few years playing social casino games has become a popular entertainment activity. Social casino games are offered via social media platforms and mobile apps and resemble gambling activities. However, social casino games are not classified as gambling as they can be played for free, outcomes may not be determined by chance, and players receive no monetary payouts. Social casino games appear to be somewhat similar to online gambling activities in terms of their visual and auditory features, but to date little research has investigated the cross over between these games. This study examines the auditory features of slot-themed social casino games and online slot machine games using a case study design. An example of each game type was played on three separate occasions during which, the auditory features (i.e., music, speech, sound effects, and the absence of sound) within the games were logged. The online slot-themed game was played in demo mode. This is the first study to provide a qualitative account of the role of auditory features within a slot-themed social casino game and an online slot machine game. Our results found many similarities between how sound is utilised within the two games. Therefore the sounds within these games may serve functions including: setting the scene for gaming, creating an image, demarcating space, interacting with visual features, prompting players to act, communicating achievements to players, providing reinforcement, heightening player emotions and the gaming experience. As a result this may reduce the ability of players to make a clear distinction between these two activities, which may facilitate migration between games.

Preliminary study for a nuclear multi-cycle reload optimization system

International Nuclear Information System (INIS)

Baptista, Rafael Pereira; Lima, Alan Miranda M. de; Medeiros, Jose Antonio Carlos Canedo; Schirru, Roberto

2007-01-01

Fuel assemblies in a reactor are discharged normally after several fuel cycles. This happens because of the concentration of fissile material existing in the fuel assemblies in the core decreases to values such that it is not more possible to keep the reactor operating producing energy at normal rated power. Therefore, the refueling optimization for a nuclear power plant is in fact a multi-cycle problem. A typical multi-cycle reload optimization depends on several kinds of relationships: one is the relationship between the locations where the fuel assemblies are placed for a specified fuel cycle; another is the relationship between fuel loading patterns for the subsequent fuel cycles. This makes the problem very complex and difficult to solve. Until the moment, all the presented proposals for solution are far from solving the multi-cycle optimization problems in reactor fuel management. In this work, we will show preliminary studies of possible solutions for a typical multi-cycle reload optimization problem trying to consider most important restrictions of a real model. In the initial comparisons, the optimization results will be compared with those obtained by the successive single cycle optimizations. (author)

Multi-objective optimal power flow with FACTS devices

International Nuclear Information System (INIS)

Basu, M.

2011-01-01

This paper presents multi-objective differential evolution to optimize cost of generation, emission and active power transmission loss of flexible ac transmission systems (FACTS) device-equipped power systems. In the proposed approach, optimal power flow problem is formulated as a multi-objective optimization problem. FACTS devices considered include thyristor controlled series capacitor (TCSC) and thyristor controlled phase shifter (TCPS). The proposed approach has been examined and tested on the modified IEEE 30-bus and 57-bus test systems. The results obtained from the proposed approach have been compared with those obtained from nondominated sorting genetic algorithm-II, strength pareto evolutionary algorithm 2 and pareto differential evolution.

Optimization of Fuel Consumption and Emissions for Auxiliary Power Unit Based on Multi-Objective Optimization Model

Directory of Open Access Journals (Sweden)

Yongpeng Shen

2016-02-01

Full Text Available Auxiliary power units (APUs are widely used for electric power generation in various types of electric vehicles, improvements in fuel economy and emissions of these vehicles directly depend on the operating point of the APUs. In order to balance the conflicting goals of fuel consumption and emissions reduction in the process of operating point choice, the APU operating point optimization problem is formulated as a constrained multi-objective optimization problem (CMOP firstly. The four competing objectives of this CMOP are fuel-electricity conversion cost, hydrocarbon (HC emissions, carbon monoxide (CO emissions and nitric oxide (NO x emissions. Then, the multi-objective particle swarm optimization (MOPSO algorithm and weighted metric decision making method are employed to solve the APU operating point multi-objective optimization model. Finally, bench experiments under New European driving cycle (NEDC, Federal test procedure (FTP and high way fuel economy test (HWFET driving cycles show that, compared with the results of the traditional fuel consumption single-objective optimization approach, the proposed multi-objective optimization approach shows significant improvements in emissions performance, at the expense of a slight drop in fuel efficiency.

Aida-CMK multi-algorithm optimization kernel applied to analog IC sizing

CERN Document Server

Lourenço, Ricardo; Horta, Nuno

2015-01-01

This work addresses the research and development of an innovative optimization kernel applied to analog integrated circuit (IC) design. Particularly, this works describes the modifications inside the AIDA Framework, an electronic design automation framework fully developed by at the Integrated Circuits Group-LX of the Instituto de Telecomunicações, Lisbon. It focusses on AIDA-CMK, by enhancing AIDA-C, which is the circuit optimizer component of AIDA, with a new multi-objective multi-constraint optimization module that constructs a base for multiple algorithm implementations. The proposed solution implements three approaches to multi-objective multi-constraint optimization, namely, an evolutionary approach with NSGAII, a swarm intelligence approach with MOPSO and stochastic hill climbing approach with MOSA. Moreover, the implemented structure allows the easy hybridization between kernels transforming the previous simple NSGAII optimization module into a more evolved and versatile module supporting multiple s...

[Influence of slot size on torque control].

Science.gov (United States)

Tian, Jun; Liu, Zhong-Hao; Zhang, Ding; Wu, Chuan-Jun

2009-12-01

To study the influence of two slot size brackets on torque control when teeth interacted in the same arch. After the upper arch was aligned and leveled in Typodont study, the inclinations of upper teeth 5 +/- 5 were measured when 0.457 2 mm x 0.635 0 mm OPA-K brackets and 0.558 8 mmx0.711 2 mm OPA-K brackets were filled with 0.431 8 mm x 0.635 0 mm stainless steel wire. This experiment was duplicated 10 times. The inclin of each tooth were transformed to the absolute values of the torque play angle psi by computing program, and paired-t test was used. The two kinds of slot size brackets were different with statistical significance on torque control. When the brackets were filled with 0.431 8 mm x 0.635 0 mm stainless steel wire, the absolute values of the angle psi in 0.558 8 mm x 0.711 2 mm and 0.457 2 mm x 0.635 0 mm slot size brackets were 6.140 degrees +/- 3.758 degrees and 2.608 degrees +/- 1.479 degrees respectively, and the average difference of that between the two slot size brackets was 3.532 degrees. The absolute values of the angle psi in the upper left and right canine brackets were 2.560 degrees +/- 2.605 degrees, 4.230 degrees +/- 2.817 degrees, 1.260 degrees +/- 0.747 degrees and 2.070 degrees +/- 0.663 degrees respectively, and average differences between them were smaller than that in the other teeth. There was difference between the two kinds of slot size brackets on torque control, and 0.457 2 mm x 0.635 0 mm slot size bracket controls torque better when filled with the same size wire. In this study, the teeth interaction in the same arch probably caused the result that the difference of two slot size brackets on torque control was less than the study results of the theory calculations and material studys before.

Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

Science.gov (United States)

Cao, Jia; Yan, Zheng; He, Guangyu

2016-06-01

This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

The Gambling Reducing Slot Machine

DEFF Research Database (Denmark)

Callesen, Mette Buhl; Thomsen, Kristine Rømer; Linnet, Jakob

2007-01-01

  The Gambling Reducing Slot Machine - Preliminary results Mette Buhl Callesen, Kristine Rømer Thomsen, Jakob Linnet and Arne Møller The PET Centre, Aarhus University Hospital and Centre of Functionally Integrative Neuroscience, Aarhus, Denmark   Slot machines are among the most addictive forms...... and willingness to continue gambling. The results may have important implications for understanding how to reduce gambling behavior in pathological gamblers.   [1] Griffiths, M. 1999. Gambling Technologies: Prospects for Problem Gambling. Journal of Gambling Studies, vol. 15(3), pp. 265-283.    ...

Theory of a Traveling Wave Feed for a Planar Slot Array Antenna

Science.gov (United States)

Rengarajan, Sembiam

2012-01-01

Planar arrays of waveguide-fed slots have been employed in many radar and remote sensing applications. Such arrays are designed in the standing wave configuration because of high efficiency. Traveling wave arrays can produce greater bandwidth at the expense of efficiency due to power loss in the load or loads. Traveling wave planar slot arrays may be designed with a long feed waveguide consisting of centered-inclined coupling slots. The feed waveguide is terminated in a matched load, and the element spacing in the feed waveguide is chosen to produce a beam squinted from the broadside. The traveling wave planar slot array consists of a long feed waveguide containing resonant-centered inclined coupling slots in the broad wall, coupling power into an array of stacked radiating waveguides orthogonal to it. The radiating waveguides consist of longitudinal offset radiating slots in a standing wave configuration. For the traveling wave feed of a planar slot array, one has to design the tilt angle and length of each coupling slot such that the amplitude and phase of excitation of each radiating waveguide are close to the desired values. The coupling slot spacing is chosen for an appropriate beam squint. Scattering matrix parameters of resonant coupling slots are used in the design process to produce appropriate excitations of radiating waveguides with constraints placed only on amplitudes. Since the radiating slots in each radiating waveguide are designed to produce a certain total admittance, the scattering (S) matrix of each coupling slot is reduced to a 2x2 matrix. Elements of each 2x2 S-matrix and the amount of coupling into the corresponding radiating waveguide are expressed in terms of the element S11. S matrices are converted into transmission (T) matrices, and the T matrices are multiplied to cascade the coupling slots and waveguide sections, starting from the load end and proceeding towards the source. While the use of non-resonant coupling slots may provide an

A solution to the optimal power flow using multi-verse optimizer

Directory of Open Access Journals (Sweden)

Bachir Bentouati

2016-12-01

Full Text Available In this work, the most common problem of the modern power system named optimal power flow (OPF is optimized using the novel meta-heuristic optimization Multi-verse Optimizer(MVO algorithm. In order to solve the optimal power flow problem, the IEEE 30-bus and IEEE 57-bus systems are used. MVO is applied to solve the proposed problem. The problems considered in the OPF problem are fuel cost reduction, voltage profile improvement, voltage stability enhancement. The obtained results are compared with recently published meta-heuristics. Simulation results clearly reveal the effectiveness and the rapidity of the proposed algorithm for solving the OPF problem.

Radiation from a Slot System in the Coaxial Line Shield

Science.gov (United States)

Katrich, V. A.; Lyashchenko, V. A.; Medvedev, N. V.

2012-06-01

The problem of electromagnetic wave excitation, scattering and radiation by the system of transverse slots, cut in the outer conductor of an infinite coaxial line, is solved by the magnetomotive forces method. The radiation and reflection coefficients of the circular and arc slot systems are investigated in dependence on slot sizes and feeder parameters. The processes of radiation into lossy material media are studied. The researches have been carried out with the interconnection between slots of internal and external regions considered.

Design of a centrifugal compressor impeller using multi-objective optimization algorithm

International Nuclear Information System (INIS)

Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong; Choi, Jae Ho

2009-01-01

This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with ε-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.

Design of a centrifugal compressor impeller using multi-objective optimization algorithm

Energy Technology Data Exchange (ETDEWEB)

Kim, Jin Hyuk; Husain, Afzal; Kim, Kwang Yong [Inha University, Incheon (Korea, Republic of); Choi, Jae Ho [Samsung Techwin Co., Ltd., Changwon (Korea, Republic of)

2009-07-01

This paper presents a design optimization of a centrifugal compressor impeller with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by finite volume approximations and solved on hexahedral grids for flow analyses. Two objectives, i.e., isentropic efficiency and total pressure ratio are selected with four design variables defining impeller hub and shroud contours in meridional contours to optimize the system. Non-dominated Sorting of Genetic Algorithm (NSGA-II) with {epsilon}-constraint strategy for local search coupled with Radial Basis Neural Network model is used for multi-objective optimization. The optimization results show that isentropic efficiencies and total pressure ratios of the five cluster points at the Pareto-optimal solutions are enhanced by multi-objective optimization.

A multi-objective optimization problem for multi-state series-parallel systems: A two-stage flow-shop manufacturing system

International Nuclear Information System (INIS)

Azadeh, A.; Maleki Shoja, B.; Ghanei, S.; Sheikhalishahi, M.

2015-01-01

This research investigates a redundancy-scheduling optimization problem for a multi-state series parallel system. The system is a flow shop manufacturing system with multi-state machines. Each manufacturing machine may have different performance rates including perfect performance, decreased performance and complete failure. Moreover, warm standby redundancy is considered for the redundancy allocation problem. Three objectives are considered for the problem: (1) minimizing system purchasing cost, (2) minimizing makespan, and (3) maximizing system reliability. Universal generating function is employed to evaluate system performance and overall reliability of the system. Since the problem is in the NP-hard class of combinatorial problems, genetic algorithm (GA) is used to find optimal/near optimal solutions. Different test problems are generated to evaluate the effectiveness and efficiency of proposed approach and compared to simulated annealing optimization method. The results show the proposed approach is capable of finding optimal/near optimal solution within a very reasonable time. - Highlights: • A redundancy-scheduling optimization problem for a multi-state series parallel system. • A flow shop with multi-state machines and warm standby redundancy. • Objectives are to optimize system purchasing cost, makespan and reliability. • Different test problems are generated and evaluated by a unique genetic algorithm. • It locates optimal/near optimal solution within a very reasonable time

Optimal Energy Management of Multi-Microgrids with Sequentially Coordinated Operations

Directory of Open Access Journals (Sweden)

Nah-Oak Song

2015-08-01

Full Text Available We propose an optimal electric energy management of a cooperative multi-microgrid community with sequentially coordinated operations. The sequentially coordinated operations are suggested to distribute computational burden and yet to make the optimal 24 energy management of multi-microgrids possible. The sequential operations are mathematically modeled to find the optimal operation conditions and illustrated with physical interpretation of how to achieve optimal energy management in the cooperative multi-microgrid community. This global electric energy optimization of the cooperative community is realized by the ancillary internal trading between the microgrids in the cooperative community which reduces the extra cost from unnecessary external trading by adjusting the electric energy production amounts of combined heat and power (CHP generators and amounts of both internal and external electric energy trading of the cooperative community. A simulation study is also conducted to validate the proposed mathematical energy management models.

Optimal allocation of SVC and TCSC using quasi-oppositional chemical reaction optimization for solving multi-objective ORPD problem

Directory of Open Access Journals (Sweden)

Susanta Dutta

2018-05-01

Full Text Available This paper presents an efficient quasi-oppositional chemical reaction optimization (QOCRO technique to find the feasible optimal solution of the multi objective optimal reactive power dispatch (RPD problem with flexible AC transmission system (FACTS device. The quasi-oppositional based learning (QOBL is incorporated in conventional chemical reaction optimization (CRO, to improve the solution quality and the convergence speed. To check the superiority of the proposed method, it is applied on IEEE 14-bus and 30-bus systems and the simulation results of the proposed approach are compared to those reported in the literature. The computational results reveal that the proposed algorithm has excellent convergence characteristics and is superior to other multi objective optimization algorithms. Keywords: Quasi-oppositional chemical reaction optimization (QOCRO, Reactive power dispatch (RPD, TCSC, SVC, Multi-objective optimization

Investigation of a slot nanoantenna in optical frequency range

Science.gov (United States)

Dinesh kumar, V.; Asakawa, Kiyoshi

2009-11-01

Following the analogy of radio frequency slot antenna and its complementary dipole, we propose the implementation of a slot nanoantenna (SNA) in the optical frequency range. Using finite-difference time-domain (FDTD) method, we investigate the electromagnetic (EM) properties of a SNA formed in a thin gold film and compare the results with the properties of a gold dipole nanoantenna (DNA) of the same dimension as the slot. It is found that the response of the SNA is very similar to the DNA, like their counterparts in the radio frequency (RF) range. The SNA can enhance the near field intensity of incident field which strongly depends on its feedgap dimension. The resonance of the SNA is influenced by its slot length; for the increasing slot length, resonant frequency decreases whereas the sharpness of resonance increases. Besides, the resonance of the SNA is found sensitive to the thickness of metal film, when the latter is smaller than the skin depth. The effect of polarization of incident field on the EM response of the SNA was examined; the field enhancement is optimum when polarization is parallel to the feedgap. Finally, we calculate the radiation patterns of the DNA and SNA and compare them with those of the RF dipole antenna. The radiation pattern of the SNA is found to be independent of its slot length when excited at resonant frequency. To the best of our knowledge, this is the first study on a slot antenna in the optical frequency.

Metal membrane with dimer slots as a universal polarizer

Science.gov (United States)

Zhukovsky, Sergej; Zalkovskij, Maksim; Malureanu, Radu; Kremers, Christian; Chigrin, Dmitry; Tang, Peter T.; Jepsen, Peter U.; Lavrinenko, Andrei V.

2014-03-01

In this work, we show theoretically and confirm experimentally that thin metal membranes patterned with an array of slot dimers (or their Babinet analogue with metal rods) can function as a versatile spectral and polarization filter. We present a detailed covariant multipole theory for the electromagnetic response of an arbitrary dimer based on the Green functions approach. The theory confirms that a great variety of polarization properties, such as birefringence, chirality and elliptical dichroism, can be achieved in a metal layer with such slot-dimer patterning (i.e. in a metasurface). Optical properties of the metasurface can be extensively tuned by varying the geometry (shape and dimensions) of the dimer, for example, by adjusting the sizes and mutual placement of the slots (e.g. inter-slot distance and alignment angle). Three basic shapes of dimers are analyzed: II-shaped (parallel slots), V-shaped, and T-shaped. These particular shapes of dimers are found to be sensitive to variations of the slots lengths and orientation of elements. Theoretical results are well supported by full-wave three-dimensional simulations. Our findings were verified experimentally on the metal membranes fabricated using UV lithography with subsequent Ni growth. Such metasurfaces were characterized using time-domain THz spectroscopy. The samples exhibit pronounced optical activity (500 degrees per wavelength) and high transmission: even though the slots cover only 4.3 % of the total membrane area the amplitude transmission reaches 0.67 at the resonance frequency 0.56 THz.

Humanizing machines: Anthropomorphization of slot machines increases gambling.

Science.gov (United States)

Riva, Paolo; Sacchi, Simona; Brambilla, Marco

2015-12-01

Do people gamble more on slot machines if they think that they are playing against humanlike minds rather than mathematical algorithms? Research has shown that people have a strong cognitive tendency to imbue humanlike mental states to nonhuman entities (i.e., anthropomorphism). The present research tested whether anthropomorphizing slot machines would increase gambling. Four studies manipulated slot machine anthropomorphization and found that exposing people to an anthropomorphized description of a slot machine increased gambling behavior and reduced gambling outcomes. Such findings emerged using tasks that focused on gambling behavior (Studies 1 to 3) as well as in experimental paradigms that included gambling outcomes (Studies 2 to 4). We found that gambling outcomes decrease because participants primed with the anthropomorphic slot machine gambled more (Study 4). Furthermore, we found that high-arousal positive emotions (e.g., feeling excited) played a role in the effect of anthropomorphism on gambling behavior (Studies 3 and 4). Our research indicates that the psychological process of gambling-machine anthropomorphism can be advantageous for the gaming industry; however, this may come at great expense for gamblers' (and their families') economic resources and psychological well-being. (c) 2015 APA, all rights reserved).

Flexural and Thermal Properties of Novel Energy Conservation Slotted Reinforced Concrete Beams

Directory of Open Access Journals (Sweden)

Gao Ma

2016-01-01

Full Text Available Conventional solid reinforced concrete (RC beams were modified to slotted beams for consideration as thermal insulation structural components. The slotted beam consisted of an outer and an inner beam, respectively, with a slot located near the middle of the beam along its width direction for filling thermal insulation material. Flexural and thermal behavior of the slotted beams were investigated. Three RC reference solid beams and six slotted beams were fabricated and tested under four-point bending tests. The test results indicated that the failure mode of both slotted beams and the solid beams was flexural failure. However, the damage process of the slotted beams was different from that of the solid beams at the final loading stage. The moment curvature analysis indicated that the tensile reinforcement ratio of the outer and inner beams had an important effect on the flexural behavior, especially the ductility of the slotted beams. Thermal study indicated that the heat transfer coefficient of the slotted beam was greatly reduced and the thermal inertia factor increased a lot, compared with the solid beam. In addition, FE simulation results showed that a new frame structure using slotted beams exhibited obvious and attractive thermal insulation property.

Light scattering of rectangular slot antennas: parallel magnetic vector vs perpendicular electric vector

Science.gov (United States)

Lee, Dukhyung; Kim, Dai-Sik

2016-01-01

We study light scattering off rectangular slot nano antennas on a metal film varying incident polarization and incident angle, to examine which field vector of light is more important: electric vector perpendicular to, versus magnetic vector parallel to the long axis of the rectangle. While vector Babinet’s principle would prefer magnetic field along the long axis for optimizing slot antenna function, convention and intuition most often refer to the electric field perpendicular to it. Here, we demonstrate experimentally that in accordance with vector Babinet’s principle, the incident magnetic vector parallel to the long axis is the dominant component, with the perpendicular incident electric field making a small contribution of the factor of 1/|ε|, the reciprocal of the absolute value of the dielectric constant of the metal, owing to the non-perfectness of metals at optical frequencies.

Analysis and design of broadband U-slot cut rectangular microstrip ...

Indian Academy of Sciences (India)

AMIT A DESHMUKH

2017-07-15

Jul 15, 2017 ... Abstract. Broadband microstrip antenna using variations of U-slot has been widely reported. However, in most of the reported work, an in-depth explanation about the mode introduced by U-slot and procedure to design. U-slot cut antennas at any given frequency is not explained. In this paper, first an ...

Optimal maintenance of multi-component systems: a review

NARCIS (Netherlands)

R.P. Nicolai (Robin); R. Dekker (Rommert)

2006-01-01

textabstractIn this article we give an overview of the literature on multi-component maintenance optimization. We focus on work appearing since the 1991 survey "A survey of maintenance models for multi-unit systems" by Cho and Parlar. This paper builds forth on the review article by Dekker et al.

Optimization of externalities using DTM measures: a Pareto optimal multi objective optimization using the evolutionary algorithm SPEA2+

NARCIS (Netherlands)

Wismans, Luc Johannes Josephus; van Berkum, Eric C.; Bliemer, Michiel; Allkim, T.P.; van Arem, Bart

2010-01-01

Multi objective optimization of externalities of traffic is performed solving a network design problem in which Dynamic Traffic Management measures are used. The resulting Pareto optimal set is determined by employing the SPEA2+ evolutionary algorithm.

Design and optimization of flexible multi-generation systems

DEFF Research Database (Denmark)

Lythcke-Jørgensen, Christoffer Ernst

variations and dynamics, and energy system analysis, which fails to consider process integration synergies in local systems. The primary objective of the thesis is to derive a methodology for linking process design practices with energy system analysis for enabling coherent and holistic design optimization...... of flexible multi-generation system. In addition, the case study results emphasize the importance of considering flexible operation, systematic process integration, and systematic assessment of uncertainties in the design optimization. It is recommended that future research focus on assessing system impacts...... from flexible multi-generation systems and performance improvements from storage options....

METHOD FOR OPTIMAL RESOLUTION OF MULTI-AIRCRAFT CONFLICTS IN THREE-DIMENSIONAL SPACE

Directory of Open Access Journals (Sweden)

Denys Vasyliev

2017-03-01

Full Text Available Purpose: The risk of critical proximities of several aircraft and appearance of multi-aircraft conflicts increases under current conditions of high dynamics and density of air traffic. The actual problem is a development of methods for optimal multi-aircraft conflicts resolution that should provide the synthesis of conflict-free trajectories in three-dimensional space. Methods: The method for optimal resolution of multi-aircraft conflicts using heading, speed and altitude change maneuvers has been developed. Optimality criteria are flight regularity, flight economy and the complexity of maneuvering. Method provides the sequential synthesis of the Pareto-optimal set of combinations of conflict-free flight trajectories using multi-objective dynamic programming and selection of optimal combination using the convolution of optimality criteria. Within described method the following are defined: the procedure for determination of combinations of aircraft conflict-free states that define the combinations of Pareto-optimal trajectories; the limitations on discretization of conflict resolution process for ensuring the absence of unobservable separation violations. Results: The analysis of the proposed method is performed using computer simulation which results show that synthesized combination of conflict-free trajectories ensures the multi-aircraft conflict avoidance and complies with defined optimality criteria. Discussion: Proposed method can be used for development of new automated air traffic control systems, airborne collision avoidance systems, intelligent air traffic control simulators and for research activities.

Exergoeconomic multi objective optimization and sensitivity analysis of a regenerative Brayton cycle

International Nuclear Information System (INIS)

Naserian, Mohammad Mahdi; Farahat, Said; Sarhaddi, Faramarz

2016-01-01

Highlights: • Finite time exergoeconomic multi objective optimization of a Brayton cycle. • Comparing the exergoeconomic and the ecological function optimization results. • Inserting the cost of fluid streams concept into finite-time thermodynamics. • Exergoeconomic sensitivity analysis of a regenerative Brayton cycle. • Suggesting the cycle performance curve drawing and utilization. - Abstract: In this study, the optimal performance of a regenerative Brayton cycle is sought through power maximization and then exergoeconomic optimization using finite-time thermodynamic concept and finite-size components. Optimizations are performed using genetic algorithm. In order to take into account the finite-time and finite-size concepts in current problem, a dimensionless mass-flow parameter is used deploying time variations. The decision variables for the optimum state (of multi objective exergoeconomic optimization) are compared to the maximum power state. One can see that the multi objective exergoeconomic optimization results in a better performance than that obtained with the maximum power state. The results demonstrate that system performance at optimum point of multi objective optimization yields 71% of the maximum power, but only with exergy destruction as 24% of the amount that is produced at the maximum power state and 67% lower total cost rate than that of the maximum power state. In order to assess the impact of the variation of the decision variables on the objective functions, sensitivity analysis is conducted. Finally, the cycle performance curve drawing according to exergoeconomic multi objective optimization results and its utilization, are suggested.

A scalable coevolutionary multi-objective particle swarm optimizer

Directory of Open Access Journals (Sweden)

Xiangwei Zheng

2010-11-01

Full Text Available Multi-Objective Particle Swarm Optimizers (MOPSOs are easily trapped in local optima, cost more function evaluations and suffer from the curse of dimensionality. A scalable cooperative coevolution and ?-dominance based MOPSO (CEPSO is proposed to address these issues. In CEPSO, Multi-objective Optimization Problems (MOPs are decomposed in terms of their decision variables and are optimized by cooperative coevolutionary subswarms, and a uniform distribution mutation operator is adopted to avoid premature convergence. All subswarms share an external archive based on ?-dominance, which is also used as a leader set. Collaborators are selected from the archive and used to construct context vectors in order to evaluate particles in a subswarm. CEPSO is tested on several classical MOP benchmark functions and experimental results show that CEPSO can readily escape from local optima and optimize both low and high dimensional problems, but the number of function evaluations only increases linearly with respect to the number of decision variables. Therefore, CEPSO is competitive in solving various MOPs.

Uncertain and multi-objective programming models for crop planting structure optimization

Directory of Open Access Journals (Sweden)

Mo LI,Ping GUO,Liudong ZHANG,Chenglong ZHANG

2016-03-01

Full Text Available Crop planting structure optimization is a significant way to increase agricultural economic benefits and improve agricultural water management. The complexities of fluctuating stream conditions, varying economic profits, and uncertainties and errors in estimated modeling parameters, as well as the complexities among economic, social, natural resources and environmental aspects, have led to the necessity of developing optimization models for crop planting structure which consider uncertainty and multi-objectives elements. In this study, three single-objective programming models under uncertainty for crop planting structure optimization were developed, including an interval linear programming model, an inexact fuzzy chance-constrained programming (IFCCP model and an inexact fuzzy linear programming (IFLP model. Each of the three models takes grayness into account. Moreover, the IFCCP model considers fuzzy uncertainty of parameters/variables and stochastic characteristics of constraints, while the IFLP model takes into account the fuzzy uncertainty of both constraints and objective functions. To satisfy the sustainable development of crop planting structure planning, a fuzzy-optimization-theory-based fuzzy linear multi-objective programming model was developed, which is capable of reflecting both uncertainties and multi-objective. In addition, a multi-objective fractional programming model for crop structure optimization was also developed to quantitatively express the multi-objective in one optimization model with the numerator representing maximum economic benefits and the denominator representing minimum crop planting area allocation. These models better reflect actual situations, considering the uncertainties and multi-objectives of crop planting structure optimization systems. The five models developed were then applied to a real case study in Minqin County, north-west China. The advantages, the applicable conditions and the solution methods

Demonstration of slot-waveguide structures on silicon nitride / silicon oxide platform.

Science.gov (United States)

Barrios, C A; Sánchez, B; Gylfason, K B; Griol, A; Sohlström, H; Holgado, M; Casquel, R

2007-05-28

We report on the first demonstration of guiding light in vertical slot-waveguides on silicon nitride/silicon oxide material system. Integrated ring resonators and Fabry-Perot cavities have been fabricated and characterized in order to determine optical features of the slot-waveguides. Group index behavior evidences guiding and confinement in the low-index slot region at O-band (1260-1370nm) telecommunication wavelengths. Propagation losses of <20 dB/cm have been measured for the transverse-electric mode of the slot-waveguides.

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.

Optimal Multi-Level Lot Sizing for Requirements Planning Systems

OpenAIRE

Earle Steinberg; H. Albert Napier

1980-01-01

The wide spread use of advanced information systems such as Material Requirements Planning (MRP) has significantly altered the practice of dependent demand inventory management. Recent research has focused on development of multi-level lot sizing heuristics for such systems. In this paper, we develop an optimal procedure for the multi-period, multi-product, multi-level lot sizing problem by modeling the system as a constrained generalized network with fixed charge arcs and side constraints. T...

Optimization of multi-phase compressible lattice Boltzmann codes on massively parallel multi-core systems

NARCIS (Netherlands)

Biferale, L.; Mantovani, F.; Pivanti, M.; Pozzati, F.; Sbragaglia, M.; Schifano, S.F.; Toschi, F.; Tripiccione, R.

2011-01-01

We develop a Lattice Boltzmann code for computational fluid-dynamics and optimize it for massively parallel systems based on multi-core processors. Our code describes 2D multi-phase compressible flows. We analyze the performance bottlenecks that we find as we gradually expose a larger fraction of

A Constraint Programming Model for Fast Optimal Stowage of Container Vessel Bays

DEFF Research Database (Denmark)

Delgado-Ortegon, Alberto; Jensen, Rune Møller; Janstrup, Kira

2012-01-01

Container vessel stowage planning is a hard combinatorial optimization problem with both high economic and environmental impact. We have developed an approach that often is able to generate near-optimal plans for large container vessels within a few minutes. It decomposes the problem into a master...... planning phase that distributes the containers to bay sections and a slot planning phase that assigns containers of each bay section to slots. In this paper, we focus on the slot planning phase of this approach and present a constraint programming and integer programming model for stowing a set...... of containers in a single bay section. This so-called slot planning problem is NP-hard and often involves stowing several hundred containers. Using state-of-the-art constraint solvers and modeling techniques, however, we were able to solve 90% of 236 real instances from our industrial collaborator to optimality...

Paper-based inkjet-printed tri-band U-slot monopole antenna for wireless applications

KAUST Repository

Abutarboush, Hattan

2012-01-01

Realization of a U-slot tri-band monopole antenna on a low-cost paper substrate using inkjet-printed technology is presented for the first time. The U-shaped slot is optimized to enhance the bandwidth and to achieve tri-band operation of 1.57, 3.2, and 5 GHz with measured impedance bandwidths of 3.21%, 28.1%, and 36%, respectively. The antenna is fabricated through a metallic nanoparticle ink on a standard commercial paper. Thus, the antenna can be used to cover the GPS, WiMAX, HiperLAN/2, and WLAN. The antenna has a compact size of 12 × 37.3 × 0.44 mm3 , leaving enough space for the driving electronics on the paper substrate. The impedance bandwidth, current distributions, radiation patterns, gain, and efficiency of the antenna have been studied through computer simulations and measurements. © 2002-2011 IEEE.

Multi-Objective Optimization of Managed Aquifer Recharge.

Science.gov (United States)

Fatkhutdinov, Aybulat; Stefan, Catalin

2018-04-27

This study demonstrates the utilization of a multi-objective hybrid global/local optimization algorithm for solving managed aquifer recharge (MAR) design problems, in which the decision variables included spatial arrangement of water injection and abstraction wells and time-variant rates of pumping and injection. The objective of the optimization was to maximize the efficiency of the MAR scheme, which includes both quantitative and qualitative aspects. The case study used to demonstrate the capabilities of the proposed approach is based on a published report on designing a real MAR site with defined aquifer properties, chemical groundwater characteristics as well as quality and volumes of injected water. The demonstration problems include steady-state and transient scenarios. The steady-state scenario demonstrates optimization of spatial arrangement of multiple injection and recovery wells, whereas the transient scenario was developed with the purpose of finding optimal regimes of water injection and recovery at a single location. Both problems were defined as multi-objective problems. The scenarios were simulated by applying coupled numerical groundwater flow and solute transport models: MODFLOW-2005 and MT3D-USGS. The applied optimization method was a combination of global - the Non-Dominated Sorting Genetic Algorithm (NSGA-2), and local - the Nelder-Mead Downhill Simplex search algorithms. The analysis of the resulting Pareto optimal solutions led to the discovery of valuable patterns and dependencies between the decision variables, model properties and problem objectives. Additionally, the performance of the traditional global and the hybrid optimization schemes were compared. This article is protected by copyright. All rights reserved.

Multi-objective based on parallel vector evaluated particle swarm optimization for optimal steady-state performance of power systems

DEFF Research Database (Denmark)

Vlachogiannis, Ioannis (John); Lee, K Y

2009-01-01

In this paper the state-of-the-art extended particle swarm optimization (PSO) methods for solving multi-objective optimization problems are represented. We emphasize in those, the co-evolution technique of the parallel vector evaluated PSO (VEPSO), analysed and applied in a multi-objective problem...

FDTD Analysis of U-Slot Rectangular Patch Antenna

Science.gov (United States)

Luk, K. M.; Tong, K. F.; Shum, S. M.; Lee, K. F.; Lee, R. Q.

1997-01-01

The U-slot rectangular patch antenna (Figure I) has been found experimentally to provide impedance and gain bandwidths of about 300 without the need of stacked or coplanar parasitic elements [1,2]. In this paper, simulation results of the U-slot patch using FDTD analysis are presented. Comparison with measured results are given.

Optimization of Multiple Related Negotiation through Multi-Negotiation Network

Science.gov (United States)

Ren, Fenghui; Zhang, Minjie; Miao, Chunyan; Shen, Zhiqi

In this paper, a Multi-Negotiation Network (MNN) and a Multi- Negotiation Influence Diagram (MNID) are proposed to optimally handle Multiple Related Negotiations (MRN) in a multi-agent system. Most popular, state-of-the-art approaches perform MRN sequentially. However, a sequential procedure may not optimally execute MRN in terms of maximizing the global outcome, and may even lead to unnecessary losses in some situations. The motivation of this research is to use a MNN to handle MRN concurrently so as to maximize the expected utility of MRN. Firstly, both the joint success rate and the joint utility by considering all related negotiations are dynamically calculated based on a MNN. Secondly, by employing a MNID, an agent's possible decision on each related negotiation is reflected by the value of expected utility. Lastly, through comparing expected utilities between all possible policies to conduct MRN, an optimal policy is generated to optimize the global outcome of MRN. The experimental results indicate that the proposed approach can improve the global outcome of MRN in a successful end scenario, and avoid unnecessary losses in an unsuccessful end scenario.

A Photonic 1 × 4 Power Splitter Based on Multimode Interference in Silicon-Gallium-Nitride Slot Waveguide Structures.

Science.gov (United States)

Malka, Dror; Danan, Yossef; Ramon, Yehonatan; Zalevsky, Zeev

2016-06-25

In this paper, a design for a 1 × 4 optical power splitter based on the multimode interference (MMI) coupler in a silicon (Si)-gallium nitride (GaN) slot waveguide structure is presented-to our knowledge, for the first time. Si and GaN were found as suitable materials for the slot waveguide structure. Numerical optimizations were carried out on the device parameters using the full vectorial-beam propagation method (FV-BPM). Simulation results show that the proposed device can be useful to divide optical signal energy uniformly in the C-band range (1530-1565 nm) into four output ports with low insertion losses (0.07 dB).

Multi-Objective Optimization for Energy Performance Improvement of Residential Buildings: A Comparative Study

Directory of Open Access Journals (Sweden)

Kangji Li

2017-02-01

Full Text Available Numerous conflicting criteria exist in building design optimization, such as energy consumption, greenhouse gas emission and indoor thermal performance. Different simulation-based optimization strategies and various optimization algorithms have been developed. A few of them are analyzed and compared in solving building design problems. This paper presents an efficient optimization framework to facilitate optimization designs with the aid of commercial simulation software and MATLAB. The performances of three optimization strategies, including the proposed approach, GenOpt method and artificial neural network (ANN method, are investigated using a case study of a simple building energy model. Results show that the proposed optimization framework has competitive performances compared with the GenOpt method. Further, in another practical case, four popular multi-objective algorithms, e.g., the non-dominated sorting genetic algorithm (NSGA-II, multi-objective particle swarm optimization (MOPSO, the multi-objective genetic algorithm (MOGA and multi-objective differential evolution (MODE, are realized using the propose optimization framework and compared with three criteria. Results indicate that MODE achieves close-to-optimal solutions with the best diversity and execution time. An uncompetitive result is achieved by the MOPSO in this case study.

Pole Shape Optimization of Permanent Magnet Synchronous Motors Using the Reduced Basis Technique

Directory of Open Access Journals (Sweden)

A. Jabbari

2010-03-01

Full Text Available In the present work, an integrated method of pole shape design optimization for reduction of torque pulsation components in permanent magnet synchronous motors is developed. A progressive design process is presented to find feasible optimal shapes. This method is applied on the pole shape optimization of two prototype permanent magnet synchronous motors, i.e., 4-poles/6-slots and 4-poles-12slots.

Interactive Preference Learning of Utility Functions for Multi-Objective Optimization

OpenAIRE

Dewancker, Ian; McCourt, Michael; Ainsworth, Samuel

2016-01-01

Real-world engineering systems are typically compared and contrasted using multiple metrics. For practical machine learning systems, performance tuning is often more nuanced than minimizing a single expected loss objective, and it may be more realistically discussed as a multi-objective optimization problem. We propose a novel generative model for scalar-valued utility functions to capture human preferences in a multi-objective optimization setting. We also outline an interactive active learn...

Multi-objective genetic optimization of linear construction projects

Directory of Open Access Journals (Sweden)

Fatma A. Agrama

2012-08-01

Full Text Available In the real world, the majority cases of optimization problems, met by engineers, are composed of several conflicting objectives. This paper presents an approach for a multi-objective optimization model for scheduling linear construction projects. Linear construction projects have many identical units wherein activities repeat from one unit to another. Highway, pipeline, and tunnels are good examples that exhibit repetitive characteristics. These projects represent a large portion of the construction industry. The present model enables construction planners to generate optimal/near-optimal construction plans that minimize project duration, total work interruptions, and total number of crews. Each of these plans identifies, from a set of feasible alternatives, optimal crew synchronization for each activity and activity interruptions at each unit. This model satisfies the following aspects: (1 it is based on the line of balance technique; (2 it considers non-serial typical activities networks with finish–start relationship and both lag or overlap time between activities is allowed; (3 it utilizes a multi-objective genetic algorithms approach; (4 it is developed as a spreadsheet template that is easy to use. Details of the model with visual charts are presented. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the scheduling of linear construction projects.

Slotted Blades Savonius Wind Turbine Analysis by CFD

Directory of Open Access Journals (Sweden)

Andrea Alaimo

2013-12-01

Full Text Available In this paper a new bucket configuration for a Savonius wind generator is proposed. Numerical analyses are performed to estimate the performances of the proposed configuration by means of the commercial code COMSOL Multiphysics® with respect to Savonius wind turbine with overlap only. Parametric analyses are performed, for a fixed overlap ratio, by varying the slot position; the results show that for slot positioned near the blade root, the Savonius rotor improves performances at low tip speed ratio, evidencing a better starting torque. This circumstance is confirmed by static analyses performed on the slotted blades in order to investigate the starting characteristic of the proposed Savonius wind generator configuration.

Progress on Ultra-Wideband (UWB Multi-Antenna radar imaging for MIGA

Directory of Open Access Journals (Sweden)

Yedlin Matthew

2016-01-01

Full Text Available Progress on the development of the multi-channel, ground penetrating radar imaging system is presented from hardware and software perspectives. A new exponentially tapered slot antenna, with an operating bandwidth from 100 MHz to 1.5 GHz was fabricated and tested using the eight-port vector network analyzer, designed by Rhode and Schwarz Incorporated for this imaging project. An eight element antenna array mounted on two carts with automatic motor drive, was designed for optimal common midpoint (CMP data acquisition. Data acquisition scenarios were tested using the acoustic version of the NORSAR2D seismic ray-tracing software. This package enables the synthesis and analysis of multi-channel, multi-offset data acquisitions comprising more than a hundred thousand traces. Preliminary processing is in good agreement with published bistatic ground-penetrating radar images obtained in the tunnels of the Low-noise Underground Laboratory (LSBB at Rustrel, France.

Slots in dielectric image line as mode launchers and circuit elements

Science.gov (United States)

Solbach, K.

1981-01-01

A planar resonator model is used to investigate slots in the ground plane of dielectric image lines. An equivalent circuit representation of the slot discontinuity is obtained, and the launching efficiency of the slot as a mode launcher is analyzed. Slots are also shown to be useful in the realization of dielectric image line array antennas. It is found that the slot discontinuity can be shown as a T-junction of the dielectric image line and a metal waveguide. The launching efficiency is found to increase with the dielectric constant of the dielectric image line, exhibiting a maximum value for guides whose height is slightly less than half a wavelength in the dielectric medium. The measured launching efficiencies of low permittivity dielectric image lines are found to be in good agreement with calculated values

Centralized Routing and Scheduling Using Multi-Channel System Single Transceiver in 802.16d

Science.gov (United States)

Al-Hemyari, A.; Noordin, N. K.; Ng, Chee Kyun; Ismail, A.; Khatun, S.

This paper proposes a cross-layer optimized strategy that reduces the effect of interferences from neighboring nodes within a mesh networks. This cross-layer design relies on the routing information in network layer and the scheduling table in medium access control (MAC) layer. A proposed routing algorithm in network layer is exploited to find the best route for all subscriber stations (SS). Also, a proposed centralized scheduling algorithm in MAC layer is exploited to assign a time slot for each possible node transmission. The cross-layer optimized strategy is using multi-channel single transceiver and single channel single transceiver systems for WiMAX mesh networks (WMNs). Each node in WMN has a transceiver that can be tuned to any available channel for eliminating the secondary interference. Among the considered parameters in the performance analysis are interference from the neighboring nodes, hop count to the base station (BS), number of children per node, slot reuse, load balancing, quality of services (QoS), and node identifier (ID). Results show that the proposed algorithms significantly improve the system performance in terms of length of scheduling, channel utilization ratio (CUR), system throughput, and average end to end transmission delay.

Multi-objective and multi-criteria optimization for power generation expansion planning with CO2 mitigation in Thailand

Directory of Open Access Journals (Sweden)

Kamphol Promjiraprawat

2013-06-01

Full Text Available In power generation expansion planning, electric utilities have encountered the major challenge of environmental awareness whilst being concerned with budgetary burdens. The approach for selecting generating technologies should depend on economic and environmental constraint as well as externalities. Thus, the multi-objective optimization becomes a more attractive approach. This paper presents a hybrid framework of multi-objective optimization and multi-criteria decision making to solve power generation expansion planning problems in Thailand. In this paper, CO2 emissions and external cost are modeled as a multi-objective optimization problem. Then the analytic hierarchy process is utilized to determine thecompromised solution. For carbon capture and storage technology, CO2 emissions can be mitigated by 74.7% from the least cost plan and leads to the reduction of the external cost of around 500 billion US dollars over the planning horizon. Results indicate that the proposed approach provides optimum cost-related CO2 mitigation plan as well as external cost.

An Evolutionary Approach for Optimizing Hierarchical Multi-Agent System Organization

OpenAIRE

Shen, Zhiqi; Yu, Ling; Yu, Han

2014-01-01

It has been widely recognized that the performance of a multi-agent system is highly affected by its organization. A large scale system may have billions of possible ways of organization, which makes it impractical to find an optimal choice of organization using exhaustive search methods. In this paper, we propose a genetic algorithm aided optimization scheme for designing hierarchical structures of multi-agent systems. We introduce a novel algorithm, called the hierarchical genetic algorithm...

Discrete-Slots Models of Visual Working-Memory Response Times

Science.gov (United States)

Donkin, Christopher; Nosofsky, Robert M.; Gold, Jason M.; Shiffrin, Richard M.

2014-01-01

Much recent research has aimed to establish whether visual working memory (WM) is better characterized by a limited number of discrete all-or-none slots or by a continuous sharing of memory resources. To date, however, researchers have not considered the response-time (RT) predictions of discrete-slots versus shared-resources models. To complement the past research in this field, we formalize a family of mixed-state, discrete-slots models for explaining choice and RTs in tasks of visual WM change detection. In the tasks under investigation, a small set of visual items is presented, followed by a test item in 1 of the studied positions for which a change judgment must be made. According to the models, if the studied item in that position is retained in 1 of the discrete slots, then a memory-based evidence-accumulation process determines the choice and the RT; if the studied item in that position is missing, then a guessing-based accumulation process operates. Observed RT distributions are therefore theorized to arise as probabilistic mixtures of the memory-based and guessing distributions. We formalize an analogous set of continuous shared-resources models. The model classes are tested on individual subjects with both qualitative contrasts and quantitative fits to RT-distribution data. The discrete-slots models provide much better qualitative and quantitative accounts of the RT and choice data than do the shared-resources models, although there is some evidence for “slots plus resources” when memory set size is very small. PMID:24015956

Multi-objective optimization using genetic algorithms: A tutorial

International Nuclear Information System (INIS)

Konak, Abdullah; Coit, David W.; Smith, Alice E.

2006-01-01

Multi-objective formulations are realistic models for many complex engineering optimization problems. In many real-life problems, objectives under consideration conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. In this paper, an overview and tutorial is presented describing genetic algorithms (GA) developed specifically for problems with multiple objectives. They differ primarily from traditional GA by using specialized fitness functions and introducing methods to promote solution diversity

Slotted Waveguide and Antenna Study for HPM and RF Applications

Science.gov (United States)

2017-07-25

conventional rectangular slot arrays. The proposed CSR-SW A provided higher peak gain than the conventional lambda /4 rectangu lar slot array and a...more compact s ize (55% size reductjon) compared to the lambda /2 rectangular slot array. Both the theoretic and measured results suggest a return loss...in terms of scattering matrix S is: (I-8) With the scattering matrix S, we can compute the scattering field at any position. The resonance of SCCR

Derivation of optimal joint operating rules for multi-purpose multi-reservoir water-supply system

Science.gov (United States)

Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wang, Chao; Lei, Xiao-hui; Xiong, Yi-song; Zhang, Wei

2017-08-01

The derivation of joint operating policy is a challenging task for a multi-purpose multi-reservoir system. This study proposed an aggregation-decomposition model to guide the joint operation of multi-purpose multi-reservoir system, including: (1) an aggregated model based on the improved hedging rule to ensure the long-term water-supply operating benefit; (2) a decomposed model to allocate the limited release to individual reservoirs for the purpose of maximizing the total profit of the facing period; and (3) a double-layer simulation-based optimization model to obtain the optimal time-varying hedging rules using the non-dominated sorting genetic algorithm II, whose objectives were to minimize maximum water deficit and maximize water supply reliability. The water-supply system of Li River in Guangxi Province, China, was selected for the case study. The results show that the operating policy proposed in this study is better than conventional operating rules and aggregated standard operating policy for both water supply and hydropower generation due to the use of hedging mechanism and effective coordination among multiple objectives.

Multi-objective optimization of a continuous bio-dissimilation process of glycerol to 1, 3-propanediol.

Science.gov (United States)

Xu, Gongxian; Liu, Ying; Gao, Qunwang

2016-02-10

This paper deals with multi-objective optimization of continuous bio-dissimilation process of glycerol to 1, 3-propanediol. In order to maximize the production rate of 1, 3-propanediol, maximize the conversion rate of glycerol to 1, 3-propanediol, maximize the conversion rate of glycerol, and minimize the concentration of by-product ethanol, we first propose six new multi-objective optimization models that can simultaneously optimize any two of the four objectives above. Then these multi-objective optimization problems are solved by using the weighted-sum and normal-boundary intersection methods respectively. Both the Pareto filter algorithm and removal criteria are used to remove those non-Pareto optimal points obtained by the normal-boundary intersection method. The results show that the normal-boundary intersection method can successfully obtain the approximate Pareto optimal sets of all the proposed multi-objective optimization problems, while the weighted-sum approach cannot achieve the overall Pareto optimal solutions of some multi-objective problems. Copyright © 2015 Elsevier B.V. All rights reserved.

Geothermal reservoirs. Position of slotted section of the tube casing

International Nuclear Information System (INIS)

Carotenuto, A.; Vanoli, L.; Casarosa, C.

1999-01-01

In the present work the authors have verified the influence of the position of slotted section casing on heat rate drawn by plants for exploitation of geothermal reservoirs that use heat exchangers placed at the bottom of the well (DHE). This study have been done modelling numerically the aquifer, by means of finite element method, evaluating the heat rate drawn by the heat exchanger at different position of the slotted section of the tube casing. Numerical calculations have allowed to show the influence of the main characteristics of the aquifer and of the main characteristics of the aquifer and of the plant on design of the slotted section of the tube casing. In particular, the authors have studied the influence of i) equivalent conductivity and permeability of the aquifer, ii) mass flow rate and the inlet and outlet aquifer temperature difference in the well, iii) the ratio between the length of the slotted section and the thickness of the geothermal layer, varying the position of the slotted section of the tube casing in the aquifer [it

Vertically Polarized Omnidirectional Printed Slot Loop AntennaPrinted Slot Loop Antenna (invited)

DEFF Research Database (Denmark)

Kammersgaard, Nikolaj Peter Iversen; Kvist, Søren Helstrup; Thaysen, Jesper

2015-01-01

and in-phase fields in the slot in order to obtain an omnidirectional radiation pattern. The antenna is designed for the 2.45 GHz Industrial, Scientific and Medical band. Applications of the antenna are many. One is for on-body applications since it is ideal for launching a creeping waves due...

Towards Optimal Multi-Dimensional Query Processing with BitmapIndices

Energy Technology Data Exchange (ETDEWEB)

Rotem, Doron; Stockinger, Kurt; Wu, Kesheng

2005-09-30

Bitmap indices have been widely used in scientific applications and commercial systems for processing complex, multi-dimensional queries where traditional tree-based indices would not work efficiently. This paper studies strategies for minimizing the access costs for processing multi-dimensional queries using bitmap indices with binning. Innovative features of our algorithm include (a) optimally placing the bin boundaries and (b) dynamically reordering the evaluation of the query terms. In addition, we derive several analytical results concerning optimal bin allocation for a probabilistic query model. Our experimental evaluation with real life data shows an average I/O cost improvement of at least a factor of 10 for multi-dimensional queries on datasets from two different applications. Our experiments also indicate that the speedup increases with the number of query dimensions.

MULTI-CRITERIA PROGRAMMING METHODS AND PRODUCTION PLAN OPTIMIZATION PROBLEM SOLVING IN METAL INDUSTRY

OpenAIRE

Tunjo Perić; Željko Mandić

2017-01-01

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 resul...

Vision-Based Parking-Slot Detection: A Benchmark and A Learning-Based Approach

Directory of Open Access Journals (Sweden)

Lin Zhang

2018-03-01

Full Text Available Recent years have witnessed a growing interest in developing automatic parking systems in the field of intelligent vehicles. However, how to effectively and efficiently locating parking-slots using a vision-based system is still an unresolved issue. Even more seriously, there is no publicly available labeled benchmark dataset for tuning and testing parking-slot detection algorithms. In this paper, we attempt to fill the above-mentioned research gaps to some extent and our contributions are twofold. Firstly, to facilitate the study of vision-based parking-slot detection, a large-scale parking-slot image database is established. This database comprises 8600 surround-view images collected from typical indoor and outdoor parking sites. For each image in this database, the marking-points and parking-slots are carefully labeled. Such a database can serve as a benchmark to design and validate parking-slot detection algorithms. Secondly, a learning-based parking-slot detection approach, namely P S D L , is proposed. Using P S D L , given a surround-view image, the marking-points will be detected first and then the valid parking-slots can be inferred. The efficacy and efficiency of P S D L have been corroborated on our database. It is expected that P S D L can serve as a baseline when the other researchers develop more sophisticated methods.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

International Nuclear Information System (INIS)

Zhou, Z; Folkert, M; Wang, J

2016-01-01

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

SU-F-R-10: Selecting the Optimal Solution for Multi-Objective Radiomics Model

Energy Technology Data Exchange (ETDEWEB)

Zhou, Z; Folkert, M; Wang, J [UT Southwestern Medical Center, Dallas, TX (United States)

2016-06-15

Purpose: To develop an evidential reasoning approach for selecting the optimal solution from a Pareto solution set obtained by a multi-objective radiomics model for predicting distant failure in lung SBRT. Methods: In the multi-objective radiomics model, both sensitivity and specificity are considered as the objective functions simultaneously. A Pareto solution set with many feasible solutions will be resulted from the multi-objective optimization. In this work, an optimal solution Selection methodology for Multi-Objective radiomics Learning model using the Evidential Reasoning approach (SMOLER) was proposed to select the optimal solution from the Pareto solution set. The proposed SMOLER method used the evidential reasoning approach to calculate the utility of each solution based on pre-set optimal solution selection rules. The solution with the highest utility was chosen as the optimal solution. In SMOLER, an optimal learning model coupled with clonal selection algorithm was used to optimize model parameters. In this study, PET, CT image features and clinical parameters were utilized for predicting distant failure in lung SBRT. Results: Total 126 solution sets were generated by adjusting predictive model parameters. Each Pareto set contains 100 feasible solutions. The solution selected by SMOLER within each Pareto set was compared to the manually selected optimal solution. Five-cross-validation was used to evaluate the optimal solution selection accuracy of SMOLER. The selection accuracies for five folds were 80.00%, 69.23%, 84.00%, 84.00%, 80.00%, respectively. Conclusion: An optimal solution selection methodology for multi-objective radiomics learning model using the evidential reasoning approach (SMOLER) was proposed. Experimental results show that the optimal solution can be found in approximately 80% cases.

A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2014-01-01

Full Text Available The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching factor, tutorial training and self-motivated learning. The MO-ITLBO algorithm uses a grid-based approach to adaptively assess the non-dominated solutions (i.e. Pareto front maintained in an external archive. The performance of the MO-ITLBO algorithm is assessed by implementing it on unconstrained and constrained test problems proposed for the Congress on Evolutionary Computation 2009 (CEC 2009 competition. The performance assessment is done by using the inverted generational distance (IGD measure. The IGD measures obtained by using the MO-ITLBO algorithm are compared with the IGD measures of the other state-of-the-art algorithms available in the literature. Finally, Lexicographic ordering is used to assess the overall performance of competitive algorithms. Results have shown that the proposed MO-ITLBO algorithm has obtained the 1st rank in the optimization of unconstrained test functions and the 3rd rank in the optimization of constrained test functions.

Modeling of Slot Waveguide Sensors Based on Polymeric Materials

Science.gov (United States)

Bettotti, Paolo; Pitanti, Alessandro; Rigo, Eveline; De Leonardis, Francesco; Passaro, Vittorio M. N.; Pavesi, Lorenzo

2011-01-01

Slot waveguides are very promising for optical sensing applications because of their peculiar spatial mode profile. In this paper we have carried out a detailed analysis of mode confinement properties in slot waveguides realized in very low refractive index materials. We show that the sensitivity of a slot waveguide is not directly related to the refractive index contrast of high and low materials forming the waveguide. Thus, a careful design of the structures allows the realization of high sensitivity devices even in very low refractive index materials (e.g., polymers) to be achieved. Advantages of low index dielectrics in terms of cost, functionalization and ease of fabrication are discussed while keeping both CMOS compatibility and integrable design schemes. Finally, applications of low index slot waveguides as substitute of bulky fiber capillary sensors or in ring resonator architectures are addressed. Theoretical results of this work are relevant to well established polymer technologies. PMID:22164020

Modeling of Slot Waveguide Sensors Based on Polymeric Materials

Directory of Open Access Journals (Sweden)

Lorenzo Pavesi

2011-07-01

Full Text Available Slot waveguides are very promising for optical sensing applications because of their peculiar spatial mode profile. In this paper we have carried out a detailed analysis of mode confinement properties in slot waveguides realized in very low refractive index materials. We show that the sensitivity of a slot waveguide is not directly related to the refractive index contrast of high and low materials forming the waveguide. Thus, a careful design of the structures allows the realization of high sensitivity devices even in very low refractive index materials (e.g., polymers to be achieved. Advantages of low index dielectrics in terms of cost, functionalization and ease of fabrication are discussed while keeping both CMOS compatibility and integrable design schemes. Finally, applications of low index slot waveguides as substitute of bulky fiber capillary sensors or in ring resonator architectures are addressed. Theoretical results of this work are relevant to well established polymer technologies.

Approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems

International Nuclear Information System (INIS)

Zhang, Xiaoshun; Yu, Tao; Yang, Bo; Zheng, Limin; Huang, Linni

2015-01-01

Highlights: • A novel optimal carbon-energy combined-flow (OCECF) model is firstly established. • A novel approximate ideal multi-objective solution Q(λ) learning is designed. • The proposed algorithm has a high convergence stability and reliability. • The proposed algorithm can be applied for OCECF in a large-scale power grid. - Abstract: This paper proposes a novel approximate ideal multi-objective solution Q(λ) learning for optimal carbon-energy combined-flow in multi-energy power systems. The carbon emissions, fuel cost, active power loss, voltage deviation and carbon emission loss are chosen as the optimization objectives, which are simultaneously optimized by five different Q-value matrices. The dynamic optimal weight of each objective is calculated online from the entire Q-value matrices such that the greedy action policy can be obtained. Case studies are carried out to evaluate the optimization performance for carbon-energy combined-flow in an IEEE 118-bus system and the regional power grid of southern China.

An Aggregated Optimization Model for Multi-Head SMD Placements

NARCIS (Netherlands)

Ashayeri, J.; Ma, N.; Sotirov, R.

2010-01-01

In this article we propose an aggregate optimization approach by formulating the multi-head SMD placement optimization problem into a mixed integer program (MIP) with the variables based on batches of components. This MIP is tractable and effective in balancing workload among placement heads,

An aggregated optimization model for multi-head SMD placements

NARCIS (Netherlands)

Ashayeri, J.; Ma, N.; Sotirov, R.

2011-01-01

In this article we propose an aggregate optimization approach by formulating the multi-head SMD placement optimization problem into a mixed integer program (MIP) with the variables based on batches of components. This MIP is tractable and effective in balancing workload among placement heads,

Adaptive multi-objective Optimization scheme for cognitive radio resource management

KAUST Repository

Alqerm, Ismail; Shihada, Basem

2014-01-01

configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance

Investigation of slot discharge on a 239 MVA hydro generator stator winding

Energy Technology Data Exchange (ETDEWEB)

Li, S.; Hong, W. [BC Hydro and Power Authority, Vancouver, BC (Canada)

2009-07-01

This paper discussed a slot discharge investigation conducted on a 239 MVA generator stator winding. The generator in which the winding was located had experienced core split distortion, stator winding phase-to-phase failures, winding failures during Hipot testing, and high partial discharge (PD) activity. The results of on-line PD testing data were evaluated. The stator winding was subjected to visual inspections, bar dissections, and failure mechanism analyses. Eleven winding bars were removed from the stator slots in order to assess groundwall insulation conditions and identify the cause of the slot discharge activity. It was determined that the root cause of the slot discharge was a loose, non-uniform bar in the slot. The vibrating bar caused the semi-conductive coating to wear out and degraded the armour tape. Results of the study demonstrated the importance of on-line PD monitoring for detecting slot PD activity. 4 refs., 3 tabs., 11 figs.

Collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation

Science.gov (United States)

Yang, Shangwen; Guo, Baohua; Xiao, Xuefei; Gao, Haichao

2018-01-01

To allocate the en-routes and slots to the flights with collaborative decision making, a collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation was proposed. Evaluation indexes include flight delay costs, delay time and the number of turning points. Analytic hierarchy process is applied to determining index weights. Remark set for current two flights not yet obtained the en-route and slot in flight schedule is established. Then, fuzzy comprehensive evaluation is performed, and the en-route and slot for the current two flights are determined. Continue selecting the flight not yet obtained an en-route and a slot in flight schedule. Perform fuzzy comprehensive evaluation until all flights have obtained the en-routes and slots. MatlabR2007b was applied to numerical test based on the simulated data of a civil en-route. Test results show that, compared with the traditional strategy of first come first service, the algorithm gains better effect. The effectiveness of the algorithm was verified.

A Photonic 1 × 4 Power Splitter Based on Multimode Interference in Silicon–Gallium-Nitride Slot Waveguide Structures

Directory of Open Access Journals (Sweden)

Dror Malka

2016-06-01

Full Text Available In this paper, a design for a 1 × 4 optical power splitter based on the multimode interference (MMI coupler in a silicon (Si–gallium nitride (GaN slot waveguide structure is presented—to our knowledge, for the first time. Si and GaN were found as suitable materials for the slot waveguide structure. Numerical optimizations were carried out on the device parameters using the full vectorial-beam propagation method (FV-BPM. Simulation results show that the proposed device can be useful to divide optical signal energy uniformly in the C-band range (1530–1565 nm into four output ports with low insertion losses (0.07 dB.

A Photonic 1 × 4 Power Splitter Based on Multimode Interference in Silicon–Gallium-Nitride Slot Waveguide Structures

Science.gov (United States)

Malka, Dror; Danan, Yossef; Ramon, Yehonatan; Zalevsky, Zeev

2016-01-01

In this paper, a design for a 1 × 4 optical power splitter based on the multimode interference (MMI) coupler in a silicon (Si)–gallium nitride (GaN) slot waveguide structure is presented—to our knowledge, for the first time. Si and GaN were found as suitable materials for the slot waveguide structure. Numerical optimizations were carried out on the device parameters using the full vectorial-beam propagation method (FV-BPM). Simulation results show that the proposed device can be useful to divide optical signal energy uniformly in the C-band range (1530–1565 nm) into four output ports with low insertion losses (0.07 dB). PMID:28773638

Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Mengjun Ming

2017-05-01

Full Text Available Due to the scarcity of conventional energy resources and the greenhouse effect, renewable energies have gained more attention. This paper proposes methods for multi-objective optimal design of hybrid renewable energy system (HRES in both isolated-island and grid-connected modes. In each mode, the optimal design aims to find suitable configurations of photovoltaic (PV panels, wind turbines, batteries and diesel generators in HRES such that the system cost and the fuel emission are minimized, and the system reliability/renewable ability (corresponding to different modes is maximized. To effectively solve this multi-objective problem (MOP, the multi-objective evolutionary algorithm based on decomposition (MOEA/D using localized penalty-based boundary intersection (LPBI method is proposed. The algorithm denoted as MOEA/D-LPBI is demonstrated to outperform its competitors on the HRES model as well as a set of benchmarks. Moreover, it effectively obtains a good approximation of Pareto optimal HRES configurations. By further considering a decision maker’s preference, the most satisfied configuration of the HRES can be identified.

Research on connection structure of aluminumbody bus using multi-objective topology optimization

Science.gov (United States)

Peng, Q.; Ni, X.; Han, F.; Rhaman, K.; Ulianov, C.; Fang, X.

2018-01-01

For connecting Aluminum Alloy bus body aluminum components often occur the problem of failure, a new aluminum alloy connection structure is designed based on multi-objective topology optimization method. Determining the shape of the outer contour of the connection structure with topography optimization, establishing a topology optimization model of connections based on SIMP density interpolation method, going on multi-objective topology optimization, and improving the design of the connecting piece according to the optimization results. The results show that the quality of the aluminum alloy connector after topology optimization is reduced by 18%, and the first six natural frequencies are improved and the strength performance and stiffness performance are obviously improved.

Multi-objective optimization of a continuous thermally regenerative electrochemical cycle for waste heat recovery

International Nuclear Information System (INIS)

Long, Rui; Li, Baode; Liu, Zhichun; Liu, Wei

2015-01-01

An optimization analysis of a continuous TREC (thermally regenerative electrochemical cycle) was conducted with maximum power output and exergy efficiency as the objective functions simultaneously. For comparison, the power output, exergy efficiency, and thermal efficiency under the corresponding single-objective optimization schematics were also calculated. Under different optimization methods it was observed that the power output and the thermal efficiency increase with increasing inlet temperature of the heat source, whereas the exergy efficiency increases with increasing inlet temperature, reaches a maximum value, and then decreases. Results revealed that the optimal power output under the multi-objective optimization turned out to be slightly less than that obtained under the single-objective optimization for power output. However, the exergy and thermal efficiencies were much greater. Furthermore, the thermal exergy and exergy efficiency by single-objective optimization for energy efficiency shows no dominant advantage than that obtained under multi-objective optimization, comparing with the increase amplitude of the power output. This suggests that the multi-objective optimization could coordinate well both the power output and the exergy efficiency of the TREC system, and may serve as a more promising guide for operating and designing TREC systems. - Highlights: • An optimal analysis of a continuous TREC is conducted based on multi-objective optimization. • Performance under corresponding single-objective optimizations has also been calculated and compared. • Power under multi-objective optimization is slightly less than the maximum power. • Exergy and thermal efficiencies are much larger than that under the single-objective optimization.

Multi-machine power system stabilizers design using chaotic optimization algorithm

Energy Technology Data Exchange (ETDEWEB)

Shayeghi, H., E-mail: hshayeghi@gmail.co [Technical Engineering Department, University of Mohaghegh Ardabili, Ardabil (Iran, Islamic Republic of); Shayanfar, H.A. [Center of Excellence for Power System Automation and Operation, Electrical Engineering Department, Iran University of Science and Technology, Tehran (Iran, Islamic Republic of); Jalilzadeh, S.; Safari, A. [Technical Engineering Department, Zanjan University, Zanjan (Iran, Islamic Republic of)

2010-07-15

In this paper, a multiobjective design of the multi-machine power system stabilizers (PSSs) using chaotic optimization algorithm (COA) is proposed. Chaotic optimization algorithms, which have the features of easy implementation, short execution time and robust mechanisms of escaping from the local optimum, is a promising tool for the engineering applications. The PSSs parameters tuning problem is converted to an optimization problem which is solved by a chaotic optimization algorithm based on Lozi map. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed chaotic optimization problem introduces chaos mapping using Lozi map chaotic sequences which increases its convergence rate and resulting precision. Two different objective functions are proposed in this study for the PSSs design problem. The first objective function is the eigenvalues based comprising the damping factor, and the damping ratio of the lightly damped electro-mechanical modes, while the second is the time domain-based multi-objective function. The robustness of the proposed COA-based PSSs (COAPSS) is verified on a multi-machine power system under different operating conditions and disturbances. The results of the proposed COAPSS are demonstrated through eigenvalue analysis, nonlinear time-domain simulation and some performance indices. In addition, the potential and superiority of the proposed method over the classical approach and genetic algorithm is demonstrated.

Integrated production planning and control: A multi-objective optimization model

Directory of Open Access Journals (Sweden)

Cheng Wang

2013-09-01

Full Text Available Purpose: Production planning and control has crucial impact on the production and business activities of enterprise. Enterprise Resource Planning (ERP is the most popular resources planning and management system, however there are some shortcomings and deficiencies in the production planning and control because its core component is still the Material Requirements Planning (MRP. For the defects of ERP system, many local improvement and optimization schemes have been proposed, and improve the feasibility and practicality of the plan in some extent, but study considering the whole planning system optimization in the multiple performance management objectives and achieving better application performance is less. The purpose of this paper is to propose a multi-objective production planning optimization model Based on the point of view of the integration of production planning and control, in order to achieve optimization and control of enterprise manufacturing management. Design/methodology/approach: On the analysis of ERP planning system’s defects and disadvantages, and related research and literature, a multi-objective production planning optimization model is proposed, in addition to net demand and capacity, multiple performance management objectives, such as on-time delivery, production balance, inventory, overtime production, are considered incorporating into the examination scope of the model, so that the manufacturing process could be management and controlled Optimally between multiple objectives. The validity and practicability of the model will be verified by the instance in the last part of the paper. Findings: The main finding is that production planning management of manufacturing enterprise considers not only the capacity and materials, but also a variety of performance management objectives in the production process, and building a multi-objective optimization model can effectively optimize the management and control of enterprise

Flow Control by Slot Position and Noise Baffle in a Self-Recirculation Casing Treatment on an Axial Fan-Rotor

Directory of Open Access Journals (Sweden)

Xiangjun Li

2017-01-01

Full Text Available To address the situations where the casing treatment needs to be used to stabilize axial compressors through strong recirculation, this paper initiated a CFD study to investigate how the flow could be suitably controlled in the casing treatment to minimize the efficiency penalty and increase the flow range. A counter-swirl self-recirculation casing treatment was first designed on a low speed axial fan rotor as a baseline case. Then three different slot positions and the influence of including the noise baffle were numerically studied. Based on the understanding of their coeffects, the shorter noise baffle was considered and it was found that the highest efficiency was achieved in the case of the upstream slot when the length of baffle was suitably adjusted to balance the incoming flow and recirculation. The largest flow range was achieved by locating the slot at the most downstream position and using a 50% length baffle since it suitably controlled the recirculating flow and relieved the separation at the low-span region. An optimization study showed that the optimum length of the baffle for efficiency was always larger than for the flow range. Both of the two optimum values reduce as the slot moves downstream.

Slot-Die-Coated V2O5 as Hole Transport Layer for Flexible Organic Solar Cells and Optoelectronic Devices

DEFF Research Database (Denmark)

Beliatis, Michail; Helgesen, Martin; Garcia Valverde, Rafael

2016-01-01

Vanadium pentoxide has been proposed as a good alternative hole transport layer for improving device lifetime of organic photovoltaics. The article presents a study on the optimization of slot-die-coated vanadium oxide films produced with a roll coating machine with the aim of achieving scalable ...

Hybrid Robust Multi-Objective Evolutionary Optimization Algorithm

Science.gov (United States)

2009-03-10

xfar by xint. Else, generate a new individual, using the Sobol pseudo- random sequence generator within the upper and lower bounds of the variables...12. Deb, K., Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons. 2002. 13. Sobol , I. M., "Uniformly Distributed Sequences

Energy characteristics of the double slot in the narrow wall of a rectangular waveguide

OpenAIRE

Martynenko, S. A.

2005-01-01

Based on approximation of the half-wave field distribution in the slots, an expression is derived for internal mutual conductance of closely-spaced slots, which form a double inclined slot in the narrow wall of a rectangular waveguide. The narrow wall has cut-outs reaching the broad wall. With the use of the method of induced magnetomotive forces, a mathematical model is devised for calculating the energy characteristics of the double slot. The impact of angle of inclination of the slots, dim...

Optimization of multi-response dynamic systems integrating multiple ...

African Journals Online (AJOL)

regression and Taguchi's dynamic signal-to-noise ratio concept ..... algorithm for dynamic multi-response optimization based on goal programming approach. .... problem-solving confirmation, if no grave infringement of model suppositions is ...

Fuzzy Linguistic Optimization on Multi-Attribute Machining

Directory of Open Access Journals (Sweden)

Tian-Syung Lan

2010-06-01

Full Text Available Most existing multi-attribute optimization researches for the modern CNC (computer numerical control turning industry were either accomplished within certain manufacturing circumstances, or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme proposed is deemed to be necessary for the industry. In this paper, four parameters (cutting depth, feed rate, speed, tool nose runoff with three levels (low, medium, high are considered to optimize the multi-attribute (surface roughness, tool wear, and material removal rate finish turning. Through FAHP (Fuzzy Analytic Hierarchy Process with eighty intervals for each attribute, the weight of each attribute is evaluated from the paired comparison matrix constructed by the expert judgment. Additionally, twenty-seven fuzzy control rules using trapezoid membership function with respective to seventeen linguistic grades for each attribute are constructed. Considering thirty input and eighty output intervals, the defuzzifierion using center of gravity is thus completed. The TOPSIS (Technique for Order Preference by Similarity to Ideal Solution is moreover utilized to integrate and evaluate the multiple machining attributes for the Taguchi experiment, and thus the optimum general deduction parameters can then be received. The confirmation experiment for optimum general deduction parameters is furthermore performed on an ECOCA-3807 CNC lathe. It is shown that the attributes from the fuzzy linguistic optimization parameters are all significantly advanced comparing to those from benchmark. This paper not only proposes a general deduction optimization scheme using orthogonal array, but also contributes the satisfactory fuzzy linguistic approach for multiple CNC turning attributes with profound insight.

Multi-objective three stage design optimization for island microgrids

International Nuclear Information System (INIS)

Sachs, Julia; Sawodny, Oliver

2016-01-01

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

Broadcast Coded Slotted ALOHA

DEFF Research Database (Denmark)

Ivanov, Mikhail; Brännström, Frederik; Graell i Amat, Alexandre

2016-01-01

We propose an uncoordinated medium access control (MAC) protocol, called all-to-all broadcast coded slotted ALOHA (B-CSA) for reliable all-to-all broadcast with strict latency constraints. In B-CSA, each user acts as both transmitter and receiver in a half-duplex mode. The half-duplex mode gives ...

Results of pressurized-slot measurements in the G-Tunnel underground facility

International Nuclear Information System (INIS)

Zimmerman, R.M.; Mann, K.L.; Dodds, D.J.

1989-01-01

A rock-mechanics field-testing program is underway at Sandia National Laboratories (SNL) as part of the YMP. SNL has the responsibility for assessing the repository design and performance as well as characterizing the geomechanical behavior of the rock. SNL has conducted field experiments in G-Tunnel in Rainier Mesa at the NTS, where tuffs similar to those at Yucca Mountain, the potential repository site, are found. Later experiments are planned as part of the YMP Exploratory Shaft investigations at Yucca Mountain. Major geomechanical factors in repository developments are determinations of the stress state and the deformability of the rock mass (described by the modulus of deformation). One feature of SNL's rock-mechanics program was the development of a testing program for cutting thin slots in a jointed welded tuff and utilizing flatjacks for pressurizing these thin-slots on a relatively, large scale. Objectives in the pressurized-slot testing in G-Tunnel have been to apply and possibly improve methods for (1) utilizing the flatjack cancellation (FC) method for measuring stresses normal to the slot and (2) measuring the modulus of deformation of the jointed rock surrounding the slot. This paper discusses the results of field measurements in and around a single slot and evaluates potential applications and limitations. 10 refs., 1 fig., 4 tabs

Pareto-optimal multi-objective dimensionality reduction deep auto-encoder for mammography classification.

Science.gov (United States)

Taghanaki, Saeid Asgari; Kawahara, Jeremy; Miles, Brandon; Hamarneh, Ghassan

2017-07-01

Feature reduction is an essential stage in computer aided breast cancer diagnosis systems. Multilayer neural networks can be trained to extract relevant features by encoding high-dimensional data into low-dimensional codes. Optimizing traditional auto-encoders works well only if the initial weights are close to a proper solution. They are also trained to only reduce the mean squared reconstruction error (MRE) between the encoder inputs and the decoder outputs, but do not address the classification error. The goal of the current work is to test the hypothesis that extending traditional auto-encoders (which only minimize reconstruction error) to multi-objective optimization for finding Pareto-optimal solutions provides more discriminative features that will improve classification performance when compared to single-objective and other multi-objective approaches (i.e. scalarized and sequential). In this paper, we introduce a novel multi-objective optimization of deep auto-encoder networks, in which the auto-encoder optimizes two objectives: MRE and mean classification error (MCE) for Pareto-optimal solutions, rather than just MRE. These two objectives are optimized simultaneously by a non-dominated sorting genetic algorithm. We tested our method on 949 X-ray mammograms categorized into 12 classes. The results show that the features identified by the proposed algorithm allow a classification accuracy of up to 98.45%, demonstrating favourable accuracy over the results of state-of-the-art methods reported in the literature. We conclude that adding the classification objective to the traditional auto-encoder objective and optimizing for finding Pareto-optimal solutions, using evolutionary multi-objective optimization, results in producing more discriminative features. Copyright © 2017 Elsevier B.V. All rights reserved.

Slot-dimer babinet metamaterials as polarization shapers for terahertz waves

DEFF Research Database (Denmark)

Zhukovsky, Sergei; Chigrin, D. N.; Lavrinenko, Andrei

2013-01-01

We theoretically study optical properties of free-standing metallic membranes patterned with an array of two-slot elements (dimers) comprising two rectangular slots of different dimensions and orientation. It is shown that these structures feature extraordinary optical transmission with strong...

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

2009-04-15

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

International Nuclear Information System (INIS)

Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

2009-01-01

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

A multi-cycle optimization approach for low leakage in-core fuel management

International Nuclear Information System (INIS)

Cheng Pingdong; Shen Wei

1999-01-01

A new approach was developed to optimize pressurized waster reactor (PWR) low-leakage multi-cycle reload core design. The multi-cycle optimization process is carried out by the following three steps: The first step is a linear programming in search for an optimum power sharing distribution and optimum cycle length distribution for the successive several cycles to yield maximum multi-cycle total cycle length. In the second step, the fuel arrangement and burnable poison (BP) assignment are decoupled by using Haling power distribution and the optimum fuel arrangement is determined at the EOL in the absence of all BPs by employing a linear programming method or direct search method with objective function to force the calculated cycle length to be as close as possible to the optimum single cycle length obtained in the first step and with optimum power sharing distribution as additional constraints during optimization. In the third step, the BP assignment is optimized by the Flexible Tolerance Method (FTM) or linear programming method using the number of BP rods as control variable. The technology employed in the second and third steps was the usual decoupling method used in low-leakage core design. The first step was developed specially for multi-cycle optimization design and discussed in detail. Based on the proposed method a computer code MCYCO was encoded and tested for Qinshan Nuclear Power Plant (QNPP) low leakage reload core design. The multi-cycle optimization method developed, together with the program MCYCO, provides an applicable tool for solving the PWR low leakage reload core design problem

Crossed-Slot Cavity-Backed Antenna with Improved Hemispherical Coverage

DEFF Research Database (Denmark)

Kim, Oleksiy S.; Breinbjerg, Olav; Østergaard, Allan

2005-01-01

The paper presents the results of the investigation of the crossed-slot cavity-backed antenna with the complementary crossed electric dipoles added to compensate the circularly polarized (CP) radiation pattern degradation near the horizon. Dependences of the radiation characteristics...... of the modified crossed-slot cavity-backed antenna on the length, width and height of the crossed electric dipoles are shown. Effects of a finite size ground plane are taken into account due to a full wave electromagnetic analysis software utilized in the parametrical investigations. Simulated and measured...... results for a selected antenna configuration prove that the properly adjusted crossed electric dipoles are able to improve the coverage and CP polarization characteristics of the crossed-slot cavity-backed antenna....

Optimizing survivability of multi-state systems with multi-level protection by multi-processor genetic algorithm

International Nuclear Information System (INIS)

Levitin, Gregory; Dai Yuanshun; Xie Min; Leng Poh, Kim

2003-01-01

In this paper we consider vulnerable systems which can have different states corresponding to different combinations of available elements composing the system. Each state can be characterized by a performance rate, which is the quantitative measure of a system's ability to perform its task. Both the impact of external factors (stress) and internal causes (failures) affect system survivability, which is determined as probability of meeting a given demand. In order to increase the survivability of the system, a multi-level protection is applied to its subsystems. This means that a subsystem and its inner level of protection are in their turn protected by the protection of an outer level. This double-protected subsystem has its outer protection and so forth. In such systems, the protected subsystems can be destroyed only if all of the levels of their protection are destroyed. Each level of protection can be destroyed only if all of the outer levels of protection are destroyed. We formulate the problem of finding the structure of series-parallel multi-state system (including choice of system elements, choice of structure of multi-level protection and choice of protection methods) in order to achieve a desired level of system survivability by the minimal cost. An algorithm based on the universal generating function method is used for determination of the system survivability. A multi-processor version of genetic algorithm is used as optimization tool in order to solve the structure optimization problem. An application example is presented to illustrate the procedure presented in this paper

Game-theoretic learning and distributed optimization in memoryless multi-agent systems

CERN Document Server

Tatarenko, Tatiana

2017-01-01

This book presents new efficient methods for optimization in realistic large-scale, multi-agent systems. These methods do not require the agents to have the full information about the system, but instead allow them to make their local decisions based only on the local information, possibly obtained during scommunication with their local neighbors. The book, primarily aimed at researchers in optimization and control, considers three different information settings in multi-agent systems: oracle-based, communication-based, and payoff-based. For each of these information types, an efficient optimization algorithm is developed, which leads the system to an optimal state. The optimization problems are set without such restrictive assumptions as convexity of the objective functions, complicated communication topologies, closed-form expressions for costs and utilities, and finiteness of the system’s state space. .

Measurement of the depth of narrow slotted sections in eddy current reference standards

Science.gov (United States)

Kim, Young-Joo; Kim, Young-gil; Ahn, Bongyoung; Yoon, Dong-Jin

2007-02-01

The dimensions of the slots in eddy current (EC) reference standards are too narrow to be measured by general depth measurement methods such as the optical (laser) or stylus methods. However, measurement of the dimensions of the machined slots is a prerequisite to using the blocks as references. The present paper suggests a measurement method for the slotted section using an ultrasonic test. The width and depth of the slots measured in our study are roughly 0.1 mm and 0.5 mm, respectively. The time of flight (TOF) of the ultrasonic wave was measured precisely. The ultrasonic velocity in the material of the EC reference standard was calculated with the measured values of the TOF and its thickness. Reflected waves from the tip of the slot and the bottom surface of the EC standard were successfully classified. Using this method we have successfully determined the depth of the slotted section.

Constrained multi-objective optimization of storage ring lattices

Science.gov (United States)

Husain, Riyasat; Ghodke, A. D.

2018-03-01

The storage ring lattice optimization is a class of constrained multi-objective optimization problem, where in addition to low beam emittance, a large dynamic aperture for good injection efficiency and improved beam lifetime are also desirable. The convergence and computation times are of great concern for the optimization algorithms, as various objectives are to be optimized and a number of accelerator parameters to be varied over a large span with several constraints. In this paper, a study of storage ring lattice optimization using differential evolution is presented. The optimization results are compared with two most widely used optimization techniques in accelerators-genetic algorithm and particle swarm optimization. It is found that the differential evolution produces a better Pareto optimal front in reasonable computation time between two conflicting objectives-beam emittance and dispersion function in the straight section. The differential evolution was used, extensively, for the optimization of linear and nonlinear lattices of Indus-2 for exploring various operational modes within the magnet power supply capabilities.

Wearable Passive E-Textile UHF RFID Tag Based on a Slotted Patch Antenna with Sewn Ground and Microchip Interconnections

Directory of Open Access Journals (Sweden)

Johanna Virkki

2017-01-01

Full Text Available We present a wearable passive UHF RFID tag based on a slotted patch antenna comprising only textile materials (e-textile, textile substrate, and conductive yearn. As a novel manufacturing approach, we realize the patch-to-ground and antenna-to-IC interfaces using only conductive thread and a sewing machine. We outline the electromagnetic optimization of the antenna for body-worn operation through simulations and present a performance comparison between the e-textile tag and a tag produced using regular electronics materials and methods. The measured results show that the textile tag achieves the electrical performance required in practical applications and that the slotted patch type antenna provides stable electromagnetic performance in different body-worn configurations.

Slot-type pickup/kicker for AA stochastic cooling

CERN Multimedia

CERN PhotoLab

1979-01-01

A "slotted transmission line" was used for both pickups and kickers of the cooling systems of the AA. They served for the cooling of the high-density antiproton stack, in momentum and both transverse planes. In the beginning in a single band, 1-2 GHz, later in 2 bands, 2-4 and 4-8 GHz. Here we see the slotted electrodes partly pulled out of the outer casing. See also 7906189, 7906581X, 7896193.

Multi-parameter optimization design of parabolic trough solar receiver

International Nuclear Information System (INIS)

Guo, Jiangfeng; Huai, Xiulan

2016-01-01

Highlights: • The optimal condition can be obtained by multi-parameter optimization. • Exergy and thermal efficiencies are employed as objective function. • Exergy efficiency increases at the expense of heat losses. • The heat obtained by working fluid increases as thermal efficiency grows. - Abstract: The design parameters of parabolic trough solar receiver are interrelated and interact with one another, so the optimal performance of solar receiver cannot be obtained by the convectional single-parameter optimization. To overcome the shortcoming of single-parameter optimization, a multi-parameter optimization of parabolic trough solar receiver is employed based on genetic algorithm in the present work. When the thermal efficiency is taken as the objective function, the heat obtained by working fluid increases while the average temperature of working fluid and wall temperatures of solar receiver decrease. The average temperature of working fluid and the wall temperatures of solar receiver increase while the heat obtained by working fluid decreases generally by taking the exergy efficiency as an objective function. Assuming that the solar radiation intensity remains constant, the exergy obtained by working fluid increases by taking exergy efficiency as the objective function, which comes at the expense of heat losses of solar receiver.

MULTI-CRITERIA PROGRAMMING METHODS AND PRODUCTION PLAN OPTIMIZATION PROBLEM SOLVING IN METAL INDUSTRY

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.

Multi-objective optimization under uncertainty for sheet metal forming

Directory of Open Access Journals (Sweden)

Lafon Pascal

2016-01-01

Full Text Available Aleatory uncertainties in material properties, blank thickness and friction condition are inherent and irreducible variabilities in sheet metal forming. Optimal design configurations, which are obtained by conventional design optimization methods, are not always able to meet the desired targets due to the effect of uncertainties. This paper proposes a multi-objective robust design optimization that aims to tackle this problem. Results obtained on a U shape draw bending benchmark show that spring-back effect can be controlled by optimizing process parameters.

Multi-infill strategy for kriging models used in variable fidelity optimization

Directory of Open Access Journals (Sweden)

Chao SONG

2018-03-01

Full Text Available In this paper, a computationally efficient optimization method for aerodynamic design has been developed. The low-fidelity model and the multi-infill strategy are utilized in this approach. Low-fidelity data is employed to provide a good global trend for model prediction, and multiple sample points chosen by different infill criteria in each updating cycle are used to enhance the exploitation and exploration ability of the optimization approach. Take the advantages of low-fidelity model and the multi-infill strategy, and no initial sample for the high-fidelity model is needed. This approach is applied to an airfoil design case and a high-dimensional wing design case. It saves a large number of high-fidelity function evaluations for initial model construction. What’s more, faster reduction of an aerodynamic function is achieved, when compared to ordinary kriging using the multi-infill strategy and variable-fidelity model using single infill criterion. The results indicate that the developed approach has a promising application to efficient aerodynamic design when high-fidelity analyses are involved. Keywords: Aerodynamics, Infill criteria, Kriging models, Multi-infill, Optimization

Optimal Design Solutions for Permanent Magnet Synchronous Machines

Directory of Open Access Journals (Sweden)

POPESCU, M.

2011-11-01

Full Text Available This paper presents optimal design solutions for reducing the cogging torque of permanent magnets synchronous machines. A first solution proposed in the paper consists in using closed stator slots that determines a nearly isotropic magnetic structure of the stator core, reducing the mutual attraction between permanent magnets and the slotted armature. To avoid complications in the windings manufacture technology the stator slots are closed using wedges made of soft magnetic composite materials. The second solution consists in properly choosing the combination of pole number and stator slots number that typically leads to a winding with fractional number of slots/pole/phase. The proposed measures for cogging torque reduction are analyzed by means of 2D/3D finite element models developed using the professional Flux software package. Numerical results are discussed and compared with experimental ones obtained by testing a PMSM prototype.

Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn

2009-01-01

Multi-objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the exergetic, economic and environmental aspects have been considered, simultaneously. The thermodynamic modeling has been implemented comprehensively while economic analysis conducted in accordance with the total revenue requirement (TRR) method. The results for the single objective thermoeconomic optimization have been compared with the previous studies in optimization of CGAM problem. In multi-objective optimization of the CGAM problem, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms. This objective has been integrated with the thermoeconomic objective to form a new unique objective function known as a thermoenvironomic objective function. The thermoenvironomic objective has been minimized while the exergetic objective has been maximized. One of the most suitable optimization techniques developed using a particular class of search algorithms known as multi-objective evolutionary algorithms (MOEAs) has been considered here. This approach which is developed based on the genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of decision-making has been presented and a final optimal solution has been introduced. The sensitivity of the solutions to the interest rate and the fuel cost has been studied

Enhanced Multi-Objective Optimization of Groundwater Monitoring Networks

DEFF Research Database (Denmark)

Bode, Felix; Binning, Philip John; Nowak, Wolfgang

Drinking-water well catchments include many sources for potential contaminations like gas stations or agriculture. Finding optimal positions of monitoring wells for such purposes is challenging because there are various parameters (and their uncertainties) that influence the reliability...... and optimality of any suggested monitoring location or monitoring network. The goal of this project is to develop and establish a concept to assess, design, and optimize early-warning systems within well catchments. Such optimal monitoring networks need to optimize three competing objectives: (1) a high...... be reduced to a minimum. The method is based on numerical simulation of flow and transport in heterogeneous porous media coupled with geostatistics and Monte-Carlo, wrapped up within the framework of formal multi-objective optimization. In order to gain insight into the flow and transport physics...

Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

Energy Technology Data Exchange (ETDEWEB)

Bellary, Sayed Ahmed Imran; Samad, Abdus [Indian Institute of Technology Madras, Chennai (India); Husain, Afzal [Sultan Qaboos University, Al-Khoudh (Oman)

2014-12-15

The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

Effectiveness of meta-models for multi-objective optimization of centrifugal impeller

International Nuclear Information System (INIS)

Bellary, Sayed Ahmed Imran; Samad, Abdus; Husain, Afzal

2014-01-01

The major issue of multiple fidelity based analysis and optimization of fluid machinery system depends upon the proper construction of low fidelity model or meta-model. A low fidelity model uses responses obtained from a high fidelity model, and the meta-model is then used to produce population of solutions required for evolutionary algorithm for multi-objective optimization. The Pareto-optimal front which shows functional relationships among the multiple objectives can produce erroneous results if the low fidelity models are not well-constructed. In the present research, response surface approximation and Kriging meta-models were evaluated for their effectiveness for the application in the turbomachinery design and optimization. A high fidelity model such as CFD technique along with the metamodels was used to obtain Pareto-optimal front via multi-objective genetic algorithm. A centrifugal impeller has been considered as case study to find relationship between two conflicting objectives, viz., hydraulic efficiency and head. Design variables from the impeller geometry have been chosen and the responses of the objective functions were evaluated through CFD analysis. The fidelity of each metamodel has been discussed in context of their predictions in entire design space in general and near optimal region in particular. Exploitation of the multiple meta-models enhances the quality of multi-objective optimization and provides the information pertaining to fidelity of optimization model. It was observed that the Kriging meta-model was better suited for this type of problem as it involved less approximation error in the Pareto-optimal front.

Slotted cage resonator for high-field magnetic resonance imaging of rodents

Energy Technology Data Exchange (ETDEWEB)

Marrufo, O; Vasquez, F; Solis, S E; Rodriguez, A O, E-mail: arog@xanum.uam.mx [Departamento de Ingenieria Electrica, Universidad Autonoma Metropolitana Iztapalapa, Mexico, DF 09340 (Mexico)

2011-04-20

A variation of the high-frequency cavity resonator coil was experimentally developed according to the theoretical frame proposed by Mansfield in 1990. Circular slots were used instead of cavities to form the coil endplates and it was called the slotted cage resonator coil. The theoretical principles were validated via a coil equivalent circuit and also experimentally with a coil prototype. The radio frequency magnetic field, B1, produced by several coil configurations was numerically simulated using the finite-element approach to investigate their performances. A transceiver coil, 8 cm long and 7.6 cm in diameter, and composed of 4 circular slots with a 15 mm diameter on both endplates, was built to operate at 300 MHz and quadrature driven. Experimental results obtained with the slotted cage resonator coil were presented and showed very good agreement with the theoretical expectations for the resonant frequency as a function of the coil dimensions and slots. A standard birdcage coil was also built for performance comparison purposes. Phantom images were then acquired to compute the signal-to-noise ratio of both coils showing an important improvement of the slotted cage coil over the birdcage coil. The whole-body images of the mouse were also obtained showing high-quality images. Volume resonator coils can be reliably built following the physical principles of the cavity resonator design for high-field magnetic resonance imaging applications of rodents.

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

Science.gov (United States)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

Evaluation of two styles of slotted, flat-head screws

International Nuclear Information System (INIS)

Reeves, C.A. Jr.; Johnson, W.B.

1979-01-01

A series of torque tests were performed to evaluate the relative merits of two different flat-head screws fabricated from a uranium--6% niobium alloy. The screws tested were machined with both normal, straight-through slots in the head and with slots having radiused bottoms. Test results indicate that both designs easily surpass the required 20-inch-pound-proof torque

An optimal multi-channel memory controller for real-time systems

NARCIS (Netherlands)

Gomony, M.D.; Akesson, K.B.; Goossens, K.G.W.

2013-01-01

Optimal utilization of a multi-channel memory, such as Wide IO DRAM, as shared memory in multi-processor platforms depends on the mapping of memory clients to the memory channels, the granularity at which the memory requests are interleaved in each channel, and the bandwidth and memory capacity

Development of high power models of four-slot Annular Coupled Structure

International Nuclear Information System (INIS)

Kageyama, T.; Morozumi, Y.; Yoshino, K.; Yamazaki, Y.

1994-01-01

A π/2-mode standing-wave linac (f=1.296 GHz) of an Annular Coupled Structure (ACS) has been developed for the 1-GeV proton linac of the Japanese Hadron Project (JHP). This ACS has four coupling slots between accelerating and coupling cells in order to suppress higher order mode mixing with the π/2 coupling mode. High-β(β=v/c=0.78) and low-β(0.52) prototypes were constructed and tested up to each design RF power. Concerning the effect of the coupling slots on the fields of a coupled-cavity linac, it was found that the slot configuration of the side-coupled structure (SCS) tilts the accelerating field. On the other hand, the four-slot configuration of the ACS gives an almost axially symmetric accelerating field to the beam. (author)

An experimental analysis of design choices of multi-objective ant colony optimization algorithms

OpenAIRE

Lopez-Ibanez, Manuel; Stutzle, Thomas

2012-01-01

There have been several proposals on how to apply the ant colony optimization (ACO) metaheuristic to multi-objective combinatorial optimization problems (MOCOPs). This paper proposes a new formulation of these multi-objective ant colony optimization (MOACO) algorithms. This formulation is based on adding specific algorithm components for tackling multiple objectives to the basic ACO metaheuristic. Examples of these components are how to represent multiple objectives using pheromone and heuris...

High slot utilization systems for electric machines

Science.gov (United States)

Hsu, John S

2009-06-23

Two new High Slot Utilization (HSU) Systems for electric machines enable the use of form wound coils that have the highest fill factor and the best use of magnetic materials. The epoxy/resin/curing treatment ensures the mechanical strength of the assembly of teeth, core, and coils. In addition, the first HSU system allows the coil layers to be moved inside the slots for the assembly purpose. The second system uses the slided-in teeth instead of the plugged-in teeth. The power density of the electric machine that uses either system can reach its highest limit.

Heat and mass transfer intensification and shape optimization a multi-scale approach

CERN Document Server

2013-01-01

Is the heat and mass transfer intensification defined as a new paradigm of process engineering, or is it just a common and old idea, renamed and given the current taste? Where might intensification occur? How to achieve intensification? How the shape optimization of thermal and fluidic devices leads to intensified heat and mass transfers? To answer these questions, Heat & Mass Transfer Intensification and Shape Optimization: A Multi-scale Approach clarifies  the definition of the intensification by highlighting the potential role of the multi-scale structures, the specific interfacial area, the distribution of driving force, the modes of energy supply and the temporal aspects of processes.   A reflection on the methods of process intensification or heat and mass transfer enhancement in multi-scale structures is provided, including porous media, heat exchangers, fluid distributors, mixers and reactors. A multi-scale approach to achieve intensification and shape optimization is developed and clearly expla...

Multi-objective compared to single-objective optimization with application to model validation and uncertainty quantification

Energy Technology Data Exchange (ETDEWEB)

Schulze-Riegert, R.; Krosche, M.; Stekolschikov, K. [Scandpower Petroleum Technology GmbH, Hamburg (Germany); Fahimuddin, A. [Technische Univ. Braunschweig (Germany)

2007-09-13

History Matching in Reservoir Simulation, well location and production optimization etc. is generally a multi-objective optimization problem. The problem statement of history matching for a realistic field case includes many field and well measurements in time and type, e.g. pressure measurements, fluid rates, events such as water and gas break-throughs, etc. Uncertainty parameters modified as part of the history matching process have varying impact on the improvement of the match criteria. Competing match criteria often reduce the likelihood of finding an acceptable history match. It is an engineering challenge in manual history matching processes to identify competing objectives and to implement the changes required in the simulation model. In production optimization or scenario optimization the focus on one key optimization criterion such as NPV limits the identification of alternatives and potential opportunities, since multiple objectives are summarized in a predefined global objective formulation. Previous works primarily focus on a specific optimization method. Few works actually concentrate on the objective formulation and multi-objective optimization schemes have not yet been applied to reservoir simulations. This paper presents a multi-objective optimization approach applicable to reservoir simulation. It addresses the problem of multi-objective criteria in a history matching study and presents analysis techniques identifying competing match criteria. A Pareto-Optimizer is discussed and the implementation of that multi-objective optimization scheme is applied to a case study. Results are compared to a single-objective optimization method. (orig.)

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)

Adaptive Multi-Agent Systems for Constrained Optimization

Science.gov (United States)

Macready, William; Bieniawski, Stefan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Multi-objective optimal strategy for generating and bidding in the power market

International Nuclear Information System (INIS)

Peng Chunhua; Sun Huijuan; Guo Jianfeng; Liu Gang

2012-01-01

Highlights: ► A new benefit/risk/emission comprehensive generation optimization model is established. ► A hybrid multi-objective differential evolution optimization algorithm is designed. ► Fuzzy set theory and entropy weighting method are employed to extract the general best solution. ► The proposed approach of generating and bidding is efficient for maximizing profit and minimizing both risk and emissions. - Abstract: Based on the coordinated interaction between units output and electricity market prices, the benefit/risk/emission comprehensive generation optimization model with objectives of maximal profit and minimal bidding risk and emissions is established. A hybrid multi-objective differential evolution optimization algorithm, which successfully integrates Pareto non-dominated sorting with differential evolution algorithm and improves individual crowding distance mechanism and mutation strategy to avoid premature and unevenly search, is designed to achieve Pareto optimal set of this model. Moreover, fuzzy set theory and entropy weighting method are employed to extract one of the Pareto optimal solutions as the general best solution. Several optimization runs have been carried out on different cases of generation bidding and scheduling. The results confirm the potential and effectiveness of the proposed approach in solving the multi-objective optimization problem of generation bidding and scheduling. In addition, the comparison with the classical optimization algorithms demonstrates the superiorities of the proposed algorithm such as integrality of Pareto front, well-distributed Pareto-optimal solutions, high search speed.

Improvement The Transmission Efficiency For Wireless Packet Communication Systems Using Automatic Control for power And Time Slot Width Of Slotted Non persistent ISMA Protocol

Directory of Open Access Journals (Sweden)

Saad M. Hardan

2013-05-01

Full Text Available In packed communication systems which use a protocol, the protocol should perform the allocation of channels such that the transmission channel is used efficiently. Efficiency is usually measured in terms of channel throughput and the average transmission  delay. The Slotted Nonpersistent ISMA protocol is one of random access protocols used in packed communication systems. In this research a Slotted Nonpersistent ISMA protocol Model with automatic control for power and time slot is proposed. the suggested algorithm enable the base station(access point to control  the protocol time slot length and  transmission power in a dynamic way to control the normalized propagation delay d and to maintain all the uplink signals in the limit of captured power threshold (capture ratio in order to control the  throughput and the average transmission delay of the communication system by an automatic method. the computer simulation results  confirm the activity of the  proposed algorithm for increasing the  throughput and decreasing the average transmission delay by an accepted ratios.

Multi-objective optimization of a vertical ground source heat pump using evolutionary algorithm

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn; Amlashi, Emad Hadaddi; Amidpour, Majid

2009-01-01

Thermodynamic and thermoeconomic optimization of a vertical ground source heat pump system has been studied. A model based on the energy and exergy analysis is presented here. An economic model of the system is developed according to the Total Revenue Requirement (TRR) method. The objective functions based on the thermodynamic and thermoeconomic analysis are developed. The proposed vertical ground source heat pump system including eight decision variables is considered for optimization. An artificial intelligence technique known as evolutionary algorithm (EA) has been utilized as an optimization method. This approach has been applied to minimize either the total levelized cost of the system product or the exergy destruction of the system. Three levels of optimization including thermodynamic single objective, thermoeconomic single objective and multi-objective optimizations are performed. In Multi-objective optimization, both thermodynamic and thermoeconomic objectives are considered, simultaneously. In the case of multi-objective optimization, an example of decision-making process for selection of the final solution from available optimal points on Pareto frontier is presented. The results obtained using the various optimization approaches are compared and discussed. Further, the sensitivity of optimized systems to the interest rate, to the annual number of operating hours and to the electricity cost are studied in detail.

Multi-objective optimization of an underwater compressed air energy storage system using genetic algorithm

International Nuclear Information System (INIS)

Cheung, Brian C.; Carriveau, Rupp; Ting, David S.K.

2014-01-01

This paper presents the findings from a multi-objective genetic algorithm optimization study on the design parameters of an underwater compressed air energy storage system (UWCAES). A 4 MWh UWCAES system was numerically simulated and its energy, exergy, and exergoeconomics were analysed. Optimal system configurations were determined that maximized the UWCAES system round-trip efficiency and operating profit, and minimized the cost rate of exergy destruction and capital expenditures. The optimal solutions obtained from the multi-objective optimization model formed a Pareto-optimal front, and a single preferred solution was selected using the pseudo-weight vector multi-criteria decision making approach. A sensitivity analysis was performed on interest rates to gauge its impact on preferred system designs. Results showed similar preferred system designs for all interest rates in the studied range. The round-trip efficiency and operating profit of the preferred system designs were approximately 68.5% and $53.5/cycle, respectively. The cost rate of the system increased with interest rates. - Highlights: • UWCAES system configurations were developed using multi-objective optimization. • System was optimized for energy efficiency, exergy, and exergoeconomics • Pareto-optimal solution surfaces were developed at different interest rates. • Similar preferred system configurations were found at all interest rates studied

Bead beavior in a non-continues slot die coating regime

NARCIS (Netherlands)

Langen, A.; Senes, A.; Vries, I. de; Groen, P.

2015-01-01

Sheet-to-sheet slot die coating is a crucial intermediate technique to bring organic and large area electronics (e.g. OLED and Flexible OPV) towards mass roll-to-roll productions. The coating on substrate has to be uniform within nanometers. Additional settings are added to the slot die coater for a

Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems

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.

A model of gas flow with friction in a slotted seal

Directory of Open Access Journals (Sweden)

Joachimiak Damian

2016-09-01

Full Text Available The paper discusses thermodynamic phenomena accompanying the flow of gas in a slotted seal. The analysis of the gas flow has been described based on an irreversible adiabatic transformation. A model based on the equation of total enthalpy balance has been proposed. The iterative process of the model aims at obtaining such a gas temperature distribution that will fulfill the continuity equation. The model allows for dissipation of the kinetic energy into friction heat by making use of the Blasius equation to determine the friction coefficient. Within the works, experimental research has been performed of the gas flow in a slotted seal of slot height 2 mm. Based on the experimental data, the equation of local friction coefficient was modified with a correction parameter. This parameter was described with the function of pressure ratio to obtain a mass flow of the value from the experiment. The reason for taking up of this problem is the absence of high accuracy models for calculating the gas flow in slotted seals. The proposed model allows an accurate determination of the mass flow in a slotted seal based on the geometry and gas initial and final parameters.

Distributed optimization-based control of multi-agent networks in complex environments

CERN Document Server

Zhu, Minghui

2015-01-01

This book offers a concise and in-depth exposition of specific algorithmic solutions for distributed optimization based control of multi-agent networks and their performance analysis. It synthesizes and analyzes distributed strategies for three collaborative tasks: distributed cooperative optimization, mobile sensor deployment and multi-vehicle formation control. The book integrates miscellaneous ideas and tools from dynamic systems, control theory, graph theory, optimization, game theory and Markov chains to address the particular challenges introduced by such complexities in the environment as topological dynamics, environmental uncertainties, and potential cyber-attack by human adversaries. The book is written for first- or second-year graduate students in a variety of engineering disciplines, including control, robotics, decision-making, optimization and algorithms and with backgrounds in aerospace engineering, computer science, electrical engineering, mechanical engineering and operations research. Resea...

Multi-objective differential evolution with adaptive Cauchy mutation for short-term multi-objective optimal hydro-thermal scheduling

Energy Technology Data Exchange (ETDEWEB)

Qin Hui [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China); Zhou Jianzhong, E-mail: jz.zhou@hust.edu.c [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China); Lu Youlin; Wang Ying; Zhang Yongchuan [College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074 (China)

2010-04-15

A new multi-objective optimization method based on differential evolution with adaptive Cauchy mutation (MODE-ACM) is presented to solve short-term multi-objective optimal hydro-thermal scheduling (MOOHS) problem. Besides fuel cost, the pollutant gas emission is also optimized as an objective. The water transport delay between connected reservoirs and the effect of valve-point loading of thermal units are also taken into account in the presented problem formulation. The proposed algorithm adopts an elitist archive to retain non-dominated solutions obtained during the evolutionary process. It modifies the DE's operators to make it suit for multi-objective optimization (MOO) problems and improve its performance. Furthermore, to avoid premature convergence, an adaptive Cauchy mutation is proposed to preserve the diversity of population. An effective constraints handling method is utilized to handle the complex equality and inequality constraints. The effectiveness of the proposed algorithm is tested on a hydro-thermal system consisting of four cascaded hydro plants and three thermal units. The results obtained by MODE-ACM are compared with several previous studies. It is found that the results obtained by MODE-ACM are superior in terms of fuel cost as well as emission output, consuming a shorter time. Thus it can be a viable alternative to generate optimal trade-offs for short-term MOOHS problem.

Contribution to the evaluation and to the improvement of multi-objective optimization methods: application to the optimization of nuclear fuel reloading pattern

International Nuclear Information System (INIS)

Collette, Y.

2002-01-01

In this thesis, we study the general problem of the selection of a multi-objective optimization method, then we study the improvement so as to efficiently solve a problem. The pertinent selection of a method presume the existence of a methodology: we have built tools to perform evaluation of performances and we propose an original method dedicated to the classification of know optimization methods. Our step has been applied to the elaboration of new methods for solving a very difficult problem: the nuclear core reload pattern optimization. First, we looked for a non usual approach of performances measurement: we have 'measured' the behavior of a method. To reach this goal, we have introduced several metrics. We have proposed to evaluate the 'aesthetic' of a distribution of solutions by defining two new metrics: a 'spacing metric' and a metric that allow us to measure the size of the biggest hole in the distribution of solutions. Then, we studied the convergence of multi-objective optimization methods by using some metrics defined in scientific literature and by proposing some more metrics: the 'Pareto ratio' which computes a ratio of solution production. Lastly, we have defined new metrics intended to better apprehend the behavior of optimization methods: the 'speed metric', which allows to compute the speed profile and a 'distribution metric' which allows to compute statistical distribution of solutions along the Pareto frontier. Next, we have studied transformations of a multi-objective problem and defined news methods: the modified Tchebychev method, or the penalized weighted sum of objective functions. We have elaborated new techniques to choose the initial point. These techniques allow to produce new initial points closer and closer to the Pareto frontier and, thanks to the 'proximal optimality concept', allowing dramatic improvements in the convergence of a multi-objective optimization method. Lastly, we have defined new vectorial multi-objective optimization

Investigating multi-objective fluence and beam orientation IMRT optimization

Science.gov (United States)

Potrebko, Peter S.; Fiege, Jason; Biagioli, Matthew; Poleszczuk, Jan

2017-07-01

Radiation Oncology treatment planning requires compromises to be made between clinical objectives that are invariably in conflict. It would be beneficial to have a ‘bird’s-eye-view’ perspective of the full spectrum of treatment plans that represent the possible trade-offs between delivering the intended dose to the planning target volume (PTV) while optimally sparing the organs-at-risk (OARs). In this work, the authors demonstrate Pareto-aware radiotherapy evolutionary treatment optimization (PARETO), a multi-objective tool featuring such bird’s-eye-view functionality, which optimizes fluence patterns and beam angles for intensity-modulated radiation therapy (IMRT) treatment planning. The problem of IMRT treatment plan optimization is managed as a combined monolithic problem, where all beam fluence and angle parameters are treated equally during the optimization. To achieve this, PARETO is built around a powerful multi-objective evolutionary algorithm, called Ferret, which simultaneously optimizes multiple fitness functions that encode the attributes of the desired dose distribution for the PTV and OARs. The graphical interfaces within PARETO provide useful information such as: the convergence behavior during optimization, trade-off plots between the competing objectives, and a graphical representation of the optimal solution database allowing for the rapid exploration of treatment plan quality through the evaluation of dose-volume histograms and isodose distributions. PARETO was evaluated for two relatively complex clinical cases, a paranasal sinus and a pancreas case. The end result of each PARETO run was a database of optimal (non-dominated) treatment plans that demonstrated trade-offs between the OAR and PTV fitness functions, which were all equally good in the Pareto-optimal sense (where no one objective can be improved without worsening at least one other). Ferret was able to produce high quality solutions even though a large number of parameters

Modeling fiber motion in a pulp pressure screen: the effect of slot shape

International Nuclear Information System (INIS)

Dong, S.; Salcudean, M.; Gartshore, I.

2003-01-01

A pressure screen is a piece of equipment in the pulp and paper industry used either to remove contaminants from the pulp suspension or to separate fibers having different properties. Contaminants such as fiber bundles, bark and plastic specks are introduced when fibers are separated from the wood by mechanical or chemical pulping processes. Contaminants significantly affect the strength and smoothness of the paper and must be removed before the final paper is produced. The screen plate is a critical part of the pressure screen and its design is the key to screen performance. This paper uses a new and comprehensive CFD simulation tool to examine the flow and fiber behavior in a single slot screen having any reasonable slot shape. -This simulation tool includes three coupled models: first, the flow model solves the Reynolds Averaged Navier-Stokes (RANS) equation using the standard k - ε turbulence model to predict the flow field in the equipment. Second, a three-dimensional flexible fiber model is used to track the fiber trajectory in the screen. Third, a very general wall model is used to deal with the case when a fiber touches the equipment wall. The simulated results show that the slot shape has a critical influence on fiber behavior and screen performance. Three general slot shapes were investigated: the smooth slot, the step-step contour slot and slope-slope contour slot. Of these the slope-slope contour slot provides the best passage for the fibers with a length of 1mm and 3mm. (author)

Study on wake structure characteristics of a slotted micro-ramp with large-eddy simulation

Energy Technology Data Exchange (ETDEWEB)

Dong, Xiangrui; Chen, Yaohui; Dong, Gang; Liu, Yixin, E-mail: cyh873@163.com [National Key Laboratory of Transient Physics, Nanjing University of Science and Technology, Nanjing, 210094 (China)

2017-06-15

In this paper, a novel slotted ramp-type micro vortex generator (slotted micro-ramp) for flow separation control is simulated in the supersonic flow of Ma = 1.5, based on large eddy simulation combined with the finite volume method. The wake structure characteristics and control mechanisms of both slotted and standard micro-ramps are presented and discussed. The results show that the wake of standard micro-ramp includes a primary counter-rotating streamwise vortex pair, a train of vortex rings, and secondary vortices. The slotted micro-ramp has more complicated wake structures, which contain a confluent counter-rotating streamwise vortex pair and additional streamwise vortices, with the same rotation generated by slot and the vortex rings enveloping the vortex pair. The additional vortices generated by the slot of the micro-ramp can mix with the primary counter-rotating vortex pair, extend the life time, and strengthen the vortex intensity of primary vortex pair. Moreover, the slot can effectively alleviate, or even eliminate the backflow and decrease the profile drag induced by the standard micro-ramp, therefore improving the efficiency of separation control. (paper)

Slot technique - an alternative method of scatter reduction in radiography

International Nuclear Information System (INIS)

Panzer, W.; Widenmann, L.

1983-01-01

The most common method of scatter reduction in radiography is the use of an antiscatter grid. Its disadvantage is the absorption of a certain percentage of primary radiation in the lead strips of the grid and the fact that due to the limited thickness of the lead strips their scatter absorption is also limited. A possibility for avoiding this disadvantage is offered by the so-called slot technique, ie, the successive exposure of the subject with a narrow fan beam provided by slots in rather thick lead plates. The results of a comparison between grid and slot technique regarding dose to the patient, scatter reduction, image quality and the effect of automatic exposure control are reported. (author)

Cusp-Gun Sixth-Harmonic Slotted Gyrotron

Science.gov (United States)

Stutzman, R. C.; McDermott, D. B.; Hirata Luhmann, Y., Jr.; Gallagher, D. A.; Spencer, T. A.

2000-10-01

A high-harmonic slotted gyrotron has been constructed at UC Davis to be driven by a 70 kV, 3.5 A, axis-encircling electron beam from a Northrop Grumman Cusp gun. The 94 GHz, slotted sixth-harmonic gyrotron is predicted to generate 50 kW with an efficiency of 20%. Using the profile of the adiabatic field reversal from the UC Davis superconducting test-magnet, EGUN simulations predict that an axis-encircling electron beam will be generated with an axial velocity spread of Δ v_z/v_z=10% for the desired velocity ratio of α =v_z/v_z=1.5. The design will also be presented for an 8th-harmonic W-band gyrotron whose magnetic field can be supplied by a lightweight permanent magnet.

Optimal Conditional Reachability for Multi-Priced Timed Automata

DEFF Research Database (Denmark)

Larsen, Kim Guldstrand; Rasmussen, Jacob Illum

2005-01-01

In this paper, we prove decidability of the optimal conditional reachability problem for multi-priced timed automata, an extension of timed automata with multiple cost variables evolving according to given rates for each location. More precisely, we consider the problem of determining the minimal...

Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Chen, Qingwei

2016-01-01

Most of the existing works addressing reliability redundancy allocation problems are based on the assumption of fixed reliabilities of components. In real-life situations, however, the reliabilities of individual components may be imprecise, most often given as intervals, under different operating or environmental conditions. This paper deals with reliability redundancy allocation problems modeled in an interval environment. An interval multi-objective optimization problem is formulated from the original crisp one, where system reliability and cost are simultaneously considered. To render the multi-objective particle swarm optimization (MOPSO) algorithm capable of dealing with interval multi-objective optimization problems, a dominance relation for interval-valued functions is defined with the help of our newly proposed order relations of interval-valued numbers. Then, the crowding distance is extended to the multi-objective interval-valued case. Finally, the effectiveness of the proposed approach has been demonstrated through two numerical examples and a case study of supervisory control and data acquisition (SCADA) system in water resource management. - Highlights: • We model the reliability redundancy allocation problem in an interval environment. • We apply the particle swarm optimization directly on the interval values. • A dominance relation for interval-valued multi-objective functions is defined. • The crowding distance metric is extended to handle imprecise objective functions.

Tri-Band CPW-Fed Stub-Loaded Slot Antenna Design for WLAN/WiMAX Applications

Science.gov (United States)

Li, Jianxing; Guo, Jianying; He, Bin; Zhang, Anxue; Liu, Qing Huo

2016-11-01

A novel uniplanar CPW-fed tri-band stub-loaded slot antenna is proposed for wireless local area network (WLAN) and worldwide interoperability for microwave access (WiMAX) applications. Dual resonant modes were effectively excited in the upper band by using two identical pairs of slot stubs and parasitic slots symmetrically along the arms of a traditional CPW-fed slot dipole, achieving a much wider bandwidth. The middle band was realized by the fundamental mode of the slot dipole. To obtain the lower band, two identical inverted-L-shaped open-ended slots were symmetrically etched in the ground plane. A prototype was fabricated and measured, showing that tri-band operation with 10-dB return loss bandwidths of 150 MHz from 2.375 to 2.525 GHz, 725 MHz from 3.075 to 3.8 GHz, and 1.9 GHz from 5.0 to 6.9 GHz has been achieved. Details of the antenna design as well as the measured and simulated results are presented and discussed.

Multi-material size optimization of a ladder frame chassis

Science.gov (United States)

Baker, Michael

The Corporate Average Fuel Economy (CAFE) is an American fuel standard that sets regulations on fuel economy in vehicles. This law ultimately shapes the development and design research for automakers. Reducing the weight of conventional cars offers a way to improve fuel efficiency. This research investigated the optimality of an automobile's ladder frame chassis (LFC) by conducting multi-objective optimization on the LFC in order to reduce the weight of the chassis. The focus of the design and optimization was a ladder frame chassis commonly used for mass production light motor vehicles with an open-top rear cargo area. This thesis is comprised of two major sections. The first looked to perform thickness optimization in the outer walls of the ladder frame. In the second section, many multi-material distributions, including steel and aluminium varieties, were investigated. A simplified model was used to do an initial hand calculation analysis of the problem. This was used to create a baseline validation to compare the theory with the modeling. A CAD model of the LFC was designed. From the CAD model, a finite element model was extracted and joined using weld and bolt connectors. Following this, a linear static analysis was performed to look at displacement and stresses when subjected to loading conditions that simulate harsh driving conditions. The analysis showed significant values of stress and displacement on the ends of the rails, suggesting improvements could be made elsewhere. An optimization scheme was used to find the values of an all steel frame an optimal thickness distribution was found. This provided a 13% weight reduction over the initial model. To advance the analysis a multi-material approach was used to push the weight savings even further. Several material distributions were analyzed and the lightest utilized aluminium in all but the most strenuous subjected components. This enabled a reduction in weight of 15% over the initial model, equivalent to

Optimizing multi-pinhole SPECT geometries using an analytical model

International Nuclear Information System (INIS)

Rentmeester, M C M; Have, F van der; Beekman, F J

2007-01-01

State-of-the-art multi-pinhole SPECT devices allow for sub-mm resolution imaging of radio-molecule distributions in small laboratory animals. The optimization of multi-pinhole and detector geometries using simulations based on ray-tracing or Monte Carlo algorithms is time-consuming, particularly because many system parameters need to be varied. As an efficient alternative we develop a continuous analytical model of a pinhole SPECT system with a stationary detector set-up, which we apply to focused imaging of a mouse. The model assumes that the multi-pinhole collimator and the detector both have the shape of a spherical layer, and uses analytical expressions for effective pinhole diameters, sensitivity and spatial resolution. For fixed fields-of-view, a pinhole-diameter adapting feedback loop allows for the comparison of the system resolution of different systems at equal system sensitivity, and vice versa. The model predicts that (i) for optimal resolution or sensitivity the collimator layer with pinholes should be placed as closely as possible around the animal given a fixed detector layer, (ii) with high-resolution detectors a resolution improvement up to 31% can be achieved compared to optimized systems, (iii) high-resolution detectors can be placed close to the collimator without significant resolution losses, (iv) interestingly, systems with a physical pinhole diameter of 0 mm can have an excellent resolution when high-resolution detectors are used

Optimal Allocation of Generalized Power Sources in Distribution Network Based on Multi-Objective Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Li Ran

2017-01-01

Full Text Available Optimal allocation of generalized power sources in distribution network is researched. A simple index of voltage stability is put forward. Considering the investment and operation benefit, the stability of voltage and the pollution emissions of generalized power sources in distribution network, a multi-objective optimization planning model is established. A multi-objective particle swarm optimization algorithm is proposed to solve the optimal model. In order to improve the global search ability, the strategies of fast non-dominated sorting, elitism and crowding distance are adopted in this algorithm. Finally, tested the model and algorithm by IEEE-33 node system to find the best configuration of GP, the computed result shows that with the generalized power reasonable access to the active distribution network, the investment benefit and the voltage stability of the system is improved, and the proposed algorithm has better global search capability.

FLOW VISUALIZATION OF RECTANGULAR SLOT AIR JET IMPINGEMENT ON FLAT SURFACES

OpenAIRE

Satheesha V *1, B. K. Muralidhra2, Abhilash N3, C. K. Umesh4

2018-01-01

Jet impingement near the mid-chord of the gas turbine blade is treated as a flat plate. Experimental and numerical investigations are carried out for a single slot air jet impinging on flat surface for two different rectangular slots of dimension (3mm x 65 mm) and (5mm x 65 mm). Experimentation is done to study the flow pattern topography on the flat target plate, with varying the flow rate from 20 LPM to 50 LPM by varying the nozzle to plate distance from 9 mm to 24 mm for slot jet of 3mm an...

Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

International Nuclear Information System (INIS)

Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

2016-01-01

Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent

BWROPT: A multi-cycle BWR fuel cycle optimization code

Energy Technology Data Exchange (ETDEWEB)

Ottinger, Keith E.; Maldonado, G. Ivan, E-mail: Ivan.Maldonado@utk.edu

2015-09-15

Highlights: • A multi-cycle BWR fuel cycle optimization algorithm is presented. • New fuel inventory and core loading pattern determination. • The parallel simulated annealing algorithm was used for the optimization. • Variable sampling probabilities were compared to constant sampling probabilities. - Abstract: A new computer code for performing BWR in-core and out-of-core fuel cycle optimization for multiple cycles simultaneously has been developed. Parallel simulated annealing (PSA) is used to optimize the new fuel inventory and placement of new and reload fuel for each cycle considered. Several algorithm improvements were implemented and evaluated. The most significant of these are variable sampling probabilities and sampling new fuel types from an ordered array. A heuristic control rod pattern (CRP) search algorithm was also implemented, which is useful for single CRP determinations, however, this feature requires significant computational resources and is currently not practical for use in a full multi-cycle optimization. The PSA algorithm was demonstrated to be capable of significant objective function reduction and finding candidate loading patterns without constraint violations. The use of variable sampling probabilities was shown to reduce runtime while producing better results compared to using constant sampling probabilities. Sampling new fuel types from an ordered array was shown to have a mixed effect compared to random new fuel type sampling, whereby using both random and ordered sampling produced better results but required longer runtimes.

Application of evolutionary algorithms for multi-objective optimization in VLSI and embedded systems

CERN Document Server

2015-01-01

This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design. Many complex engineering optimization problems can be modelled as multi-objective formulations. This book provides an introduction to multi-objective optimization using meta-heuristic algorithms, GA and PSO, and how they can be applied to problems like hardware/software partitioning in embedded systems, circuit partitioning in VLSI, design of operational amplifiers in analog VLSI, design space exploration in high-level synthesis, delay fault testing in VLSI testing, and scheduling in heterogeneous distributed systems. It is shown how, in each case, the various aspects of the EA, namely its representation, and operators like crossover, mutation, etc. can be separately formulated to solve these problems. This book is intended for design engineers and researchers in the field ...

Multi-objective optimization of a plate and frame heat exchanger via genetic algorithm

Energy Technology Data Exchange (ETDEWEB)

Najafi, Hamidreza; Najafi, Behzad [K. N. Toosi University of Technology, Department of Mechanical Engineering, Tehran (Iran)

2010-06-15

In the present paper, a plate and frame heat exchanger is considered. Multi-objective optimization using genetic algorithm is developed in order to obtain a set of geometric design parameters, which lead to minimum pressure drop and the maximum overall heat transfer coefficient. Vividly, considered objective functions are conflicting and no single solution can satisfy both objectives simultaneously. Multi-objective optimization procedure yields a set of optimal solutions, called Pareto front, each of which is a trade-off between objectives and can be selected by the user, regarding the application and the project's limits. The presented work takes care of numerous geometric parameters in the presence of logical constraints. A sensitivity analysis is also carried out to study the effects of different geometric parameters on the considered objective functions. Modeling the system and implementing the multi-objective optimization via genetic algorithm has been performed by MATLAB. (orig.)

An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning

Directory of Open Access Journals (Sweden)

Nizar Hadi Abbas

2016-07-01

Full Text Available This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In order to evaluate the proposed algorithm in term of finding the best solution, six benchmark test functions are used to make a comparison between AMOPSO and the standard MOPSO. The results show that the AMOPSO has a better ability to get away from local optimums with a quickest convergence than the MOPSO. The simulation results using Matlab 2014a, indicate that this methodology is extremely valuable for every robot in multi-robot framework to discover its own particular proper pa‌th from the start to the destination position with minimum distance and time.

Investigations into the Optimization of Multi-Source Strength Brachytherapy Treatment Procedures

CERN Document Server

Henderson, D L; Yoo, S

2002-01-01

The goal of this project is to investigate the use of multi-strength and multi-specie radioactive sources in permanent prostate implant brachytherapy. In order to fulfill the requirement for an optimal dose distribution, the prescribed dose should be delivered to the target in a nearly uniform dose distribution while simultaneously sparing sensitive structures. The treatment plan should use a small number of needles and sources while satisfying the treatment requirements. The hypothesis for the use of multi-strength and/or multi-specie sources is that a better treatment plan using fewer sources and needles could be obtained than by treatment plans using single-strength sources could reduce the overall number of sources used for treatment. We employ a recently developed greedy algorithm based on the adjoint concept as the optimization search engine. The algorithm utilizes and ''adjoint ratio'', which provides a means of ranking source positions, as the pseudo-objective function. It ha s been shown that the gre...

Optimization of machining parameters of turning operations based on multi performance criteria

Directory of Open Access Journals (Sweden)

N.K.Mandal

2013-01-01

Full Text Available The selection of optimum machining parameters plays a significant role to ensure quality of product, to reduce the manufacturing cost and to increase productivity in computer controlled manufacturing process. For many years, multi-objective optimization of turning based on inherent complexity of process is a competitive engineering issue. This study investigates multi-response optimization of turning process for an optimal parametric combination to yield the minimum power consumption, surface roughness and frequency of tool vibration using a combination of a Grey relational analysis (GRA. Confirmation test is conducted for the optimal machining parameters to validate the test result. Various turning parameters, such as spindle speed, feed and depth of cut are considered. Experiments are designed and conducted based on full factorial design of experiment.

Small angle slot divertor concept for long pulse advanced tokamaks

Science.gov (United States)

Guo, H. Y.; Sang, C. F.; Stangeby, P. C.; Lao, L. L.; Taylor, T. S.; Thomas, D. M.

2017-04-01

SOLPS-EIRENE edge code analysis shows that a gas-tight slot divertor geometry with a small-angle (glancing-incidence) target, named the small angle slot (SAS) divertor, can achieve cold, dissipative/detached divertor conditions at relatively low values of plasma density at the outside midplane separatrix. SAS exhibits the following key features: (1) strong enhancement of the buildup of neutral density in a localized region near the plasma strike point on the divertor target; (2) spreading of the cooling front across the divertor target with the slot gradually flaring out from the strike point, thus effectively reducing both heat flux and erosion on the entire divertor target surface. Such a divertor may potentially provide a power and particle handling solution for long pulse advanced tokamaks.

Multi-period mean–variance portfolio optimization based on Monte-Carlo simulation

NARCIS (Netherlands)

F. Cong (Fei); C.W. Oosterlee (Kees)

2016-01-01

htmlabstractWe propose a simulation-based approach for solving the constrained dynamic mean– variance portfolio managemen tproblem. For this dynamic optimization problem, we first consider a sub-optimal strategy, called the multi-stage strategy, which can be utilized in a forward fashion. Then,

Energy optimization methodology of multi-chiller plant in commercial buildings

International Nuclear Information System (INIS)

Thangavelu, Sundar Raj; Myat, Aung; Khambadkone, Ashwin

2017-01-01

This study investigates the potential energy savings in commercial buildings through optimized operation of a multi-chiller plant. The cooling load contributes 45–60% of total power consumption in commercial and office buildings, especially at tropics. The chiller plant operation is not optimal in most of the existing buildings because the chiller plant is either operated at design condition irrespective of the cooling load or optimized locally due to lack of overall chiller plant behavior. In this study, an overall energy model of chiller plant is developed to capture the thermal behavior of all systems and their interactions including the power consumption. An energy optimization methodology is proposed to derive optimized operation decisions for chiller plant at regular intervals based on building thermal load and weather condition. The benefits of proposed energy optimization methodology are examined using case study problems covering different chiller plant configurations. The case studies result confirmed the energy savings achieved through optimized operations is up to 40% for moderate size chiller plant and around 20% for small chiller plant which consequently reduces the energy cost and greenhouse gas emissions. - Highlights: • Energy optimization methodology improves the performance of multi-chiller plant. • Overall energy model of chiller plant accounts all equipment and the interactions. • Operation decisions are derived at regular interval based on time-varying factors. • Three case studies confirmed 20 to 40% of energy savings than conventional method.

Optimization of orthotropic distributed-mode loudspeaker using attached masses and multi-exciters.

Science.gov (United States)

Lu, Guochao; Shen, Yong; Liu, Ziyun

2012-02-01

Based on the orthotropic model of the plate, the method to optimize the sound response of the distributed-mode loudspeaker (DML) using the attached masses and the multi-exciters has been investigated. The attached masses method will rebuild the modes distribution of the plate, based on which multi-exciter method will smooth the sound response. The results indicate that the method can be used to optimize the sound response of the DML. © 2012 Acoustical Society of America

Three essays on multi-level optimization models and applications

Science.gov (United States)

Rahdar, Mohammad

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation

Cogging Torque Reduction by Slot-Opening Shift for Permanent Magnet Machines

DEFF Research Database (Denmark)

Liu, Ting; Huang, Shoudao; Gao, Jian

2013-01-01

In this paper, an effective cogging torque reduction method based on shifting the slot-openings is presented. Stator teeth are divided into groups and proper slot-opening shift is applied for each group. The cogging torque can then be greatly reduced while the back-EMF waveforms remain symmetrical...

Evolutionary optimization and game strategies for advanced multi-disciplinary design applications to aeronautics and UAV design

CERN Document Server

Periaux, Jacques; Lee, Dong Seop Chris

2015-01-01

Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with c...

Study on hybrid multi-objective optimization algorithm for inverse treatment planning of radiation therapy

International Nuclear Information System (INIS)

Li Guoli; Song Gang; Wu Yican

2007-01-01

Inverse treatment planning for radiation therapy is a multi-objective optimization process. The hybrid multi-objective optimization algorithm is studied by combining the simulated annealing(SA) and genetic algorithm(GA). Test functions are used to analyze the efficiency of algorithms. The hybrid multi-objective optimization SA algorithm, which displacement is based on the evolutionary strategy of GA: crossover and mutation, is implemented in inverse planning of external beam radiation therapy by using two kinds of objective functions, namely the average dose distribution based and the hybrid dose-volume constraints based objective functions. The test calculations demonstrate that excellent converge speed can be achieved. (authors)

Application of multi response optimization with grey relational analysis and fuzzy logic method

Science.gov (United States)

Winarni, Sri; Wahyu Indratno, Sapto

2018-01-01

Multi-response optimization is an optimization process by considering multiple responses simultaneously. The purpose of this research is to get the optimum point on multi-response optimization process using grey relational analysis and fuzzy logic method. The optimum point is determined from the Fuzzy-GRG (Grey Relational Grade) variable which is the conversion of the Signal to Noise Ratio of the responses involved. The case study used in this research are case optimization of electrical process parameters in electrical disharge machining. It was found that the combination of treatments resulting to optimum MRR and SR was a 70 V gap voltage factor, peak current 9 A and duty factor 0.8.

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

Hydraulic performance of a low specific speed centrifugal pump with Spanwise-Slotted Blades

International Nuclear Information System (INIS)

Ye, D X; Li, H; Wang, Y

2013-01-01

The hydraulic efficiency of a low specific speed centrifugal pump is low because of the long and narrow meridian flow passage, and the severe disk friction. Spanwise slotted blade flow control technology has been applied to the low specific speed centrifugal pump. This paper concluded that spanwise slotted blades can improve the pump performance in both experiments and simulations. In order to study the influence to the impeller and volute by spanwise slotted blade, impeller efficiency and volute efficiency were defined. The minimum volute efficiency and the maximum pump efficiency appear at the same time in the design flow condition in the unsteady simulation. The mechanism of spanwise slotted blade flow control technology should be researched furthermore

Effective multi-objective optimization of Stirling engine systems

International Nuclear Information System (INIS)

Punnathanam, Varun; Kotecha, Prakash

2016-01-01

Highlights: • Multi-objective optimization of three recent Stirling engine models. • Use of efficient crossover and mutation operators for real coded Genetic Algorithm. • Demonstrated supremacy of the strategy over the conventionally used algorithm. • Improvements of up to 29% in comparison to literature results. - Abstract: In this article we demonstrate the supremacy of the Non-dominated Sorting Genetic Algorithm-II with Simulated Binary Crossover and Polynomial Mutation operators for the multi-objective optimization of Stirling engine systems by providing three examples, viz., (i) finite time thermodynamic model, (ii) Stirling engine thermal model with associated irreversibility and (iii) polytropic finite speed based thermodynamics. The finite time thermodynamic model involves seven decision variables and consists of three objectives: output power, thermal efficiency and rate of entropy generation. In comparison to literature, it was observed that the used strategy provides a better Pareto front and leads to improvements of up to 29%. The performance is also evaluated on a Stirling engine thermal model which considers the associated irreversibility of the cycle and consists of three objectives involving eleven decision variables. The supremacy of the suggested strategy is also demonstrated on the experimentally validated polytropic finite speed thermodynamics based Stirling engine model for optimization involving two objectives and ten decision variables.

Thermodynamic design of Stirling engine using multi-objective particle swarm optimization algorithm

International Nuclear Information System (INIS)

Duan, Chen; Wang, Xinggang; Shu, Shuiming; Jing, Changwei; Chang, Huawei

2014-01-01

Highlights: • An improved thermodynamic model taking into account irreversibility parameter was developed. • A multi-objective optimization method for designing Stirling engine was investigated. • Multi-objective particle swarm optimization algorithm was adopted in the area of Stirling engine for the first time. - Abstract: In the recent years, the interest in Stirling engine has remarkably increased due to its ability to use any heat source from outside including solar energy, fossil fuels and biomass. A large number of studies have been done on Stirling cycle analysis. In the present study, a mathematical model based on thermodynamic analysis of Stirling engine considering regenerative losses and internal irreversibilities has been developed. Power output, thermal efficiency and the cycle irreversibility parameter of Stirling engine are optimized simultaneously using Particle Swarm Optimization (PSO) algorithm, which is more effective than traditional genetic algorithms. In this optimization problem, some important parameters of Stirling engine are considered as decision variables, such as temperatures of the working fluid both in the high temperature isothermal process and in the low temperature isothermal process, dead volume ratios of each heat exchanger, volumes of each working spaces, effectiveness of the regenerator, and the system charge pressure. The Pareto optimal frontier is obtained and the final design solution has been selected by Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP). Results show that the proposed multi-objective optimization approach can significantly outperform traditional single objective approaches

Multi-objective PID Optimization for Speed Control of an Isolated Steam Turbine using Gentic Algorithm

OpenAIRE

Sanjay Kr. Singh; D. Boolchandani; S.G. Modani; Nitish Katal

2014-01-01

This study focuses on multi-objective optimization of the PID controllers for optimal speed control for an isolated steam turbine. In complex operations, optimal tuning plays an imperative role in maintaining the product quality and process safety. This study focuses on the comparison of the optimal PID tuning using Multi-objective Genetic Algorithm (NSGA-II) against normal genetic algorithm and Ziegler Nichols methods for the speed control of an isolated steam turbine. Isolated steam turbine...

Realistic Free-Spins Features Increase Preference for Slot Machines.

Science.gov (United States)

Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

2017-06-01

Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

14 CFR 93.226 - Allocation of slots in low-demand periods.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 2 2010-01-01 2010-01-01 false Allocation of slots in low-demand periods. 93.226 Section 93.226 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF... low-demand periods. (a) If there are available slots in the following time periods and there are no...

Elevated CPW-Fed Slotted Microstrip Antenna for Ultra-Wideband Application

Directory of Open Access Journals (Sweden)

Chandan Kumar Ghosh

2012-01-01

Full Text Available Elevated-coplanar-waveguide- (ECPW- fed microstrip antenna with inverted “G” slots in the back conductor is presented. It is modeled and analyzed for the application of multiple frequency bands. The changes in radiation and the transmission characteristics are investigated by the introduction of the slots in two different positions at the ground plane (back conductor. The proposed antenna without slots exhibits a stop band from 2.55 GHz to 4.25 GHz while introducing two slots on the back conductor, two adjacent poles appear at central frequencies of 3.0 GHz and 3.9 GHz, respectively, and the antenna shows the ultra-wideband (UWB characteristics. The first pole appears at the central frequency of 3.0 GHz and covers the band width of 950 MHz, and the second pole exists at a central frequency of 3.90 GHz covering a bandwidth of 750 MHz. Experimental result shows that impedance bandwidth of 129% (S11<-10 dB is well achieved when the antenna is excited with both slots. Compared to most of the previously reported ECPW structures, the impedance bandwidth of this antenna is increased and also the size of the antenna becomes smaller and more suitable for many wireless applications like PCS (1850–1990 MHz, WLAN (2.4–2.484 GHz, WiMAX (2.5–2.69 GHz and 5.15–5.85 GHz, and also X-band communication.

Development of a Multi-Event Trajectory Optimization Tool for Noise-Optimized Approach Route Design

NARCIS (Netherlands)

Braakenburg, M.L.; Hartjes, S.; Visser, H.G.; Hebly, S.J.

2011-01-01

This paper presents preliminary results from an ongoing research effort towards the development of a multi-event trajectory optimization methodology that allows to synthesize RNAV approach routes that minimize a cumulative measure of noise, taking into account the total noise effect aggregated for

Multi-step optimization strategy for fuel-optimal orbital transfer of low-thrust spacecraft

Science.gov (United States)

Rasotto, M.; Armellin, R.; Di Lizia, P.

2016-03-01

An effective method for the design of fuel-optimal transfers in two- and three-body dynamics is presented. The optimal control problem is formulated using calculus of variation and primer vector theory. This leads to a multi-point boundary value problem (MPBVP), characterized by complex inner constraints and a discontinuous thrust profile. The first issue is addressed by embedding the MPBVP in a parametric optimization problem, thus allowing a simplification of the set of transversality constraints. The second problem is solved by representing the discontinuous control function by a smooth function depending on a continuation parameter. The resulting trajectory optimization method can deal with different intermediate conditions, and no a priori knowledge of the control structure is required. Test cases in both the two- and three-body dynamics show the capability of the method in solving complex trajectory design problems.

An Agent-Based Co-Evolutionary Multi-Objective Algorithm for Portfolio Optimization

Directory of Open Access Journals (Sweden)

Rafał Dreżewski

2017-08-01

Full Text Available Algorithms based on the process of natural evolution are widely used to solve multi-objective optimization problems. In this paper we propose the agent-based co-evolutionary algorithm for multi-objective portfolio optimization. The proposed technique is compared experimentally to the genetic algorithm, co-evolutionary algorithm and a more classical approach—the trend-following algorithm. During the experiments historical data from the Warsaw Stock Exchange is used in order to assess the performance of the compared algorithms. Finally, we draw some conclusions from these experiments, showing the strong and weak points of all the techniques.

Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2004-01-01

We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

Design Optimization of Multi-Cluster Embedded Systems for Real-Time Applications

DEFF Research Database (Denmark)

Pop, Paul; Eles, Petru; Peng, Zebo

2006-01-01

We present an approach to design optimization of multi-cluster embedded systems consisting of time-triggered and event-triggered clusters, interconnected via gateways. In this paper, we address design problems which are characteristic to multi-clusters: partitioning of the system functionality...... into time-triggered and event-triggered domains, process mapping, and the optimization of parameters corresponding to the communication protocol. We present several heuristics for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving...... an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....

Modeling and characterization of electret based vibration energy harvesters in slot-effect configuration

International Nuclear Information System (INIS)

Renaud, M; Altena, G; Elfrink, R; Goedbloed, M; De Nooijer, C; Van Schaijk, R

2015-01-01

The purpose of this article is to elaborate a model and the optimization guidelines for electret based harvesters with a specific electret/electrodes configuration, namely the slot-effect configuration. Slot-effect configured harvesters have been investigated experimentally by several research groups. A model describing their dynamic behavior has also been recently proposed in the literature. However, the simplifications used in the existing model can lead to inaccuracies and a refined analysis is elaborated in the present article. The model is compared with experimental measurements on MEMS fabricated devices with a corrugated electret. The electrodes dimensioning in the MEMS device are chosen so that the harvester behaves in a quasi-linear manner over its full range of displacement. This quasi-linearity simplifies greatly the device optimization. Indeed, the behavior of the developed electrostatic harvester is shown to be very comparable to that of piezoelectric harvesters, which are very well understood and documented. The influence of several design parameters on output power performance is investigated. As long as pull-in and breakdown voltage effects can be avoided, the electret surface potential should be maximized and the air gap minimized. We also investigate theoretically the influence of three types of electret on the generated power: planar, corrugated with partial charge coverage, and corrugated with full charge coverage. With the dimensions corresponding to our MEMS devices, the output power characteristics for the three types of electret are similar. However, it is shown that this is not always true. In some conditions, corrugated electrets with full charge coverage are detrimental for the generated power. (paper)

Numerical study on non-locally reacting behavior of nacelle liners incorporating drainage slots

Science.gov (United States)

Chen, Chao; Li, Xiaodong; Thiele, Frank

2018-06-01

For acoustic liners used in current commercial nacelles, in order to prevent any liquid accumulating in the resonators, drainage slots are incorporated on the partition walls between closely packed cavities. Recently, an experimental study conducted by Busse-Gerstengarbe et al. shown that the cell interaction introduced by drainage slots causes an additional dissipation peak which increases with the size of the slot. However, the variation of damping process due to drainage slots is still not fully understood. Therefore, a numerical study based on computational aeroacoustic methods is carried out to investigate the mechanism of the changed attenuation characteristics due to drainage slots in presence of grazing incident sound waves with low or high intensities. Different slot configurations are designed based on the generic non-locally reacting liner model adopted in the experimental investigation. Both 2-D and 3-D numerical simulations of only slit resonators are carried out. Numerical results indicate that the extra peak is a result of a resonance excited in the second cavity at specific frequency. Under high sound pressure level incoming waves, the basic characteristics of the acoustic performance remain. However, vortex shedding transpires at the resonances around both the slits and the drainage slot. Vorticity contours show that the connection of two coupled cavities decreases the strength of vortex shedding around the basic Helmholtz resonance due to a higher energy reflection. Meanwhile, the cell interaction significantly increases the vorticity magnitude near the extra resonant frequency. Finally, a semi-empirical model is derived to predict the extra attenuation peak frequency.

Slotted Photonic Crystal Sensors

Science.gov (United States)

Scullion, Mark G.; Krauss, Thomas F.; Di Falco, Andrea

2013-01-01

Optical biosensors are increasingly being considered for lab-on-a-chip applications due to their benefits such as small size, biocompatibility, passive behaviour and lack of the need for fluorescent labels. The light guiding mechanisms used by many of them results in poor overlap of the optical field with the target molecules, reducing the maximum sensitivity achievable. This review article presents a new platform for optical biosensors, namely slotted photonic crystals, which provide higher sensitivities due to their ability to confine, spatially and temporally, the optical mode peak within the analyte itself. Loss measurements showed values comparable to standard photonic crystals, confirming their ability to be used in real devices. A novel resonant coupler was designed, simulated, and experimentally tested, and was found to perform better than other solutions within the literature. Combining with cavities, microfluidics and biological functionalization allowed proof-of-principle demonstrations of protein binding to be carried out. Higher sensitivities were observed in smaller structures than possible with most competing devices reported in the literature. This body of work presents slotted photonic crystals as a realistic platform for complete on-chip biosensing; addressing key design, performance and application issues, whilst also opening up exciting new ideas for future study. PMID:23503295

Slotted Photonic Crystal Sensors

Directory of Open Access Journals (Sweden)

Andrea Di Falco

2013-03-01

Full Text Available Optical biosensors are increasingly being considered for lab-on-a-chip applications due to their benefits such as small size, biocompatibility, passive behaviour and lack of the need for fluorescent labels. The light guiding mechanisms used by many of them results in poor overlap of the optical field with the target molecules, reducing the maximum sensitivity achievable. This review article presents a new platform for optical biosensors, namely slotted photonic crystals, which provide higher sensitivities due to their ability to confine, spatially and temporally, the optical mode peak within the analyte itself. Loss measurements showed values comparable to standard photonic crystals, confirming their ability to be used in real devices. A novel resonant coupler was designed, simulated, and experimentally tested, and was found to perform better than other solutions within the literature. Combining with cavities, microfluidics and biological functionalization allowed proof-of-principle demonstrations of protein binding to be carried out. Higher sensitivities were observed in smaller structures than possible with most competing devices reported in the literature. This body of work presents slotted photonic crystals as a realistic platform for complete on-chip biosensing; addressing key design, performance and application issues, whilst also opening up exciting new ideas for future study.

Low profile frequency agile MIMO slot antenna with TCM characterization

KAUST Repository

Ghalib, Asim

2017-06-07

In this paper, a frequency reconfigurable multiple-input-multiple-output (MIMO) slot antenna is presented. The proposed design is low profile and compact with wide tunability range, covering several well-known frequency bands from 1800 MHz to 2450 MHz. The frequency reconfigurability is achieved by loading the annular slot with varactor diodes. The antenna system is also analyzed for MIMO performance metrics. Moreover, the effect of circular slot antenna on the chassis modes is also investigated using the theory of characteristic modes (TCM). The physical principle behind frequency reconfigurability is also investigated using TCM analysis. An interesting finding is observed using varactor diodes for frequency reconfigurability, that is the reactive impedance loading does not alter the modal significance (MS) plots but only aid in the input impedance matching at different frequency bands.

Dual-mode nested search method for categorical uncertain multi-objective optimization

Science.gov (United States)

Tang, Long; Wang, Hu

2016-10-01

Categorical multi-objective optimization is an important issue involved in many matching design problems. Non-numerical variables and their uncertainty are the major challenges of such optimizations. Therefore, this article proposes a dual-mode nested search (DMNS) method. In the outer layer, kriging metamodels are established using standard regular simplex mapping (SRSM) from categorical candidates to numerical values. Assisted by the metamodels, a k-cluster-based intelligent sampling strategy is developed to search Pareto frontier points. The inner layer uses an interval number method to model the uncertainty of categorical candidates. To improve the efficiency, a multi-feature convergent optimization via most-promising-area stochastic search (MFCOMPASS) is proposed to determine the bounds of objectives. Finally, typical numerical examples are employed to demonstrate the effectiveness of the proposed DMNS method.

Multi-Objective Optimization in Physical Synthesis of Integrated Circuits

CERN Document Server

A Papa, David

2013-01-01

This book introduces techniques that advance the capabilities and strength of modern software tools for physical synthesis, with the ultimate goal to improve the quality of leading-edge semiconductor products.  It provides a comprehensive introduction to physical synthesis and takes the reader methodically from first principles through state-of-the-art optimizations used in cutting edge industrial tools. It explains how to integrate chip optimizations in novel ways to create powerful circuit transformations that help satisfy performance requirements. Broadens the scope of physical synthesis optimization to include accurate transformations operating between the global and local scales; Integrates groups of related transformations to break circular dependencies and increase the number of circuit elements that can be jointly optimized to escape local minima;  Derives several multi-objective optimizations from first observations through complete algorithms and experiments; Describes integrated optimization te...

Design of shared unit-dose drug distribution network using multi-level particle swarm optimization.

Science.gov (United States)

Chen, Linjie; Monteiro, Thibaud; Wang, Tao; Marcon, Eric

2018-03-01

Unit-dose drug distribution systems provide optimal choices in terms of medication security and efficiency for organizing the drug-use process in large hospitals. As small hospitals have to share such automatic systems for economic reasons, the structure of their logistic organization becomes a very sensitive issue. In the research reported here, we develop a generalized multi-level optimization method - multi-level particle swarm optimization (MLPSO) - to design a shared unit-dose drug distribution network. Structurally, the problem studied can be considered as a type of capacitated location-routing problem (CLRP) with new constraints related to specific production planning. This kind of problem implies that a multi-level optimization should be performed in order to minimize logistic operating costs. Our results show that with the proposed algorithm, a more suitable modeling framework, as well as computational time savings and better optimization performance are obtained than that reported in the literature on this subject.

Free-time and fixed end-point multi-target optimal control theory: Application to quantum computing

International Nuclear Information System (INIS)

Mishima, K.; Yamashita, K.

2011-01-01

Graphical abstract: The two-state Deutsch-Jozsa algortihm used to demonstrate the utility of free-time and fixed-end point multi-target optimal control theory. Research highlights: → Free-time and fixed-end point multi-target optimal control theory (FRFP-MTOCT) was constructed. → The features of our theory include optimization of the external time-dependent perturbations with high transition probabilities, that of the temporal duration, the monotonic convergence, and the ability to optimize multiple-laser pulses simultaneously. → The advantage of the theory and a comparison with conventional fixed-time and fixed end-point multi-target optimal control theory (FIFP-MTOCT) are presented by comparing data calculated using the present theory with those published previously [K. Mishima, K. Yamashita, Chem. Phys. 361 (2009) 106]. → The qubit system of our interest consists of two polar NaCl molecules coupled by dipole-dipole interaction. → The calculation examples show that our theory is useful for minor adjustment of the external fields. - Abstract: An extension of free-time and fixed end-point optimal control theory (FRFP-OCT) to monotonically convergent free-time and fixed end-point multi-target optimal control theory (FRFP-MTOCT) is presented. The features of our theory include optimization of the external time-dependent perturbations with high transition probabilities, that of the temporal duration, the monotonic convergence, and the ability to optimize multiple-laser pulses simultaneously. The advantage of the theory and a comparison with conventional fixed-time and fixed end-point multi-target optimal control theory (FIFP-MTOCT) are presented by comparing data calculated using the present theory with those published previously [K. Mishima, K. Yamashita, Chem. Phys. 361, (2009), 106]. The qubit system of our interest consists of two polar NaCl molecules coupled by dipole-dipole interaction. The calculation examples show that our theory is useful for minor

Initiative Optimization Operation Strategy and Multi-objective Energy Management Method for Combined Cooling Heating and Power

Institute of Scientific and Technical Information of China (English)

Feng Zhao; Chenghui Zhang; Bo Sun

2016-01-01

This paper proposed an initiative optimization operation strategy and multi-objective energy management method for combined cooling heating and power(CCHP) with storage systems.Initially,the initiative optimization operation strategy of CCHP system in the cooling season,the heating season and the transition season was formulated.The energy management of CCHP system was optimized by the multi-objective optimization model with maximum daily energy efficiency,minimum daily carbon emissions and minimum daily operation cost based on the proposed initiative optimization operation strategy.Furthermore,the pareto optimal solution set was solved by using the niche particle swarm multi-objective optimization algorithm.Ultimately,the most satisfactory energy management scheme was obtained by using the technique for order preference by similarity to ideal solution(TOPSIS) method.A case study of CCHP system used in a hospital in the north of China validated the effectiveness of this method.The results showed that the satisfactory energy management scheme of CCHP system was obtained based on this initiative optimization operation strategy and multi-objective energy management method.The CCHP system has achieved better energy efficiency,environmental protection and economic benefits.

Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle

International Nuclear Information System (INIS)

Lei, Fei; Du, Bin; Liu, Xin; Xie, Xiaoping; Chai, Tian

2016-01-01

In this paper, implicit constrained multi-physics model of a motor wheel for an electric vehicle is built and then optimized. A novel optimization approach is proposed to solve the compliance problem between implicit constraints and stochastic global optimization. Firstly, multi-physics model of motor wheel is built from the theories of structural mechanics, electromagnetism and thermal physics. Then, implicit constraints are applied from the vehicle performances and magnetic characteristics. Implicit constrained optimization is carried out by a series of unconstrained optimization and verifications. In practice, sequentially updated subspaces are designed to completely substitute the original design space in local areas. In each subspace, a solution is obtained and is then verified by the implicit constraints. Optimal solutions which satisfy the implicit constraints are accepted as final candidates. The final global optimal solution is optimized from those candidates. Discussions are carried out to discover the differences between optimal solutions with unconstrained problem and different implicit constrained problems. Results show that the implicit constraints have significant influences on the optimal solution and the proposed approach is effective in finding the optimals. - Highlights: • An implicit constrained multi-physics model is built for sizing a motor wheel. • Vehicle dynamic performances are applied as implicit constraints for nonlinear system. • An efficient novel optimization is proposed to explore the constrained design space. • The motor wheel is optimized to achieve maximum efficiency on vehicle dynamics. • Influences of implicit constraints on vehicle performances are compared and analyzed.

Multi-GPU implementation of a VMAT treatment plan optimization algorithm

International Nuclear Information System (INIS)

Tian, Zhen; Folkerts, Michael; Tan, Jun; Jia, Xun; Jiang, Steve B.; Peng, Fei

2015-01-01

Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is

Multi-GPU implementation of a VMAT treatment plan optimization algorithm

Energy Technology Data Exchange (ETDEWEB)

Tian, Zhen, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Folkerts, Michael; Tan, Jun; Jia, Xun, E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu; Jiang, Steve B., E-mail: Zhen.Tian@UTSouthwestern.edu, E-mail: Xun.Jia@UTSouthwestern.edu, E-mail: Steve.Jiang@UTSouthwestern.edu [Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, Texas 75390 (United States); Peng, Fei [Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213 (United States)

2015-06-15

Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU’s relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors’ group, on a multi-GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors’ method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H and N) cancer case is

Investigation on multi-objective performance optimization algorithm application of fan based on response surface method and entropy method

Science.gov (United States)

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.

Low emittance lattice optimization using a multi-objective evolutionary algorithm

International Nuclear Information System (INIS)

Gao Weiwei; Wang Lin; Li Weimin; He Duohui

2011-01-01

A low emittance lattice design and optimization procedure are systematically studied with a non-dominated sorting-based multi-objective evolutionary algorithm which not only globally searches the low emittance lattice, but also optimizes some beam quantities such as betatron tunes, momentum compaction factor and dispersion function simultaneously. In this paper the detailed algorithm and lattice design procedure are presented. The Hefei light source upgrade project storage ring lattice, with fixed magnet layout, is designed to illustrate this optimization procedure. (authors)

Success probability orientated optimization model for resource allocation of the technological innovation multi-project system

Institute of Scientific and Technical Information of China (English)

Weixu Dai; Weiwei Wu; Bo Yu; Yunhao Zhu

2016-01-01

A success probability orientated optimization model for resource al ocation of the technological innovation multi-project system is studied. Based on the definition of the technological in-novation multi-project system, the leveling optimization of cost and success probability is set as the objective of resource al ocation. The cost function and the probability function of the optimization model are constructed. Then the objective function of the model is constructed and the solving process is explained. The model is applied to the resource al ocation of an enterprise’s technological innovation multi-project system. The results show that the pro-posed model is more effective in rational resource al ocation, and is more applicable in maximizing the utility of the technological innovation multi-project system.

Extended great deluge algorithm for the imperfect preventive maintenance optimization of multi-state systems

International Nuclear Information System (INIS)

Nahas, Nabil; Khatab, Abdelhakim; Ait-Kadi, Daoud; Nourelfath, Mustapha

2008-01-01

This paper deals with preventive maintenance optimization problem for multi-state systems (MSS). This problem was initially addressed and solved by Levitin and Lisnianski [Optimization of imperfect preventive maintenance for multi-state systems. Reliab Eng Syst Saf 2000;67:193-203]. It consists on finding an optimal sequence of maintenance actions which minimizes maintenance cost while providing the desired system reliability level. This paper proposes an approach which improves the results obtained by genetic algorithm (GENITOR) in Levitin and Lisnianski [Optimization of imperfect preventive maintenance for multi-state systems. Reliab Eng Syst Saf 2000;67:193-203]. The considered MSS have a range of performance levels and their reliability is defined to be the ability to meet a given demand. This reliability is evaluated by using the universal generating function technique. An optimization method based on the extended great deluge algorithm is proposed. This method has the advantage over other methods to be simple and requires less effort for its implementation. The developed algorithm is compared to than in Levitin and Lisnianski [Optimization of imperfect preventive maintenance for multi-state systems. Reliab Eng Syst Saf 2000;67:193-203] by using a reference example and two newly generated examples. This comparison shows that the extended great deluge gives the best solutions (i.e. those with minimal costs) for 8 instances among 10

Wideband Circularly Polarized Printed Ring Slot Antenna for 5 GHz – 6 GHz

Science.gov (United States)

Nasrun Osman, Mohamed; Rahim, Mohamad Helmi A.; Jusoh, Muzammil; Sabapathy, Thennarasan; Rahim, Mohamad Kamal A.; Norlyana Azemi, Saidatul

2018-03-01

This paper presents the design of circularly polarized printed slot antenna operating at 5 – 6 GHz. The proposed antenna consists of L-shaped feedline on the top of structure and circular ring slot positioned at the ground plane underneath the substrate as a radiator. A radial and narrow slot in the ground plane provides coupling between the L-shaped feedline and circular ring slot. The circular polarization is realized by implementing the slits perturbation located diagonally to perturb the current flow on the slot structure. The antenna prototype is fabricated on FR4 substrate. The simulated and measured results are compared and analyzed to demonstrate the performance of the antenna. Good measured of simulated results are obtained at the targeted operating frequency. The simulated -10dB reflection coefficient bandwidths and axial ratio are 750 MHz and 165 MHz, respectively. The investigation on the affect of the important parameters towards the reflection coefficient and axial are also presented. The proposed antenna is highly potential to be used for wireless local area network (WLAN) and wireless power transfer (WPT).

Modeling arbitrarily directed slots that are narrow both in width and depth with regard to the FDTD spatial cell

Energy Technology Data Exchange (ETDEWEB)

Riley, D.J.; Turner, C.D.

1991-12-31

The Hybrid Thin-Slot Algorithm (HTSA) integrates a transient integral-equation solution for an aperture in an infinite plane into a finite-difference time-domain (FDTD) code. The technique was introduced for linear apertures and was extended to include wall loss and lossy internal gaskets. A general implementation for arbitrary thin slots is briefly described here. The 3-D FDTD-code TSAR was selected for the implementation. The HTSA does not provide universal solutions to the narrow slot problem, but has merits appropriate for particular applications. The HTSA is restricted to planar slots, but can solve the important case that both the width and depth of the slot are narrow compared to the FDTD spatial cell. IN addition, the HTSA is not bound to the FDTD discrete spatial and time increments, and therefore, high-resolution solutions for the slot physics are possible. The implementation of the HTSA into TSAR is based upon a ``slot data file`` that includes the cell indices where the desired slots are exist within the FDTD mesh. For an HTSA-defined slot, the wall region local to the slot is shorted, and therefore, to change the slot`s topology simply requires altering the file to include the desired cells. 7 refs.

Multi-Target Tracking via Mixed Integer Optimization

Science.gov (United States)

2016-05-13

an easily interpretable global objective function. Furthermore, we propose a greedy heuristic which quickly finds good solutions. We extend both the... heuristic and the MIO model to scenarios with missed detections and false alarms. Index Terms—optimization; multi-target tracking; data asso- ciation...energy in [14] and then again as a minimization of discrete-continuous energy in [15]. These algorithms aim to more accurately represent the nature of the

An improved fast and elitist multi-objective genetic algorithm-ANSGA-II for multi-objective optimization of inverse radiotherapy treatment planning

International Nuclear Information System (INIS)

Cao Ruifen; Li Guoli; Song Gang; Zhao Pan; Lin Hui; Wu Aidong; Huang Chenyu; Wu Yican

2007-01-01

Objective: To provide a fast and effective multi-objective optimization algorithm for inverse radiotherapy treatment planning system. Methods: Non-dominated Sorting Genetic Algorithm-NSGA-II is a representative of multi-objective evolutionary optimization algorithms and excels the others. The paper produces ANSGA-II that makes use of advantage of NSGA-II, and uses adaptive crossover and mutation to improve its flexibility; according the character of inverse radiotherapy treatment planning, the paper uses the pre-known knowledge to generate individuals of every generation in the course of optimization, which enhances the convergent speed and improves efficiency. Results: The example of optimizing average dose of a sheet of CT, including PTV, OAR, NT, proves the algorithm could find satisfied solutions in several minutes. Conclusions: The algorithm could provide clinic inverse radiotherapy treatment planning system with selection of optimization algorithms. (authors)

ATLAS Cold Leg Top Slot Break Analysis using RELAP5

Energy Technology Data Exchange (ETDEWEB)

Sung, Haejung; Lee, Sang Ik; Park, Ju-Hyun; Choi, Tong-Soo [KEPCO NF, Daejeon (Korea, Republic of)

2016-10-15

U.S. Nuclear Regulatory Commission (US-NRC) has been reviewing the design certification application for APR1400 submitted by Korea Electric Power Corporation (KEPCO). The main concern about cold leg top slot break is that cladding temperature might be increased by core uncover due to four loop seal reformation following flooding of safety injection water. An integral effect test for cold leg top slot break was performed by KAERI (Korea Atomic Energy Research Institute) using ATLAS (Advanced Thermal-Hydraulic Test Loop for Accident Simulation), which is a scaled down experimental facility for APR1400. In this study, RELAP5/MOD3.3/Patch04 is assessed by experimental result of ATLAS cold leg top slot break. Also, thermal hydraulic phenomena by four loop seals reformation is observed by RELAP5 result. The RELAP5/MOD3.3/Patch04 is assessed by the experimental result of ATLAS cold leg top slot break. The top slot break is described by offtake model, and the mass flow rate is fairly well estimated. The RELAP5 well predicts the correlation between general trend and four loop seal reformation. The pressure of the core region and the cladding temperature tends to increase during four loop seal reformation due to steam path blockage on four loop seals. It is presumed that the code cannot estimate two phase phenomena by loop seal clearing as same as experiments. In terms of cladding temperature, loop seal reformation due to loop seal elevation of APR1400 does not need to be the issue, since the void fraction at the active top core is maintained over 0.4.

Ensemble based multi-objective production optimization of smart wells

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Jansen, J.D.

2012-01-01

In a recent study two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However this previous study has two limitations: 1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access

A Bandwidth-Optimized Multi-Core Architecture for Irregular Applications

Energy Technology Data Exchange (ETDEWEB)

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

2012-05-31

This paper presents an architecture template for next-generation high performance computing systems specifically targeted to irregular applications. We start our work by considering that future generation interconnection and memory bandwidth full-system numbers are expected to grow by a factor of 10. In order to keep up with such a communication capacity, while still resorting to fine-grained multithreading as the main way to tolerate unpredictable memory access latencies of irregular applications, we show how overall performance scaling can benefit from the multi-core paradigm. At the same time, we also show how such an architecture template must be coupled with specific techniques in order to optimize bandwidth utilization and achieve the maximum scalability. We propose a technique based on memory references aggregation, together with the related hardware implementation, as one of such optimization techniques. We explore the proposed architecture template by focusing on the Cray XMT architecture and, using a dedicated simulation infrastructure, validate the performance of our template with two typical irregular applications. Our experimental results prove the benefits provided by both the multi-core approach and the bandwidth optimization reference aggregation technique.

A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems

International Nuclear Information System (INIS)

Attar, Ahmad; Raissi, Sadigh; Khalili-Damghani, Kaveh

2017-01-01

A simulation-based optimization (SBO) method is proposed to handle multi-objective joint availability-redundancy allocation problem (JARAP). Here, there is no emphasis on probability distributions of time to failures and repair times for multi-state multi-component series-parallel configuration under active, cold and hot standby strategies. Under such conditions, estimation of availability is not a trivial task. First, an efficient computer simulation model is proposed to estimate the availability of the aforementioned system. Then, the estimated availability values are used in a repetitive manner as parameter of a two-objective joint availability-redundancy allocation optimization model through SBO mechanism. The optimization model is then solved using two well-known multi-objective evolutionary computation algorithms, i.e., non-dominated sorting genetic algorithm (NSGA-II), and Strength Pareto Evolutionary Algorithm (SPEA2). The proposed SBO approach is tested using non-exponential numerical example with multi-state repairable components. The results are presented and discussed through different demand scenarios under cold and hot standby strategies. Furthermore, performance of NSGA-II and SPEA2 are statistically compared regarding multi-objective accuracy, and diversity metrics. - Highlights: • A Simulation-Based Optimization (SBO) procedure is introduced for JARAP. • The proposed SBO works for any given failure and repair times. • An efficient simulation procedure is developed to estimate availability. • Customized NSGA-II and SPEA2 are proposed to solve the bi-objective JARAP. • Statistical analysis is employed to test the performance of optimization methods.

Multi-objective optimization of GENIE Earth system models.

Science.gov (United States)

Price, Andrew R; Myerscough, Richard J; Voutchkov, Ivan I; Marsh, Robert; Cox, Simon J

2009-07-13

The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

Multi Dimensional Honey Bee Foraging Algorithm Based on Optimal Energy Consumption

Science.gov (United States)

Saritha, R.; Vinod Chandra, S. S.

2017-10-01

In this paper a new nature inspired algorithm is proposed based on natural foraging behavior of multi-dimensional honey bee colonies. This method handles issues that arise when food is shared from multiple sources by multiple swarms at multiple destinations. The self organizing nature of natural honey bee swarms in multiple colonies is based on the principle of energy consumption. Swarms of multiple colonies select a food source to optimally fulfill the requirements of its colonies. This is based on the energy requirement for transporting food between a source and destination. Minimum use of energy leads to maximizing profit in each colony. The mathematical model proposed here is based on this principle. This has been successfully evaluated by applying it on multi-objective transportation problem for optimizing cost and time. The algorithm optimizes the needs at each destination in linear time.

Cat swarm optimization based evolutionary framework for multi document summarization

Science.gov (United States)

Rautray, Rasmita; Balabantaray, Rakesh Chandra

2017-07-01

Today, World Wide Web has brought us enormous quantity of on-line information. As a result, extracting relevant information from massive data has become a challenging issue. In recent past text summarization is recognized as one of the solution to extract useful information from vast amount documents. Based on number of documents considered for summarization, it is categorized as single document or multi document summarization. Rather than single document, multi document summarization is more challenging for the researchers to find accurate summary from multiple documents. Hence in this study, a novel Cat Swarm Optimization (CSO) based multi document summarizer is proposed to address the problem of multi document summarization. The proposed CSO based model is also compared with two other nature inspired based summarizer such as Harmony Search (HS) based summarizer and Particle Swarm Optimization (PSO) based summarizer. With respect to the benchmark Document Understanding Conference (DUC) datasets, the performance of all algorithms are compared in terms of different evaluation metrics such as ROUGE score, F score, sensitivity, positive predicate value, summary accuracy, inter sentence similarity and readability metric to validate non-redundancy, cohesiveness and readability of the summary respectively. The experimental analysis clearly reveals that the proposed approach outperforms the other summarizers included in the study.

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

International Nuclear Information System (INIS)

Ammar, Karim

2014-01-01

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

Extremely High-Birefringent Asymmetric Slotted-Core Photonic Crystal Fiber in THz Regime

DEFF Research Database (Denmark)

Islam, Raonaqul; Habib, Selim; Hasanuzzaman, G.K.M.

2015-01-01

We present a thorough numerical analysis of a highly birefringent slotted porous-core circular photonic crystal fiber (PCF) for terahertz (THz) wave guidance. The slot shaped air-holes break the symmetry of the porous-core which offers a very high birefringence whereas the compact geometry of the...

Metal membrane with dimer slots as a universal polarizer

DEFF Research Database (Denmark)

Zhukovsky, Sergei; Zalkovskij, Maksim; Malureanu, Radu

2014-01-01

In this work, we show theoretically and confirm experimentally that thin metal membranes patterned with an array of slot dimers (or their Babinet analogue with metal rods) can function as a versatile spectral and polarization filter. We present a detailed covariant multipole theory for the electr......In this work, we show theoretically and confirm experimentally that thin metal membranes patterned with an array of slot dimers (or their Babinet analogue with metal rods) can function as a versatile spectral and polarization filter. We present a detailed covariant multipole theory...

A mixed integer linear programming approach for optimal DER portfolio, sizing, and placement in multi-energy microgrids

International Nuclear Information System (INIS)

Mashayekh, Salman; Stadler, Michael; Cardoso, Gonçalo; Heleno, Miguel

2017-01-01

Highlights: • This paper presents a MILP model for optimal design of multi-energy microgrids. • Our microgrid design includes optimal technology portfolio, placement, and operation. • Our model includes microgrid electrical power flow and heat transfer equations. • The case study shows advantages of our model over aggregate single-node approaches. • The case study shows the accuracy of the integrated linearized power flow model. - Abstract: Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs.

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

Science.gov (United States)

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

Dynamic Channel Slot Allocation Scheme and Performance Analysis of Cyclic Quorum Multichannel MAC Protocol

Directory of Open Access Journals (Sweden)

Xing Hu

2017-01-01

Full Text Available In high diversity node situation, multichannel MAC protocol can improve the frequency efficiency, owing to fewer collisions compared with single-channel MAC protocol. And the performance of cyclic quorum-based multichannel (CQM MAC protocol is outstanding. Based on cyclic quorum system and channel slot allocation, it can avoid the bottleneck that others suffered from and can be easily realized with only one transceiver. To obtain the accurate performance of CQM MAC protocol, a Markov chain model, which combines the channel-hopping strategy of CQM protocol and IEEE 802.11 distributed coordination function (DCF, is proposed. The results of numerical analysis show that the optimal performance of CQM protocol can be obtained in saturation bound situation. And then we obtain the saturation bound of CQM system by bird swarm algorithm. In addition, to improve the performance of CQM protocol in unsaturation situation, a dynamic channel slot allocation of CQM (DCQM protocol is proposed, based on wavelet neural network. Finally, the performance of CQM protocol and DCQM protocol is simulated by Qualnet platform. And the simulation results show that the analytic and simulation results match very well; the DCQM performs better in unsaturation situation.

Polar vessel hullform design based on the multi-objective optimization NSGA II

Directory of Open Access Journals (Sweden)

DUAN Fei

2017-12-01

Full Text Available [Objectives] With the increasing exploitation of the Arctic abundant oil and gas resources, a large number of ships which meet the polar navigational requirements are needed.[Methods] In this paper, the fast elitist Non-Dominated Sorting Genetic Algorithm (NSGA Ⅱ is applied to the hull optimization, and the multi-objective optimization method of polar vessel design is proposed. With the optimization goal of resistance and icebreaking resistance, filtering hull forms through the standard of polar vessel displacement and EEDI, fast ship hull optimization that satisfy the ice-ship dead weight and EEDI requirements has been achieved. Taking a 65 000 t shuttle tanker as an example, full parametric modeling method is adopted, the hull optimization of three different bow forms is conducted through the polar vessel multi-objective optimization method.[Results] The ship hull after optimization can satisfy the IA class navigation require, where the resistance in calm water decreases up to 12.94%, and the minimum propulsion power in ice field has a 27.36% reduction.[Conclusions] The feasibility and validity of the NSGA Ⅱ applying in polar vessel design is verified.

Multi-Objective Optimization for Solid Amine CO2 Removal Assembly in Manned Spacecraft

Directory of Open Access Journals (Sweden)

Rong A

2017-07-01

Full Text Available Carbon Dioxide Removal Assembly (CDRA is one of the most important systems in the Environmental Control and Life Support System (ECLSS for a manned spacecraft. With the development of adsorbent and CDRA technology, solid amine is increasingly paid attention due to its obvious advantages. However, a manned spacecraft is launched far from the Earth, and its resources and energy are restricted seriously. These limitations increase the design difficulty of solid amine CDRA. The purpose of this paper is to seek optimal design parameters for the solid amine CDRA. Based on a preliminary structure of solid amine CDRA, its heat and mass transfer models are built to reflect some features of the special solid amine adsorbent, Polyethylenepolyamine adsorbent. A multi-objective optimization for the design of solid amine CDRA is discussed further in this paper. In this study, the cabin CO2 concentration, system power consumption and entropy production are chosen as the optimization objectives. The optimization variables consist of adsorption cycle time, solid amine loading mass, adsorption bed length, power consumption and system entropy production. The Improved Non-dominated Sorting Genetic Algorithm (NSGA-II is used to solve this multi-objective optimization and to obtain optimal solution set. A design example of solid amine CDRA in a manned space station is used to show the optimal procedure. The optimal combinations of design parameters can be located on the Pareto Optimal Front (POF. Finally, Design 971 is selected as the best combination of design parameters. The optimal results indicate that the multi-objective optimization plays a significant role in the design of solid amine CDRA. The final optimal design parameters for the solid amine CDRA can guarantee the cabin CO2 concentration within the specified range, and also satisfy the requirements of lightweight and minimum energy consumption.

Loading pattern optimization by multi-objective simulated annealing with screening technique

International Nuclear Information System (INIS)

Tong, K. P.; Hyun, C. L.; Hyung, K. J.; Chang, H. K.

2006-01-01

This paper presents a new multi-objective function which is made up of the main objective term as well as penalty terms related to the constraints. All the terms are represented in the same functional form and the coefficient of each term is normalized so that each term has equal weighting in the subsequent simulated annealing optimization calculations. The screening technique introduced in the previous work is also adopted in order to save computer time in 3-D neutronics evaluation of trial loading patterns. For numerical test of the new multi-objective function in the loading pattern optimization, the optimum loading patterns for the initial and the cycle 7 reload PWR core of Yonggwang Unit 4 are calculated by the simulated annealing algorithm with screening technique. A total of 10 optimum loading patterns are obtained for the initial core through 10 independent simulated annealing optimization runs. For the cycle 7 reload core one optimum loading pattern has been obtained from a single simulated annealing optimization run. More SA optimization runs will be conducted to optimum loading patterns for the cycle 7 reload core and results will be presented in the further work. (authors)

Multi objective optimization of horizontal axis tidal current turbines, using Meta heuristics algorithms

International Nuclear Information System (INIS)

Tahani, Mojtaba; Babayan, Narek; Astaraei, Fatemeh Razi; Moghadam, Ali

2015-01-01

Highlights: • The performance of four different Meta heuristic optimization algorithms was studied. • Power coefficient and produced torque on stationary blade were selected as objective functions. • Chord and twist distributions were selected as decision variables. • All optimization algorithms were combined with blade element momentum theory. • The best Pareto front was obtained by multi objective flower pollination algorithm for HATCTs. - Abstract: The performance of horizontal axis tidal current turbines (HATCT) strongly depends on their geometry. According to this fact, the optimum performance will be achieved by optimized geometry. In this research study, the multi objective optimization of the HATCT is carried out by using four different multi objective optimization algorithms and their performance is evaluated in combination with blade element momentum theory (BEM). The second version of non-dominated sorting genetic algorithm (NSGA-II), multi objective particle swarm optimization algorithm (MOPSO), multi objective cuckoo search algorithm (MOCS) and multi objective flower pollination algorithm (MOFPA) are the selected algorithms. The power coefficient and the produced torque on stationary blade are selected as objective functions and chord and twist distributions along the blade span are selected as decision variables. These algorithms are combined with the blade element momentum (BEM) theory for the purpose of achieving the best Pareto front. The obtained Pareto fronts are compared with each other. Different sets of experiments are carried out by considering different numbers of iterations, population size and tip speed ratios. The Pareto fronts which are achieved by MOFPA and NSGA-II have better quality in comparison to MOCS and MOPSO, but on the other hand a detail comparison between the first fronts of MOFPA and NSGA-II indicated that MOFPA algorithm can obtain the best Pareto front and can maximize the power coefficient up to 4.3% and the

14 CFR 93.218 - Slots for transborder service to and from Canada.

Science.gov (United States)

2010-01-01

... Canada. 93.218 Section 93.218 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF... service to and from Canada. (a) Except as otherwise provided in this subpart, international slots...'Hare in the Winter season. (c) Any modification to the slot base by the Government of Canada or the...

A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

NARCIS (Netherlands)

Hamdy, M.; Nguyen, A.T. (Anh Tuan); Hensen, J.L.M.

2016-01-01

Integrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently. Many multi-objective optimization algorithms have been developed; however few of them are tested in solving building design

Multi-Objective Climb Path Optimization for Aircraft/Engine Integration Using Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Aristeidis Antonakis

2017-04-01

Full Text Available In this article, a new multi-objective approach to the aircraft climb path optimization problem, based on the Particle Swarm Optimization algorithm, is introduced to be used for aircraft–engine integration studies. This considers a combination of a simulation with a traditional Energy approach, which incorporates, among others, the use of a proposed path-tracking scheme for guidance in the Altitude–Mach plane. The adoption of population-based solver serves to simplify case setup, allowing for direct interfaces between the optimizer and aircraft/engine performance codes. A two-level optimization scheme is employed and is shown to improve search performance compared to the basic PSO algorithm. The effectiveness of the proposed methodology is demonstrated in a hypothetic engine upgrade scenario for the F-4 aircraft considering the replacement of the aircraft’s J79 engine with the EJ200; a clear advantage of the EJ200-equipped configuration is unveiled, resulting, on average, in 15% faster climbs with 20% less fuel.

A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems

Science.gov (United States)

Moghaddam, Kamran S.; Usher, John S.

2011-07-01

In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.

Multi-Robot, Multi-Target Particle Swarm Optimization Search in Noisy Wireless Environments

Energy Technology Data Exchange (ETDEWEB)

Kurt Derr; Milos Manic

2009-05-01

Multiple small robots (swarms) can work together using Particle Swarm Optimization (PSO) to perform tasks that are difficult or impossible for a single robot to accomplish. The problem considered in this paper is exploration of an unknown environment with the goal of finding a target(s) at an unknown location(s) using multiple small mobile robots. This work demonstrates the use of a distributed PSO algorithm with a novel adaptive RSS weighting factor to guide robots for locating target(s) in high risk environments. The approach was developed and analyzed on multiple robot single and multiple target search. The approach was further enhanced by the multi-robot-multi-target search in noisy environments. The experimental results demonstrated how the availability of radio frequency signal can significantly affect robot search time to reach a target.

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

Science.gov (United States)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

Intersection signal control multi-objective optimization based on genetic algorithm

OpenAIRE

Zhanhong Zhou; Ming Cai

2014-01-01

A signal control intersection increases not only vehicle delay, but also vehicle emissions and fuel consumption in that area. Because more and more fuel and air pollution problems arise recently, an intersection signal control optimization method which aims at reducing vehicle emissions, fuel consumption and vehicle delay is required heavily. This paper proposed a signal control multi-object optimization method to reduce vehicle emissions, fuel consumption and vehicle delay simultaneously at ...

Seawave Slot-Cone Generator

DEFF Research Database (Denmark)

Vicinanza, Diego; Margheritini, Lucia; Contestabile, Pasquale

2009-01-01

This paper discusses a new type of Wave Energy Converter (WEC) named Seawave Slot-Cone Generator (SSG). The SSG is a WEC of the overtopping type. The structure consists of a number of reservoirs one on the top of each others above the mean water level in which the water of incoming waves is store...... on sloping walls constituting the structure. The research is intended to be of direct use to engineers analyzing design and stability of this peculiar kind of coastal structure....

Optimization of sound absorbing performance for gradient multi-layer-assembled sintered fibrous absorbers

Science.gov (United States)

Zhang, Bo; Zhang, Weiyong; Zhu, Jian

2012-04-01

The transfer matrix method, based on plane wave theory, of multi-layer equivalent fluid is employed to evaluate the sound absorbing properties of two-layer-assembled and three-layer-assembled sintered fibrous sheets (generally regarded as a kind of compound absorber or structures). Two objective functions which are more suitable for the optimization of sound absorption properties of multi-layer absorbers within the wider frequency ranges are developed and the optimized results of using two objective functions are also compared with each other. It is found that using the two objective functions, especially the second one, may be more helpful to exert the sound absorbing properties of absorbers at lower frequencies to the best of their abilities. Then the calculation and optimization of sound absorption properties of multi-layer-assembled structures are performed by developing a simulated annealing genetic arithmetic program and using above-mentioned objective functions. Finally, based on the optimization in this work the thoughts of the gradient design over the acoustic parameters- the porosity, the tortuosity, the viscous and thermal characteristic lengths and the thickness of each samples- of porous metals are put forth and thereby some useful design criteria upon the acoustic parameters of each layer of porous fibrous metals are given while applying the multi-layer-assembled compound absorbers in noise control engineering.

Optimal preventive maintenance and repair policies for multi-state systems

International Nuclear Information System (INIS)

Sheu, Shey-Huei; Chang, Chin-Chih; Chen, Yen-Luan; George Zhang, Zhe

2015-01-01

This paper studies the optimal preventive maintenance (PM) policies for multi-state systems. The scheduled PMs can be either imperfect or perfect type. The improved effective age is utilized to model the effect of an imperfect PM. The system is considered as in a failure state (unacceptable state) once its performance level falls below a given customer demand level. If the system fails before a scheduled PM, it is repaired and becomes operational again. We consider three types of major, minimal, and imperfect repair actions, respectively. The deterioration of the system is assumed to follow a non-homogeneous continuous time Markov process (NHCTMP) with finite state space. A recursive approach is proposed to efficiently compute the time-dependent distribution of the multi-state system. For each repair type, we find the optimal PM schedule that minimizes the average cost rate. The main implication of our results is that in determining the optimal scheduled PM, choosing the right repair type will significantly improve the efficiency of the system maintenance. Thus PM and repair decisions must be made jointly to achieve the best performance

Ka-Band Slot-Microstrip-Covered and Waveguide-Cavity-Backed Monopulse Antenna Array

Directory of Open Access Journals (Sweden)

Li-Ming Si

2014-01-01

Full Text Available A slot-microstrip-covered and waveguide-cavity-backed monopulse antenna array is proposed for high-resolution tracking applications at Ka-band. The monopulse antenna array is designed with a microstrip with 2×32 slots, a waveguide cavity, and a waveguide monopulse comparator, to make the structure simple, reduce the feeding network loss, and increase the frequency bandwidth. The 2×32 slot-microstrip elements are formed by a metal clad dielectric substrate and slots etched in the metal using the standard printed circuit board (PCB process with dimensions of 230 mm  ×  10 mm. The proposed monopulse antenna array not only maintains the advantages of the traditional waveguide slot antenna array, but also has the characteristics of wide bandwidth, high consistence, easy of fabrication, and low cost. From the measured results, it exhibits good monopulse characteristics, including the following: the maximum gains of sum pattern are greater than 24 dB, the 3 dB beamwidth of sum pattern is about 2.2 degrees, the sidelobe levels of the sum pattern are less than −18 dB, and the null depths of the difference pattern are less than −25 dB within the operating bandwidth between 33.65 GHz and 34.35 GHz for VSWR ≤ 2.

Optimal erasure protection for scalably compressed video streams with limited retransmission.

Science.gov (United States)

Taubman, David; Thie, Johnson

2005-08-01

This paper shows how the priority encoding transmission (PET) framework may be leveraged to exploit both unequal error protection and limited retransmission for RD-optimized delivery of streaming media. Previous work on scalable media protection with PET has largely ignored the possibility of retransmission. Conversely, the PET framework has not been harnessed by the substantial body of previous work on RD optimized hybrid forward error correction/automatic repeat request schemes. We limit our attention to sources which can be modeled as independently compressed frames (e.g., video frames), where each element in the scalable representation of each frame can be transmitted in one or both of two transmission slots. An optimization algorithm determines the level of protection which should be assigned to each element in each slot, subject to transmission bandwidth constraints. To balance the protection assigned to elements which are being transmitted for the first time with those which are being retransmitted, the proposed algorithm formulates a collection of hypotheses concerning its own behavior in future transmission slots. We show how the PET framework allows for a decoupled optimization algorithm with only modest complexity. Experimental results obtained with Motion JPEG2000 compressed video demonstrate that substantial performance benefits can be obtained using the proposed framework.

A Generalized Decision Framework Using Multi-objective Optimization for Water Resources Planning

Science.gov (United States)

Basdekas, L.; Stewart, N.; Triana, E.

2013-12-01

Colorado Springs Utilities (CSU) is currently engaged in an Integrated Water Resource Plan (IWRP) to address the complex planning scenarios, across multiple time scales, currently faced by CSU. The modeling framework developed for the IWRP uses a flexible data-centered Decision Support System (DSS) with a MODSIM-based modeling system to represent the operation of the current CSU raw water system coupled with a state-of-the-art multi-objective optimization algorithm. Three basic components are required for the framework, which can be implemented for planning horizons ranging from seasonal to interdecadal. First, a water resources system model is required that is capable of reasonable system simulation to resolve performance metrics at the appropriate temporal and spatial scales of interest. The system model should be an existing simulation model, or one developed during the planning process with stakeholders, so that 'buy-in' has already been achieved. Second, a hydrologic scenario tool(s) capable of generating a range of plausible inflows for the planning period of interest is required. This may include paleo informed or climate change informed sequences. Third, a multi-objective optimization model that can be wrapped around the system simulation model is required. The new generation of multi-objective optimization models do not require parameterization which greatly reduces problem complexity. Bridging the gap between research and practice will be evident as we use a case study from CSU's planning process to demonstrate this framework with specific competing water management objectives. Careful formulation of objective functions, choice of decision variables, and system constraints will be discussed. Rather than treating results as theoretically Pareto optimal in a planning process, we use the powerful multi-objective optimization models as tools to more efficiently and effectively move out of the inferior decision space. The use of this framework will help CSU

Distributed Optimization of Multi Beam Directional Communication Networks

Science.gov (United States)

2017-06-30

Distributed Optimization of Multi-Beam Directional Communication Networks Theodoros Tsiligkaridis MIT Lincoln Laboratory Lexington, MA 02141, USA...based routing. I. INTRODUCTION Missions where multiple communication goals are of in- terest are becoming more prevalent in military applications...Multilayer communications may occur within a coalition; for example, a team consisting of ground vehicles and an airborne set of assets may desire to

Multi-Objective Optimization of the Hedging Model for reservoir Operation Using Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

sadegh sadeghitabas

2015-12-01

Full Text Available Multi-objective problems rarely ever provide a single optimal solution, rather they yield an optimal set of outputs (Pareto fronts. Solving these problems was previously accomplished by using some simplifier methods such as the weighting coefficient method used for converting a multi-objective problem to a single objective function. However, such robust tools as multi-objective meta-heuristic algorithms have been recently developed for solving these problems. The hedging model is one of the classic problems for reservoir operation that is generally employed for mitigating drought impacts in water resources management. According to this method, although it is possible to supply the total planned demands, only portions of the demands are met to save water by allowing small deficits in the current conditions in order to avoid or reduce severe deficits in future. The approach heavily depends on economic and social considerations. In the present study, the meta-heuristic algorithms of NSGA-II, MOPSO, SPEA-II, and AMALGAM are used toward the multi-objective optimization of the hedging model. For this purpose, the rationing factors involved in Taleghan dam operation are optimized over a 35-year statistical period of inflow. There are two objective functions: a minimizing the modified shortage index, and b maximizing the reliability index (i.e., two opposite objectives. The results show that the above algorithms are applicable to a wide range of optimal solutions. Among the algorithms, AMALGAM is found to produce a better Pareto front for the values of the objective function, indicating its more satisfactory performance.

Multi-objective optimization of coal-fired power plants using differential evolution

International Nuclear Information System (INIS)

Wang, Ligang; Yang, Yongping; Dong, Changqing; Morosuk, Tatiana; Tsatsaronis, George

2014-01-01

Highlights: • Multi-objective optimization of large-scale coal-fired power plants using differential evolution. • A newly-proposed algorithm for searching the fronts of decision space in a single run. • A reduction of cost of electricity by 2–4% with an optimal efficiency increase up to 2% points. • The uncertainty comes mainly from temperature- and reheat-related cost factors of steam generator. • An exergoeconomic analysis and comparison between optimal designs and one real industrial design. - Abstract: The design trade-offs between thermodynamics and economics for thermal systems can be studied with the aid of multi-objective optimization techniques. The investment costs usually increase with increasing thermodynamic performance of a system. In this paper, an enhanced differential evolution with diversity-preserving and density-adjusting mechanisms, and a newly-proposed algorithm for searching the decision space frontier in a single run were used, to conduct the multi-objective optimization of large-scale, supercritical coal-fired plants. The uncertainties associated with cost functions were discussed by analyzing the sensitivity of the decision space frontier to some significant parameters involved in cost functions. Comparisons made with the aid of an exergoeconomic analysis between the cost minimum designs and a real industrial design demonstrated how the plant improvement was achieved. It is concluded that the cost of electricity could be reduced by a 2–4%, whereas the efficiency could be increased by up to two percentage points. The largest uncertainty is introduced by the temperature-related and reheat-related cost coefficients of the steam generator. More reliable data on the price prediction of future advanced materials should be used to obtain more accurate fronts of the objective space

Enhancement of acousto-optical coupling in two-dimensional air-slot phoxonic crystal cavities by utilizing surface acoustic waves

Energy Technology Data Exchange (ETDEWEB)

Ma, Tian-Xue [Institute of Engineering Mechanics, Beijing Jiaotong University, Beijing 100044 (China); Wang, Yue-Sheng, E-mail: yswang@bjtu.edu.cn [Institute of Engineering Mechanics, Beijing Jiaotong University, Beijing 100044 (China); Zhang, Chuanzeng [Department of Civil Engineering, University of Siegen, D-57068 Siegen (Germany)

2017-01-30

A phoxonic crystal is a periodically patterned material that can simultaneously localize optical and acoustic modes. The acousto-optical coupling in two-dimensional air-slot phoxonic crystal cavities is investigated numerically. The photons can be well confined in the slot owing to the large electric field discontinuity at the air/dielectric interfaces. Besides, the surface acoustic modes lead to the localization of the phonons near the air-slot. The high overlap of the photonic and phononic cavity modes near the slot results in a significant enhancement of the moving interface effect, and thus strengthens the total acousto-optical interaction. The results of two cavities with different slot widths show that the coupling strength is dependent on the slot width. It is expected to achieve a strong acousto-optical/optomechanical coupling in air-slot phoxonic crystal structures by utilizing surface acoustic modes. - Highlights: • Two-dimensional air-slot phoxonic crystal cavities which can confine simultaneously optical and acoustic waves are proposed. • The acoustic and optical waves are highly confined near/in the air-slot. • The high overlap of the photonic and phononic cavity modes significantly enhances the moving interface effect. • Different factors which affect the acousto-optical coupling are discussed.

Detailed Study of Closed Stator Slots for a Direct-Driven Synchronous Permanent Magnet Linear Wave Energy Converter

Directory of Open Access Journals (Sweden)

Erik Lejerskog

2014-01-01

Full Text Available The aim of this paper is to analyze how a permanent magnet linear generator for wave power behaves when the stator slots are closed. The usual design of stator geometry is to use open slots to maintain a low magnetic leakage flux between the stator teeth. By doing this, harmonics are induced in the magnetic flux density in the air-gap due to slotting. The closed slots are designed to cause saturation, to keep the permeability low. This reduces the slot harmonics in the magnetic flux density, but will also increase the flux leakage between the stator teeth. An analytical model has been created to study the flux through the closed slots and the result compared with finite element simulations. The outcome shows a reduction of the cogging force and a reduction of the harmonics of the magnetic flux density in the air-gap. It also shows a small increase of the total magnetic flux entering the stator and an increased magnetic flux leakage through the closed slots.

Image Segmentation Method Using Fuzzy C Mean Clustering Based on Multi-Objective Optimization

Science.gov (United States)

Chen, Jinlin; Yang, Chunzhi; Xu, Guangkui; Ning, Li

2018-04-01

Image segmentation is not only one of the hottest topics in digital image processing, but also an important part of computer vision applications. As one kind of image segmentation algorithms, fuzzy C-means clustering is an effective and concise segmentation algorithm. However, the drawback of FCM is that it is sensitive to image noise. To solve the problem, this paper designs a novel fuzzy C-mean clustering algorithm based on multi-objective optimization. We add a parameter λ to the fuzzy distance measurement formula to improve the multi-objective optimization. The parameter λ can adjust the weights of the pixel local information. In the algorithm, the local correlation of neighboring pixels is added to the improved multi-objective mathematical model to optimize the clustering cent. Two different experimental results show that the novel fuzzy C-means approach has an efficient performance and computational time while segmenting images by different type of noises.

Effect of Slotted Anode on Gas Bubble Behaviors in Aluminum Reduction Cell

Science.gov (United States)

Sun, Meijia; Li, Baokuan; Li, Linmin; Wang, Qiang; Peng, Jianping; Wang, Yaowu; Cheung, Sherman C. P.

2017-12-01

In the aluminum reduction cells, gas bubbles are generated at the bottom of the anode which eventually reduces the effective current contact area and the system efficiency. To encourage the removal of gas bubbles, slotted anode has been proposed and increasingly adopted by some industrial aluminum reduction cells. Nonetheless, the exact gas bubble removal mechanisms are yet to be fully understood. A three-dimensional (3D) transient, multiphase flow mathematical model coupled with magnetohydrodynamics has been developed to investigate the effect of slotted anode on the gas bubble movement. The Eulerian volume of fluid approach is applied to track the electrolyte (bath)-molten aluminum (metal) interface. Meanwhile, the Lagrangian discrete particle model is employed to handle the dynamics of gas bubbles with considerations of the buoyancy force, drag force, virtual mass force, and pressure gradient force. The gas bubble coalescence process is also taken into account based on the O'Rourke's algorithm. The two-way coupling between discrete bubbles and fluids is achieved by the inter-phase momentum exchange. Numerical predictions are validated against the anode current variation in an industrial test. Comparing the results using slotted anode with the traditional one, the time-averaged gas bubble removal rate increases from 36 to 63 pct; confirming that the slotted anode provides more escaping ways and shortens the trajectories for gas bubbles. Furthermore, the slotted anode also reduces gas bubble's residence time and the probability of coalescence. Moreover, the bubble layer thickness in aluminum cell with slotted anode is reduced about 3.5 mm (17.4 pct), so the resistance can be cut down for the sake of energy saving and the metal surface fluctuation amplitude is significantly reduced for the stable operation due to the slighter perturbation with smaller bubbles.

Optimal Sequential Resource Sharing and Exchange in Multi-Agent Systems

OpenAIRE

Xiao, Yuanzhang

2014-01-01

Central to the design of many engineering systems and social networks is to solve the underlying resource sharing and exchange problems, in which multiple decentralized agents make sequential decisions over time to optimize some long-term performance metrics. It is challenging for the decentralized agents to make optimal sequential decisions because of the complicated coupling among the agents and across time. In this dissertation, we mainly focus on three important classes of multi-agent seq...

A study of the LCA based biofuel supply chain multi-objective optimization model with multi-conversion paths in China

International Nuclear Information System (INIS)

Liu, Zhexuan; Qiu, Tong; Chen, Bingzhen

2014-01-01

Highlights: • A LCA based biofuel supply chain model considering 3E criteria was proposed. • The model was used to design a supply chain considering three conversion pathways. • An experimental biofuel supply chain for China was designed. • A Pareto-optimal solution surface of this multi-objective problem was obtained. • The designed supply chain was rather robust to price variation. - Abstract: In this paper we present a life cycle assessment (LCA) based biofuel supply chain model with multi-conversion pathways. This model was formulated as a mixed integer linear programming (MILP) problem which took economic, energy, and environmental criteria (3E) into consideration. The economic objective was measured by the total annual profit. The energy objective was measured by using the average fossil energy input per megajoule (MJ) of biofuel. The environmental objective was measured by greenhouse gas (GHG) emissions per MJ of biofuel. After carefully consideration of the current situation in China, we chose to examine three conversion pathways: bio-ethanol (BE), bio-methanol (BM) and bio-diesel (BD). LCA was integrated to a multi-objective supply chain model by dividing each pathway into several individual parts and analyzing each part. The multi-objective MILP problem was solved using a ε-constraint method by defining the total annual profit as the optimization objective and assigning the average fossil energy input per MJ biofuel and GHG emissions per MJ biofuel as constraints. This model was then used to design an experimental biofuel supply chain for China. A surface of the Pareto optimal solutions was obtained by linear interpolation of the non-inferior solutions. The optimal results included the choice of optimal conversion pathway, biomass type, biomass locations, facility locations, and network topology structure in the biofuel supply chain. Distributed and centralized systems were also factored into our experimental system design. In addition, the

Layered Multi-mode Optimal Control Strategy for Multi-MW Wind Turbine

Institute of Scientific and Technical Information of China (English)

KONG Yi-gang; WANG Zhi-xin

2008-01-01

The control strategy is one of the most important renewable technology, and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch (VS-VP) technology. The main objective of adopting a VS-VP technology is to improve the fast response speed and capture maximum energy. But the power generated by wind turbine changes rapidly because of the centinuous fluctuation of wind speed and direction. At the same time, wind energy conversion systems are of high order, time delays and strong nonlinear characteristics because of many uncertain factors. Based on analyzing the all dynamic processes of wind turbine, a kind of layered multi-mode optimal control strategy is presented which is that three control strategies: bang-bang, fuzzy and adaptive proportienai integral derivative (PID) are adopted according to different stages and expected performance of wind turbine to capture optimum wind power, compensate the nonlinearity and improve the wind turbine performance at low, rated and high wind speed.

Benefits and unexpected artifacts of biplanar digital slot-scanning imaging in children

Energy Technology Data Exchange (ETDEWEB)

Blumer, Steven L. [Nemours/A.I duPont Hospital for Children, Department of Medical Imaging, Wilmington, DE (United States); Dinan, David [Nemours Children' s Hospital, Orlando, FL (United States); Grissom, Leslie E. [Nemours/Alfred I. duPont Hospital for Children, Department of Radiology, Wilmington, DE (United States)

2014-07-15

Biplanar digital slot-scanning allows for relatively low-dose orthopedic imaging, an advantage in imaging children given the growing concerns regarding radiosensitivity. We have used this system for approximately 1 year for orthopedic imaging of the spine and lower extremities. We have noted advantages of using the digital slot-scanning system when compared with computed radiographic and standard digital radiographic imaging systems, but we also found unexpected but common imaging artifacts that are the direct result of the imaging method and that have not been reported. This pictorial essay serves to familiarize radiologists with the advantages of the digital slot-scanning system as well as imaging artifacts common with this new technology. (orig.)

An Efficacious Multi-Objective Fuzzy Linear Programming Approach for Optimal Power Flow Considering Distributed Generation.

Science.gov (United States)

Warid, Warid; Hizam, Hashim; Mariun, Norman; Abdul-Wahab, Noor Izzri

2016-01-01

This paper proposes a new formulation for the multi-objective optimal power flow (MOOPF) problem for meshed power networks considering distributed generation. An efficacious multi-objective fuzzy linear programming optimization (MFLP) algorithm is proposed to solve the aforementioned problem with and without considering the distributed generation (DG) effect. A variant combination of objectives is considered for simultaneous optimization, including power loss, voltage stability, and shunt capacitors MVAR reserve. Fuzzy membership functions for these objectives are designed with extreme targets, whereas the inequality constraints are treated as hard constraints. The multi-objective fuzzy optimal power flow (OPF) formulation was converted into a crisp OPF in a successive linear programming (SLP) framework and solved using an efficient interior point method (IPM). To test the efficacy of the proposed approach, simulations are performed on the IEEE 30-busand IEEE 118-bus test systems. The MFLP optimization is solved for several optimization cases. The obtained results are compared with those presented in the literature. A unique solution with a high satisfaction for the assigned targets is gained. Results demonstrate the effectiveness of the proposed MFLP technique in terms of solution optimality and rapid convergence. Moreover, the results indicate that using the optimal DG location with the MFLP algorithm provides the solution with the highest quality.

Optimization of inverse model identification for multi-axial test rig control

Directory of Open Access Journals (Sweden)

Müller Tino

2016-01-01

Full Text Available Laboratory testing of multi-axial fatigue situations improves repeatability and allows a time condensing of tests which can be carried out until component failure, compared to field testing. To achieve realistic and convincing durability results, precise load data reconstruction is necessary. Cross-talk and a high number of degrees of freedom negatively affect the control accuracy. Therefore a multiple input/multiple output (MIMO model of the system, capturing all inherent cross-couplings is identified. In a first step the model order is estimated based on the physical fundamentals of a one channel hydraulic-servo system. Subsequently, the structure of the MIMO model is optimized using correlation of the outputs, to increase control stability and reduce complexity of the parameter optimization. The identification process is successfully applied to the iterative control of a multi-axial suspension rig. The results show accurate control, with increased stability compared to control without structure optimization.

High-Q silicon-on-insulator slot photonic crystal cavity infiltrated by a liquid

International Nuclear Information System (INIS)

Caër, Charles; Le Roux, Xavier; Cassan, Eric

2013-01-01

We report the experimental realization of a high-Q slot photonic crystal cavity in Silicon-On-Insulator (SOI) configuration infiltrated by a liquid. Loaded Q-factor of 23 000 is measured at telecom wavelength. The intrinsic quality factor inferred from the transmission spectrum is higher than 200 000, which represents a record value for slot photonic crystal cavities on SOI, whereas the maximum of intensity of the cavity is roughly equal to 20% of the light transmitted in the waveguide. This result makes filled slot photonic crystal cavities very promising for silicon-based light emission and ultrafast nonlinear optics

Chance-constrained multi-objective optimization of groundwater remediation design at DNAPLs-contaminated sites using a multi-algorithm genetically adaptive method.

Science.gov (United States)

Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan

2017-05-01

In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

International Nuclear Information System (INIS)

Pang, X.; Rybarcyk, L.J.

2014-01-01

Particle swarm optimization (PSO) and genetic algorithm (GA) are both nature-inspired population based optimization methods. Compared to GA, whose long history can trace back to 1975, PSO is a relatively new heuristic search method first proposed in 1995. Due to its fast convergence rate in single objective optimization domain, the PSO method has been extended to optimize multi-objective problems. In this paper, we will introduce the PSO method and its multi-objective extension, the MOPSO, apply it along with the MOGA (mainly the NSGA-II) to simulations of the LANSCE linac and operational set point optimizations. Our tests show that both methods can provide very similar Pareto fronts but the MOPSO converges faster

Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation

Energy Technology Data Exchange (ETDEWEB)

Pang, X., E-mail: xpang@lanl.gov; Rybarcyk, L.J.

2014-03-21

Particle swarm optimization (PSO) and genetic algorithm (GA) are both nature-inspired population based optimization methods. Compared to GA, whose long history can trace back to 1975, PSO is a relatively new heuristic search method first proposed in 1995. Due to its fast convergence rate in single objective optimization domain, the PSO method has been extended to optimize multi-objective problems. In this paper, we will introduce the PSO method and its multi-objective extension, the MOPSO, apply it along with the MOGA (mainly the NSGA-II) to simulations of the LANSCE linac and operational set point optimizations. Our tests show that both methods can provide very similar Pareto fronts but the MOPSO converges faster.

A linear bi-level multi-objective program for optimal allocation of water resources.

Directory of Open Access Journals (Sweden)

Ijaz Ahmad

Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Impedance of a slotted-pipe kicker

Energy Technology Data Exchange (ETDEWEB)

Zhou, Feng [Academia Sinica, Beijing, BJ (China). Inst. of High Energy Physics

1996-08-01

This paper introduces the principle of a new slotted kicker simply, which is made by using vacuum pipe itself with proper slits as current conductors, and then, presents a rough estimation of its longitudinal and transverse impedance, respectively. Calculation shows that its impedance is reduced significantly compared to our present air-coil kicker. (author)

A fast semi-analytical model for the slotted structure of induction motors with 36/28 stator/rotor slot combination

NARCIS (Netherlands)

Sprangers, R.L.J.; Paulides, J.J.H.; Gysen, B.L.J.; Lomonova, E.A.

2014-01-01

A fast, semi-analyticalmodel for inductionmotors (IMs) with 36/28 stator/rotor slot combination is presented. In comparison to traditional analytical models for IMs, such as lumped parameter, magnetic equivalent circuit and anisotropic layer models, the presented model calculates a continuous

Vertical Slot Convection: A linear study

International Nuclear Information System (INIS)

McAllister, A.; Steinolfson, R.; Tajima, T.

1992-11-01

The linear stability properties of fluid convection in a vertical slot were studied. We use a Fourier-Chebychev decomposition was used to set up the linear eigenvalue problems for the Vertical Slot Convection and Benard problems. The eigenvalues, neutral stability curves, and critical point values of the Grashof number, G, and the wavenumber were determined. Plots of the real and imaginary parts of the eigenvalues as functions of G and α are given for a wide range of the Prandtl number, Pr, and special note is made of the complex mode that becomes linearly unstable above Pr ∼ 12.5. A discussion comparing different special cases facilitates the physical understanding of the VSC equations, especially the interaction of the shear-flow and buoyancy induced physics. Making use of the real and imaginary eigenvalues and the phase properties of the eigenmodes, the eigenmodes were characterized. One finds that the mode structure becomes progressively simpler with increasing Pr, with the greatest complexity in the mid ranges where the terms in the heat equation are of roughly the same size

Optimal Golomb Ruler Sequences Generation for Optical WDM Systems: A Novel Parallel Hybrid Multi-objective Bat Algorithm

Science.gov (United States)

Bansal, Shonak; Singh, Arun Kumar; Gupta, Neena

2017-02-01

In real-life, multi-objective engineering design problems are very tough and time consuming optimization problems due to their high degree of nonlinearities, complexities and inhomogeneity. Nature-inspired based multi-objective optimization algorithms are now becoming popular for solving multi-objective engineering design problems. This paper proposes original multi-objective Bat algorithm (MOBA) and its extended form, namely, novel parallel hybrid multi-objective Bat algorithm (PHMOBA) to generate shortest length Golomb ruler called optimal Golomb ruler (OGR) sequences at a reasonable computation time. The OGRs found their application in optical wavelength division multiplexing (WDM) systems as channel-allocation algorithm to reduce the four-wave mixing (FWM) crosstalk. The performances of both the proposed algorithms to generate OGRs as optical WDM channel-allocation is compared with other existing classical computing and nature-inspired algorithms, including extended quadratic congruence (EQC), search algorithm (SA), genetic algorithms (GAs), biogeography based optimization (BBO) and big bang-big crunch (BB-BC) optimization algorithms. Simulations conclude that the proposed parallel hybrid multi-objective Bat algorithm works efficiently as compared to original multi-objective Bat algorithm and other existing algorithms to generate OGRs for optical WDM systems. The algorithm PHMOBA to generate OGRs, has higher convergence and success rate than original MOBA. The efficiency improvement of proposed PHMOBA to generate OGRs up to 20-marks, in terms of ruler length and total optical channel bandwidth (TBW) is 100 %, whereas for original MOBA is 85 %. Finally the implications for further research are also discussed.

Implementing of the multi-objective particle swarm optimizer and fuzzy decision-maker in exergetic, exergoeconomic and environmental optimization of a benchmark cogeneration system

International Nuclear Information System (INIS)

Sayyaadi, Hoseyn; Babaie, Meisam; Farmani, Mohammad Reza

2011-01-01

Multi-objective optimization for design of a benchmark cogeneration system namely as the CGAM cogeneration system is performed. In optimization approach, Exergetic, Exergoeconomic and Environmental objectives are considered, simultaneously. In this regard, the set of Pareto optimal solutions known as the Pareto frontier is obtained using the MOPSO (multi-objective particle swarm optimizer). The exergetic efficiency as an exergetic objective is maximized while the unit cost of the system product and the cost of the environmental impact respectively as exergoeconomic and environmental objectives are minimized. Economic model which is utilized in the exergoeconomic analysis is built based on both simple model (used in original researches of the CGAM system) and the comprehensive modeling namely as TTR (total revenue requirement) method (used in sophisticated exergoeconomic analysis). Finally, a final optimal solution from optimal set of the Pareto frontier is selected using a fuzzy decision-making process based on the Bellman-Zadeh approach and results are compared with corresponding results obtained in a traditional decision-making process. Further, results are compared with the corresponding performance of the base case CGAM system and optimal designs of previous works and discussed. -- Highlights: → A multi-objective optimization approach has been implemented in optimization of a benchmark cogeneration system. → Objective functions based on the environmental impact evaluation, thermodynamic and economic analysis are obtained and optimized. → Particle swarm optimizer implemented and its robustness is compared with NSGA-II. → A final optimal configuration is found using various decision-making approaches. → Results compared with previous works in the field.

Multi-objective robust optimization method for the modified epoxy resin sheet molding compounds of the impeller

Directory of Open Access Journals (Sweden)

Xiaozhang Qu

2016-07-01

Full Text Available A kind of modified epoxy resin sheet molding compounds of the impeller has been designed. Through the test, the non-metal impeller has a better environmental aging performance, but must do the waterproof processing design. In order to improve the stability of the impeller vibration design, the influence of uncertainty factors is considered, and a multi-objective robust optimization method is proposed to reduce the weight of the impeller. Firstly, based on the fluid-structure interaction，the analysis model of the impeller vibration is constructed. Secondly, the optimal approximate model of the impeller is constructed by using the Latin hypercube and radial basis function, and the fitting and optimization accuracy of the approximate model is improved by increasing the sample points. Finally, the micro multi-objective genetic algorithm is applied to the robust optimization of approximate model, and the Monte Carlo simulation and Sobol sampling techniques are used for reliability analysis. By comparing the results of the deterministic, different sigma levels and different materials, the multi-objective optimization of the SMC molding impeller can meet the requirements of engineering stability and lightweight. And the effectiveness of the proposed multi-objective robust optimization method is verified by the error analysis. After the SMC molding and the robust optimization of the impeller, the optimized rate reached 42.5%, which greatly improved the economic benefit, and greatly reduce the vibration of the ventilation system.

Examination report: Remote video examination of air slots under the primary tank at 241-AN-107

International Nuclear Information System (INIS)

Pedersen, L.T.

1998-01-01

This report documents the results of remote video examination of air slots in the insulating concrete slab beneath the primary tank at 241-AN-107. Life Extension Equipment Engineering has selected tank 241-AN-107 for ultrasonic evaluation of tank wall, knuckle, and floor plates. Access to the primary tank floor plates is via the air slots which were formed into the insulating concrete slab during tank construction (reference drawings H-2-71105 and H-2-71160). Prior to deployment of the ultrasonic inspection equipment it is desirable to examine the air slots for obstructions and debris which could impede the ultrasonic equipment. The criteria, equipment description, deliverables, and responsibilities for examination of the air slots are described in HNF-1949, Rev. 0, ''Engineering Task Plan for Remote Video Examination of Air Slots Under the Primary Tank at 241-AN-107''

Thermo-economic and environmental analyses based multi-objective optimization of vapor compression–absorption cascaded refrigeration system using NSGA-II technique

International Nuclear Information System (INIS)

Jain, Vaibhav; Sachdeva, Gulshan; Kachhwaha, Surendra Singh; Patel, Bhavesh

2016-01-01

Highlights: • It addresses multi-objective optimization study on cascaded refrigeration system. • Cascaded system is a promising decarburizing and energy efficient technology. • NSGA-II technique is used for multi-objective optimization. • Total annual product cost and irreversibility rate are simultaneously optimized. - Abstract: Present work optimizes the performance of 170 kW vapor compression–absorption cascaded refrigeration system (VCACRS) based on combined thermodynamic, economic and environmental parameters using Non-dominated Sort Genetic Algorithm-II (NSGA-II) technique. Two objective functions including the total irreversibility rate (as a thermodynamic criterion) and the total product cost (as an economic criterion) of the system are considered simultaneously for multi-objective optimization of VCACRS. The capital and maintenance costs of the system components, the operational cost, and the penalty cost due to CO_2 emission are included in the total product cost of the system. Three optimized systems including a single-objective thermodynamic optimized, a single-objective economic optimized and a multi-objective optimized are analyzed and compared. The results showed that the multi-objective design considers the combined thermodynamic and total product cost criteria better than the two individual single-objective thermodynamic and total product cost optimized designs.

Design optimization of multi-layer Silicon Carbide cladding for light water reactors

Energy Technology Data Exchange (ETDEWEB)

Lee, Youho, E-mail: euo@unm.edu [Department of Nuclear Engineering, University of New Mexico, MSC01 1120 1 University of New Mexico, Albuquerque, NM 87131 (United States); NO, Hee Cheon, E-mail: hcno@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of); Lee, Jeong Ik, E-mail: jeongiklee@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701 (Korea, Republic of)

2017-01-15

Highlights: • SiC cladding designs are optimized with a multi-layer structural analysis code. • Layer radial thickness fraction that minimizes cladding fracture probability exists. • The demonstrated procedure is applicable for multi-layer SiC cladding design. • Duplex SiC with the inner composite fraction ∼0.4 is optimal in a reference case. • Increasing composite thermal conductivity markedly decreases SiC cladding stress. - Abstract: A parametric study that demonstrates a methodology for determining the optimum bilayer composition in a duplex SiC cladding is discussed. The structural performance of multi-layer SiC cladding design is significantly affected by radial thickness fraction of each layer. This study shows that there exists an optimal composite/monolith radial thickness fraction that minimizes failure probability for a duplex SiC cladding in steady-state operation. An exemplary reference case study shows that the duplex cladding with the inner composite fraction ∼0.4 and the outer CVD-SiC fraction ∼0.6 is found to be the optimal SiC cladding design for the current PWRs with the reference material choice for CVD-SiC and fiber reinforced composite. A marginal increase in the composite fraction from the presented optimal designs may lead to increase structural integrity by introducing some unquantified merits such as increasing damage tolerance. The major factors that affect the optimum cladding designs are temperature gradients and internal gas pressure. Clad wall thickness, thermal conductivity, and Weibull modulus are among the key design parameters/material properties.

Incorporation of the stress concentration slots into the flexures for a high-performance microaccelerometer

International Nuclear Information System (INIS)

Zhao Yulong; Sun Lu; Liu Yan; Wang Weizhong; Tian Bian

2012-01-01

Presented in this paper is a development of a high-performance piezoresistive microaccelerometer based on the slot etching in the quad flexures for the vibration detection of high speed spindle. The proposed structure consists of a proof mass supported by four thin flexures with slots etched in the middle. Boron diffused piezoresistors located near the stress concentration regions are used for sensing the localized stress resulting from the incorporation of the slots into the flexures. Theoretical analysis and finite element analysis show satisfactory results of an improved sensitivity and favorable natural frequency higher than 10 kHz, conforming to the initial design requirements. The microfabrication techniques are described to prototype the two accelerometer chips, one with slots and the other one without slots. The tested microaccelerometers with 3 V DC power supply show an average sensitivity of 0.424 mV/g normal to the proof mass plane, increased by 60.6% than the ones without slots. An average transverse sensitivity is found to be 9.2 μV/g along X axis and 14.2 μV/g along Y axis, either of which is less than 3.5% of prime-axis sensitivity. Concerning the resonant frequency, dynamic experiment shows about 12.46 kHz and is available for the proposed design with a tiny loss of 3.5% compared with the quad-beam design. When taking the product of sensitivity and natural frequency as judgment criteria, an inspiring increase by 28.6% of the figure of merit is accomplished for the proposed accelerometer. Overall, the findings of this study confirm the feasibility of incorporating slots into the conventional configurations to improve the sensor sensitivity while maintaining a comparatively high natural frequency.

A numerical investigation on the effects of slot geometry on shock boundary layer interaction

Energy Technology Data Exchange (ETDEWEB)

Bazazzadeh, M.; Menshadi, M. D.; Karbasizadeh, M. [Dept. of Mechanical and Aerospace Engineering, Malek Ashtar University of Technology, Esfahan (Turkmenistan)

2017-01-15

Slot is one of the features that control Shock wave-boundary layer interaction (SBLI), which is generally used to prevent strong interference from shockwaves to the boundary layer in supersonic flows. With this feature, the height of the triple point of λ shock significantly increases, and this increase causes a decline in shock power and pressure drop rate. In the current paper, the main focus is on the monitoring of the geometrical effect of slot as an influential parameter on the structure of the shock and flow characteristics by using numerical methods. Therefore, the averaged implicit Navier-Stokes equations and two equation standard k-ω turbulence models for the numerical simulation of the flow field have been used. Results indicate that the numerical results are fairly consistent with the experimental data. Because of the increase in the number of slots (n), and the leading leg of the λ shock is located within the slot, the height of the triple point increases. However, because of the increasing drops due to viscosity, the total pressure changes are negligible. In addition, with an increase in this parameter, changes in the static pressure caused by the leading leg of the shock have increased. By increasing the width of the slots, the height of the triple point has had an upward trend up to s = 8 mm and then had nearly constant values. In this mode, the static pressure changes resulting from the leading leg of the shock are negligible. For increasing the number or the width of slots, the re-expansion waves formed within the slot are removed because of the reduction in the severity of the changes in the boundary layer. To simulate and compare the results with the data obtained from the experimental tests, results from the Cambridge University's wind tunnel tests have been used.

Ensemble-based hierarchical multi-objective production optimization of smart wells

NARCIS (Netherlands)

Fonseca, R.M.; Leeuwenburgh, O.; Van den Hof, P.M.J.; Jansen, J.D.

2014-01-01

In an earlier study two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However this earlier study has two limitations: 1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access

Rotor Pole Shape Optimization of Permanent Magnet Brushless DC Motors Using the Reduced Basis Technique

Directory of Open Access Journals (Sweden)

GHOLAMIAN, A. S.

2009-06-01

Full Text Available In this paper, a magnet shape optimization method for reduction of cogging torque and torque ripple in Permanent Magnet (PM brushless DC motors is presented by using the reduced basis technique coupled by finite element and design of experiments methods. The primary objective of the method is to reduce the enormous number of design variables required to define the magnet shape. The reduced basis technique is a weighted combination of several basis shapes. The aim of the method is to find the best combination using the weights for each shape as the design variables. A multi-level design process is developed to find suitable basis shapes or trial shapes at each level that can be used in the reduced basis technique. Each level is treated as a separated optimization problem until the required objective is achieved. The experimental design of Taguchi method is used to build the approximation model and to perform optimization. This method is demonstrated on the magnet shape optimization of a 6-poles/18-slots PM BLDC motor.

Slotted coax as a beam electrode

International Nuclear Information System (INIS)

Lambertson, G.R.; Kim, K.J.; Voelker, F.V.

1983-03-01

The slot coupled TEM line has been employed at CERN as a pick up electrode in the GHz range. It is a compact and broad band device, and will be quite attractive if the coupling efficiency is competitive with an array of quarter wave loops. In this paper, we study various properties of such a structure

Multi-Objective Sustainable Operation of the Three Gorges Cascaded Hydropower System Using Multi-Swarm Comprehensive Learning Particle Swarm Optimization

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Xiang Yu

2016-06-01

Full Text Available Optimal operation of hydropower reservoir systems often needs to optimize multiple conflicting objectives simultaneously. The conflicting objectives result in a Pareto front, which is a set of non-dominated solutions. Non-dominated solutions cannot outperform each other on all the objectives. An optimization framework based on the multi-swarm comprehensive learning particle swarm optimization algorithm is proposed to solve the multi-objective operation of hydropower reservoir systems. Through adopting search techniques such as decomposition, mutation and differential evolution, the algorithm tries to derive multiple non-dominated solutions reasonably distributed over the true Pareto front in one single run, thereby facilitating determining the final tradeoff. The long-term sustainable planning of the Three Gorges cascaded hydropower system consisting of the Three Gorges Dam and Gezhouba Dam located on the Yangtze River in China is studied. Two conflicting objectives, i.e., maximizing hydropower generation and minimizing deviation from the outflow lower target to realize the system’s economic, environmental and social benefits during the drought season, are optimized simultaneously. Experimental results demonstrate that the optimization framework helps to robustly derive multiple feasible non-dominated solutions with satisfactory convergence, diversity and extremity in one single run for the case studied.

Dynamic Programming Optimization of Multi-rate Multicast Video-Streaming Services

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Nestor Michael Caños Tiglao

2010-06-01

Full Text Available In large scale IP Television (IPTV and Mobile TV distributions, the video signal is typically encoded and transmitted using several quality streams, over IP Multicast channels, to several groups of receivers, which are classified in terms of their reception rate. As the number of video streams is usually constrained by both the number of TV channels and the maximum capacity of the content distribution network, it is necessary to find the selection of video stream transmission rates that maximizes the overall user satisfaction. In order to efficiently solve this problem, this paper proposes the Dynamic Programming Multi-rate Optimization (DPMO algorithm. The latter was comparatively evaluated considering several user distributions, featuring different access rate patterns. The experimental results reveal that DPMO is significantly more efficient than exhaustive search, while presenting slightly higher execution times than the non-optimal Multi-rate Step Search (MSS algorithm.

Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Patel G.C.M.

2016-09-01

Full Text Available The near net shaped manufacturing ability of squeeze casting process requiresto set the process variable combinations at their optimal levels to obtain both aesthetic appearance and internal soundness of the cast parts. The aesthetic and internal soundness of cast parts deal with surface roughness and tensile strength those can readily put the part in service without the requirement of costly secondary manufacturing processes (like polishing, shot blasting, plating, hear treatment etc.. It is difficult to determine the levels of the process variable (that is, pressure duration, squeeze pressure, pouring temperature and die temperature combinations for extreme values of the responses (that is, surface roughness, yield strength and ultimate tensile strength due to conflicting requirements. In the present manuscript, three population based search and optimization methods, namely genetic algorithm (GA, particle swarm optimization (PSO and multi-objective particle swarm optimization based on crowding distance (MOPSO-CD methods have been used to optimize multiple outputs simultaneously. Further, validation test has been conducted for the optimal casting conditions suggested by GA, PSO and MOPSO-CD. The results showed that PSO outperformed GA with regard to computation time.

Stall inception and warning in a single-stage transonic axial compressor with axial skewed slot casing treatment

International Nuclear Information System (INIS)

Lim, Byeung Jun; Kwon, Se Jin; Park, Tae Choon

2014-01-01

Characteristic changes in the stall inception in a single-stage transonic axial compressor with an axial skewed slot casing treatment were investigated experimentally. A rotating stall occurred intermittently in a compressor with an axial skewed slot, whereas spike-type rotating stalls occurred in the case of smooth casing. The axial skewed slot suppressed stall cell growth and increased the operating range. A mild surge, the frequency of which is the Helmholtz frequency of the compressor system, occurred with the rotating stall. The irregularity in the pressure signals at the slot bottom increased decreasing flow rate. An autocorrelation-based stall warning method was applied to the measured pressure signals. Results estimate and warn against the stall margin in a compressor with an axial skewed slot.

PIV study of large-scale flow organisation in slot jets

International Nuclear Information System (INIS)

Shestakov, Maxim V.; Dulin, Vladimir M.; Tokarev, Mikhail P.; Sikovsky, Dmitrii Ph.; Markovich, Dmitriy M.

2015-01-01

Highlights: • Volumetric velocity measurements are perfumed by PIV to analyse 3D flow organisation in a slot jet. • Proper orthogonal decomposition is used to extract coherent flow motion. • Movement of quasi-two-dimensional large-scale vortices is associated with jet meandering. • Amplitude of jet meandering is found to be aperiodically modulated. • Secondary longitudinal vortex rolls are important for cross-stream mixing and momentum transfer. - Abstract: The paper reports on particle image velocimetry (PIV) measurements in turbulent slot jets bounded by two solid walls with the separation distance smaller than the jet width (5–40%). In the far-field such jets are known to manifest features of quasi-two dimensional, two component turbulence. Stereoscopic and tomographic PIV systems were used to analyse local flows. Proper orthogonal decomposition (POD) was applied to extract coherent modes of the velocity fluctuations. The measurements were performed both in the initial region close to the nozzle exit and in the far fields of the developed turbulent slot jets for Re ⩾ 10,000. A POD analysis in the initial region indicates a correlation between quasi-2D vortices rolled-up in the shear layer and local flows in cross-stream planes. While the near-field turbulence shows full 3D features, the wall-normal velocity fluctuations day out gradually due to strong wall-damping resulting in an almost two-component turbulence. On the other hand, the longitudinal vortex rolls take over to act as the main agents in wall-normal and spanwise mixing and momentum transfer. The quantitative analysis indicates that the jet meandering amplitude was aperiodically modulated when arrangement of the large-scale quasi-2D vortices changed between asymmetric and symmetric pattern relatively to the jet axis. The paper shows that the dynamics of turbulent slot jets are more complex than those of 2D, plane and rectangular 3D jets. In particular, the detected secondary longitudinal

Lift Optimization Study of a Multi-Element Three-Segment Variable Camber Airfoil

Science.gov (United States)

Kaul, Upender K.; Nguyen, Nhan T.

2016-01-01

This paper reports a detailed computational high-lift study of the Variable Camber Continuous Trailing Edge Flap (VCCTEF) system carried out to explore the best VCCTEF designs, in conjunction with a leading edge flap called the Variable Camber Krueger (VCK), for take-off and landing. For this purpose, a three-segment variable camber airfoil employed as a performance adaptive aeroelastic wing shaping control effector for a NASA Generic Transport Model (GTM) in landing and take-off configurations is considered. The objective of the study is to define optimal high-lift VCCTEF settings and VCK settings/configurations. A total of 224 combinations of VCK settings/configurations and VCCTEF settings are considered for the inboard GTM wing, where the VCCTEFs are configured as a Fowler flap that forms a slot between the VCCTEF and the main wing. For the VCK settings of deflection angles of 55deg, 60deg and 65deg, 18, 19 and 19 vck configurations, respectively, were considered for each of the 4 different VCCTEF deflection settings. Different vck configurations were defined by varying the horizontal and vertical distance of the vck from the main wing. A computational investigation using a Reynolds-Averaged Navier-Stokes (RANS) solver was carried out to complement a wind-tunnel experimental study covering three of these configurations with the goal of identifying the most optimal high-lift configurations. Four most optimal high-lift configurations, corresponding to each of the VCK deflection settings, have been identified out of all the different configurations considered in this study yielding the highest lift performance.

Optimal control of cooperative multi-vehicle systems; Optimalsteuerung kooperierender Mehrfahrzeugsysteme

Energy Technology Data Exchange (ETDEWEB)

Reinl, Christian; Stryk, Oskar von [Technische Univ. Darmstadt (Germany). FB Informatik; Glocker, Markus [Trimble Terrasat GmbH, Hoehenkirchen (Germany)

2009-07-01

Nonlinear hybrid dynamical systems for modeling optimal cooperative control enable a tight and formal coupling of discrete and continuous state dynamics, i.e. of dynamic role and task assignment with switching dynamics of motions. In the resulting mixed-integer multi-phase optimal control problems constraints on the discrete and continuous state and control variables can be considered, e.g., formation or communication requirements. Two numerical methods are investigated: a decomposition approach using branch-and-bound and direct collocation methods as well as an approximation by large-scale, mixed-integer linear problems. Both methods are applied to example problems: the optimal simultaneous waypoint sequencing and trajectory planning of a team of aerial vehicles and the optimization of role distribution and trajectories in robot soccer. (orig.)

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

Directory of Open Access Journals (Sweden)

He Bin

2016-01-01

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

A multi-objective genetic approach to domestic load scheduling in an energy management system

International Nuclear Information System (INIS)

Soares, Ana; Antunes, Carlos Henggeler; Oliveira, Carlos; Gomes, Álvaro

2014-01-01

In this paper a multi-objective genetic algorithm is used to solve a multi-objective model to optimize the time allocation of domestic loads within a planning period of 36 h, in a smart grid context. The management of controllable domestic loads is aimed at minimizing the electricity bill and the end-user’s dissatisfaction concerning two different aspects: the preferred time slots for load operation and the risk of interruption of the energy supply. The genetic algorithm is similar to the Elitist NSGA-II (Nondominated Sorting Genetic Algorithm II), in which some changes have been introduced to adapt it to the physical characteristics of the load scheduling problem and improve usability of results. The mathematical model explicitly considers economical, technical, quality of service and comfort aspects. Illustrative results are presented and the characteristics of different solutions are analyzed. - Highlights: • A genetic algorithm similar to the NSGA-II is used to solve a multi-objective model. • The optimized time allocation of domestic loads in a smart grid context is achieved. • A variable preference profile for the operation of the managed loads is included. • A safety margin is used to account for the quality of the energy services provided. • A non-dominated front with the solutions in the two-objective space is obtained

Stepwise multi-criteria optimization for robotic radiosurgery

International Nuclear Information System (INIS)

Schlaefer, A.; Schweikard, A.

2008-01-01

Achieving good conformality and a steep dose gradient around the target volume remains a key aspect of radiosurgery. Clearly, this involves a trade-off between target coverage, conformality of the dose distribution, and sparing of critical structures. Yet, image guidance and robotic beam placement have extended highly conformal dose delivery to extracranial and moving targets. Therefore, the multi-criteria nature of the optimization problem becomes even more apparent, as multiple conflicting clinical goals need to be considered coordinate to obtain an optimal treatment plan. Typically, planning for robotic radiosurgery is based on constrained optimization, namely linear programming. An extension of that approach is presented, such that each of the clinical goals can be addressed separately and in any sequential order. For a set of common clinical goals the mapping to a mathematical objective and a corresponding constraint is defined. The trade-off among the clinical goals is explored by modifying the constraints and optimizing a simple objective, while retaining feasibility of the solution. Moreover, it becomes immediately obvious whether a desired goal can be achieved and where a trade-off is possible. No importance factors or predefined prioritizations of clinical goals are necessary. The presented framework forms the basis for interactive and automated planning procedures. It is demonstrated for a sample case that the linear programming formulation is suitable to search for a clinically optimal treatment, and that the optimization steps can be performed quickly to establish that a Pareto-efficient solution has been found. Furthermore, it is demonstrated how the stepwise approach is preferable compared to modifying importance factors

Fuzzy portfolio optimization advances in hybrid multi-criteria methodologies

CERN Document Server

Gupta, Pankaj; Inuiguchi, Masahiro; Chandra, Suresh

2014-01-01

This monograph presents a comprehensive study of portfolio optimization, an important area of quantitative finance. Considering that the information available in financial markets is incomplete and that the markets are affected by vagueness and ambiguity, the monograph deals with fuzzy portfolio optimization models. At first, the book makes the reader familiar with basic concepts, including the classical mean–variance portfolio analysis. Then, it introduces advanced optimization techniques and applies them for the development of various multi-criteria portfolio optimization models in an uncertain environment. The models are developed considering both the financial and non-financial criteria of investment decision making, and the inputs from the investment experts. The utility of these models in practice is then demonstrated using numerical illustrations based on real-world data, which were collected from one of the premier stock exchanges in India. The book addresses both academics and professionals pursuin...

Co-simulation of a complete rectenna with a circular slot loop antenna in CPW technology

Science.gov (United States)

Rivière, Jérôme; Douyère, Alexandre; Cazour, Jonathan; Alicalapa, Frédéric; Luk, Jean-Daniel Lan Sun

2017-05-01

This study starts with the design of a planar and compact CPW antenna fabricated on Arlon AD1000 substrate, ɛr=10.35. The antenna is a coplanar waveguide (CPW) fed circular slot loop antenna matched to the standard impedance 50 Ω by two stubs. The goal is to implement this antenna with a CPW RF/DC rectifier to build an optimized low power level rectenna. The rectenna design is restricted to allow easy and fast fabrication of an array with a high reproducibility. The full rectenna is simulated and achieves 10% effciency at -20 dBm.

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

Science.gov (United States)

Meyn, Larry A.

2018-01-01

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

Study on collaborative optimization control of ventilation and radon reduction system based on multi-agent technology

International Nuclear Information System (INIS)

Dai Jianyong; Meng Lingcong; Zou Shuliang

2015-01-01

According to the radioactive safety features such as radon and its progeny, combined with the theory of ventilation system, structure of multi-agent system for ventilation and radon reduction system is constructed with the application of multi agent technology. The function attribute of the key agent and the connection between the nodes in the multi-agent system are analyzed to establish the distributed autonomous logic structure and negotiation mechanism of multi agent system of ventilation and radon reduction system, and thus to implement the coordination optimization control of the multi-agent system. The example analysis shows that the system structure of the multi-agent system of ventilation and reducing radon system and its collaborative mechanism can improve and optimize the radioactive pollutants control, which provides a theoretical basis and important application prospect. (authors)

Semi-automatic parking slot marking recognition for intelligent parking assist systems

Directory of Open Access Journals (Sweden)

Ho Gi Jung

2014-01-01

Full Text Available This paper proposes a semi-automatic parking slot marking-based target position designation method for parking assist systems in cases where the parking slot markings are of a rectangular type, and its efficient implementation for real-time operation. After the driver observes a rearview image captured by a rearward camera installed at the rear of the vehicle through a touchscreen-based human machine interface, a target parking position is designated by touching the inside of a parking slot. To ensure the proposed method operates in real-time in an embedded environment, access of the bird's-eye view image is made efficient: image-wise batch transformation is replaced with pixel-wise instantaneous transformation. The proposed method showed a 95.5% recognition rate in 378 test cases with 63 test images. Additionally, experiments confirmed that the pixel-wise instantaneous transformation reduced execution time by 92%.

MIDA - Optimizing control room performance through multi-modal design

International Nuclear Information System (INIS)

Ronan, A. M.

2006-01-01

Multi-modal interfaces can support the integration of humans with information processing systems and computational devices to maximize the unique qualities that comprise a complex system. In a dynamic environment, such as a nuclear power plant control room, multi-modal interfaces, if designed correctly, can provide complementary interaction between the human operator and the system which can improve overall performance while reducing human error. Developing such interfaces can be difficult for a designer without explicit knowledge of Human Factors Engineering principles. The Multi-modal Interface Design Advisor (MIDA) was developed as a support tool for system designers and developers. It provides design recommendations based upon a combination of Human Factors principles, a knowledge base of historical research, and current interface technologies. MIDA's primary objective is to optimize available multi-modal technologies within a human computer interface in order to balance operator workload with efficient operator performance. The purpose of this paper is to demonstrate MIDA and illustrate its value as a design evaluation tool within the nuclear power industry. (authors)

A Pareto-based multi-objective optimization algorithm to design energy-efficient shading devices

International Nuclear Information System (INIS)

Khoroshiltseva, Marina; Slanzi, Debora; Poli, Irene

2016-01-01

Highlights: • We present a multi-objective optimization algorithm for shading design. • We combine Harmony search and Pareto-based procedures. • Thermal and daylighting performances of external shading were considered. • We applied the optimization process to a residential social housing in Madrid. - Abstract: In this paper we address the problem of designing new energy-efficient static daylight devices that will surround the external windows of a residential building in Madrid. Shading devices can in fact largely influence solar gains in a building and improve thermal and lighting comforts by selectively intercepting the solar radiation and by reducing the undesirable glare. A proper shading device can therefore significantly increase the thermal performance of a building by reducing its energy demand in different climate conditions. In order to identify the set of optimal shading devices that allow a low energy consumption of the dwelling while maintaining high levels of thermal and lighting comfort for the inhabitants we derive a multi-objective optimization methodology based on Harmony Search and Pareto front approaches. The results show that the multi-objective approach here proposed is an effective procedure in designing energy efficient shading devices when a large set of conflicting objectives characterizes the performance of the proposed solutions.

Multi-objective optimization approach for air traffic flow management

Directory of Open Access Journals (Sweden)

Fadil Rabie

2017-01-01

The decision-making stage was then performed with the aid of data clustering techniques to reduce the sizeof the Pareto-optimal set and obtain a smaller representation of the multi-objective design space, there by making it easier for the decision-maker to find satisfactory and meaningful trade-offs, and to select a preferred final design solution.

Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g

Directory of Open Access Journals (Sweden)

Guozheng Li

2018-03-01

Full Text Available The integration of renewable energies into combined cooling, heating, and power (CCHP systems has become increasingly popular in recent years. However, the optimization of renewable energies integrated CCHP (RECCHP systems (i.e., optimal component configurations is far from being well addressed, especially in isolated mode. This study aims to fill this research gap. A multi-objective optimization model characterizing the system reliability, system cost, and environmental sustainability is constructed. In this model, the objectives include minimization of annual total cost (ATC, carbon dioxide emission (CDE, and loss of energy supply probability (LESP. The decision variables representing the configuration of the RECCHP system include the number of photovoltaic (PV panels and wind turbines (WTs, the tilt angle of PV panels, the height of WTs, the maximum fuel consumption, and the capacity of battery and heat storage tanks (HSTs. The multi-objective model is solved by a multi-objective evolutionary algorithm, namely, the preference-inspired coevolutionary algorithm (PICEA-g, resulting in a set of Pareto optimal (trade-off solutions. Then, a decision-making process is demonstrated, selecting a preferred solution amongst those trade-off solutions by further considering the decision-maker preferences. Furthermore, on the optimization of the RECCHP system, operational strategies (i.e., following electric load, FEL, and following thermal load, FTL are considered, respectively. Experimental results show that the FEL and FTL strategies lead to different optimal configurations. In general, the FTL is recommended in summer and winter, while the FEL is more suitable for spring and autumn. Compared with traditional energy systems, RECCHP has better economic and environmental advantages.

Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

Directory of Open Access Journals (Sweden)

Xiaoya Ma

2015-11-01

Full Text Available As the main feature of land use planning, land use allocation (LUA optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA optimization is a multi-objective optimization problem under the land use supply and demand constraints in a region. In order to obtain a better sustainable multi-objective LUA optimization solution, the present study proposes a LUA model based on the multi-objective artificial immune optimization algorithm (MOAIM-LUA model. The main achievements of the present study are as follows: (a the land-use supply and demand factors are analyzed and the constraint conditions of LUA optimization problems are constructed based on the analysis framework of the balance between the land use supply and demand; (b the optimization objectives of LUA optimization problems are defined and modeled using ecosystem service value theory and land rent and price theory; and (c a multi-objective optimization algorithm is designed for solving multi-objective LUA optimization problems based on the novel immune clonal algorithm (NICA. On the basis of the aforementioned achievements, MOAIM-LUA was applied to a real case study of land-use planning in Anlu County, China. Compared to the current land use situation in Anlu County, optimized LUA solutions offer improvements in the social and ecological objective areas. Compared to the existing models, such as the non-dominated sorting genetic algorithm-II, experimental results demonstrate that the model designed in the present study can obtain better non-dominated solution sets and is superior in terms of algorithm stability.

Development and Validation of a Sensitive Method for Trace Nickel Determination by Slotted Quartz Tube Flame Atomic Absorption Spectrometry After Dispersive Liquid-Liquid Microextraction.

Science.gov (United States)

Yolcu, Şükran Melda; Fırat, Merve; Chormey, Dotse Selali; Büyükpınar, Çağdaş; Turak, Fatma; Bakırdere, Sezgin

2018-05-01

In this study, dispersive liquid-liquid microextraction was systematically optimized for the preconcentration of nickel after forming a complex with diphenylcarbazone. The measurement output of the flame atomic absorption spectrometer was further enhanced by fitting a custom-cut slotted quartz tube to the flame burner head. The extraction method increased the amount of nickel reaching the flame and the slotted quartz tube increased the residence time of nickel atoms in the flame to record higher absorbance. Two methods combined to give about 90 fold enhancement in sensitivity over the conventional flame atomic absorption spectrometry. The optimized method was applicable over a wide linear concentration range, and it gave a detection limit of 2.1 µg L -1 . Low relative standard deviations at the lowest concentration in the linear calibration plot indicated high precision for both extraction process and instrumental measurements. A coal fly ash standard reference material (SRM 1633c) was used to determine the accuracy of the method, and experimented results were compatible with the certified value. Spiked recovery tests were also used to validate the applicability of the method.

[The characteristics of and social support for pathological gamblers among "pachinko" or "slot" users in Japan].

Science.gov (United States)

Kumagami, Takashi

2014-01-01

In Japan, there are one to two million people suspected of being pathological gamblers according to the definition in DSM-IV-TR. Almost all of them use "pachinko" or "slot," which are gambling stores, throughout Japan, that number 12,000 in total. However, the characteristics and ratio of pathological "pachinko" and "slot" gamblers have not been investigated. The author aimed to determine the characteristics, ratio, and social support available for these users. The author administered an internet survey for users of "pachinko" or "slot." Two hundred and fifty users visited "pachinko" or "slot" stores more than twice a week, and 250 users visited once a week or once a month. The Japanese version of the South Oaks Gambling Screen was administered, and gamblers were asked about their awareness of pathological gambling and the condition of their social support. The author observed that 70.2% of "pachinko" or "slot" users were suspected pathological gamblers and 28.6% of "pachinko" or "slot" users were severe gamblers. A total of 39.3% of them were aware of their pathological gambling, and 6.5% of users who had awareness of pathological gambling had social support. However, most of their social support consisted of family and friends, and almost none of them attended psychiatric clinics, community health centers, or self-help groups like gamblers anonymous. Almost all "pachinko" or "slot" users were suspected of being pathological or severe gamblers. However, they did not approach psychiatric facilities or self-help groups. The author strongly recommends the need for educational programs in junior or high school to prevent future pathological gambling, and create awareness of the dangers of pathological gambling through TV commercials and "pachinko" or "slot" stores. Pathological gambling is a disease that afflicts many people; hence, psychiatric and social welfare professionals should continue to stress the dangers of and offer prevention programs for "pachinko" or

System, methods and apparatus for program optimization for multi-threaded processor architectures

Science.gov (United States)

Bastoul, Cedric; Lethin, Richard A; Leung, Allen K; Meister, Benoit J; Szilagyi, Peter; Vasilache, Nicolas T; Wohlford, David E

2015-01-06

Methods, apparatus and computer software product for source code optimization are provided. In an exemplary embodiment, a first custom computing apparatus is used to optimize the execution of source code on a second computing apparatus. In this embodiment, the first custom computing apparatus contains a memory, a storage medium and at least one processor with at least one multi-stage execution unit. The second computing apparatus contains at least two multi-stage execution units that allow for parallel execution of tasks. The first custom computing apparatus optimizes the code for parallelism, locality of operations and contiguity of memory accesses on the second computing apparatus. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

Frequency Reconfigurable Circular Patch Antenna with an Arc-Shaped Slot Ground Controlled by PIN Diodes

Directory of Open Access Journals (Sweden)

Yao Chen

2017-01-01

Full Text Available In this paper, a compact frequency reconfigurable circular patch antenna with an arc-shaped slot loaded in the ground layer is proposed for multiband wireless communication applications. By controlling the ON/OFF states of the five PIN diodes mounted on the arc-shaped slot, the effective length of the arc-shaped slot and the effective length of antennas current are changed, and accordingly six-frequency band reconfiguration can be achieved. The simulated and measured results show that the antenna can operate from 1.82 GHz to 2.46 GHz, which is located in DCS1800 (1.71–1.88 GHz, UMTS (2.11–2.20 GHz, WiBro (2.3–2.4 GHz, and Bluetooth (2.4–2.48 GHz frequency bands and so forth. Compared to the common rectangular slot circular patch antenna, the proposed arc-shaped slot circular patch antenna not only has a better rotational symmetry with the circular patch and substrate but also has more compact size. For the given operating frequency at 1.82 GHz, over 55% area reduction is achieved in this design with respect to the common design with rectangular slot. Since the promising frequency reconfiguration, this antenna may have potential applications in modern multiband and multifunctional mobile communication systems.

Grey Relational Analyses for Multi-Objective Optimization of Turning S45C Carbon Steel

International Nuclear Information System (INIS)

Shah, A.H.A.; Azmi, A.I.; Khalil, A.N.M.

2016-01-01

The optimization of performance characteristics in turning process can be achieved through selection of proper machining parameters. It is well known that many researchers have successfully reported the optimization of single performance characteristic. Nevertheless, the multi-objective optimization can be difficult and challenging to be studied due to its complexity in analysis. This is because an improvement of one performance characteristic may lead to degradation of other performance characteristic. As a result, the study of multi-objective optimization in CNC turning of S45C carbon steel has been attempted in this paper through Taguchi and Grey Relational Analysis (GRA) method. Through this methodology, the multiple performance characteristics, namely; surface roughness, material removal rate (MRR), tool wear, and power consumption; can be optimized simultaneously. It appears from the experimental results that the multiple performance characteristics in CNC turning was achieved and improved through the methodology employed. (paper)

Pathological gambling: A comparison of gambling at German-style slot machines and "Classical" gambling.

Science.gov (United States)

Fabian, T

1995-09-01

German-style slot machines and related legal issues are described. On the basis of a survey on 437 members of self-help groups (Gamblers Anonymous) in Germany, slot machine gamblers were compared with casino gamblers on such variables as sociodemographic data, gambling behaviour, financial expenditure, emotional experience while gambling, symptoms of pathological gambling, psychosocial consequences and gambling related delinquency. The casino gamblers' gambling behaviour is financially more extensive. There were similarities regarding the emotional intensity of the gambling experience. However the casino gamblers show more pronounced symptoms of pathological gambling and the psychosocial consequences of their gambling behaviour are more severe. In spite of these differences, the data show that for young people slot machines can be as stimulating and therefore as dangerous as casino gambling. The young slot machine gambler runs a similar risk of acquiring a pathological gambling habit as the casino gambler.

Collaborative Emission Reduction Model Based on Multi-Objective Optimization for Greenhouse Gases and Air Pollutants.

Science.gov (United States)

Meng, Qing-chun; Rong, Xiao-xia; Zhang, Yi-min; Wan, Xiao-le; Liu, Yuan-yuan; Wang, Yu-zhi

2016-01-01

CO2 emission influences not only global climate change but also international economic and political situations. Thus, reducing the emission of CO2, a major greenhouse gas, has become a major issue in China and around the world as regards preserving the environmental ecology. Energy consumption from coal, oil, and natural gas is primarily responsible for the production of greenhouse gases and air pollutants such as SO2 and NOX, which are the main air pollutants in China. In this study, a mathematical multi-objective optimization method was adopted to analyze the collaborative emission reduction of three kinds of gases on the basis of their common restraints in different ways of energy consumption to develop an economic, clean, and efficient scheme for energy distribution. The first part introduces the background research, the collaborative emission reduction for three kinds of gases, the multi-objective optimization, the main mathematical modeling, and the optimization method. The second part discusses the four mathematical tools utilized in this study, which include the Granger causality test to analyze the causality between air quality and pollutant emission, a function analysis to determine the quantitative relation between energy consumption and pollutant emission, a multi-objective optimization to set up the collaborative optimization model that considers energy consumption, and an optimality condition analysis for the multi-objective optimization model to design the optimal-pole algorithm and obtain an efficient collaborative reduction scheme. In the empirical analysis, the data of pollutant emission and final consumption of energies of Tianjin in 1996-2012 was employed to verify the effectiveness of the model and analyze the efficient solution and the corresponding dominant set. In the last part, several suggestions for collaborative reduction are recommended and the drawn conclusions are stated.

Advanced hybrid query tree algorithm based on slotted backoff mechanism in RFID

Directory of Open Access Journals (Sweden)

XIE Xiaohui

2013-12-01

Full Text Available The merits of performance quality for a RFID system are determined by the effectiveness of tag anti-collision algorithm.Many algorithms for RFID system of tag identification have been proposed,but they all have obvious weaknesses,such as slow speed of identification,unstable and so on.The existing algorithms can be divided into two groups,one is based on ALOHA and another is based on query tree.This article is based on the hybrid query tree algorithm,combined with a slotted backoff mechanism and a specific encoding (Manchester encoding.The number of value“1” in every three consecutive bits of tags is used to determine the tag response time slots,which will greatly reduce the time slot of the collision and improve the recognition efficiency.

Cross-layer optimization of wireless multi-hop networks

OpenAIRE

Soldati, Pablo

2007-01-01

The interest in wireless communications has grown constantly for the past decades, leading to an enormous number of applications and services embraced by billions of users. In order to meet the increasing demand for mobile Internet access, several high data-rate radio networking technologies have been proposed to offer wide area high-speed wireless communications, eventually replacing fixed (wired) networks for many applications. This thesis considers cross-layer optimization of multi-hop rad...

Image de-noising based on mathematical morphology and multi-objective particle swarm optimization

Science.gov (United States)

Dou, Liyun; Xu, Dan; Chen, Hao; Liu, Yicheng

2017-07-01

To overcome the problem of image de-noising, an efficient image de-noising approach based on mathematical morphology and multi-objective particle swarm optimization (MOPSO) is proposed in this paper. Firstly, constructing a series and parallel compound morphology filter based on open-close (OC) operation and selecting a structural element with different sizes try best to eliminate all noise in a series link. Then, combining multi-objective particle swarm optimization (MOPSO) to solve the parameters setting of multiple structural element. Simulation result shows that our algorithm can achieve a superior performance compared with some traditional de-noising algorithm.

Finite element analysis of slot wall deformation in stainless steel and titanium orthodontic brackets during simulated palatal root torque.

Science.gov (United States)

Magesh, Varadaraju; Harikrishnan, Pandurangan; Kingsly Jeba Singh, Devadhas

2018-04-01

Torque applied on anterior teeth is vital for root positioning and stability. The aim of this study was to evaluate the detailed slot wall deformation in stainless steel (SS) and titanium (Ti) edgewise brackets during palatal root torque using finite element analysis. A finite element model was developed from a maxillary central incisor SS bracket (0.022 in). The generated torque values from an SS rectangular archwire (0.019 × 0.025 in) while twisting from 5° to 40° were obtained experimentally by a spine tester, and the calculated torque force was applied in the bracket slot. The deformations of the slot walls in both SS and Ti brackets were measured at various locations. There were gradual increases in the deformations of both bracket slot walls from the bottom to top locations. In the SS bracket slot for the 40° twist, the deformations were 9.28, 36.8, and 44.8 μm in the bottom, middle, and top slot wall locations, respectively. Similarly, in the Ti bracket slot for the 40° twist, the deformations were 39.2, 62.4, and 76.2 μm in the bottom, middle, and top slot wall locations, respectively. The elastic limits were reached at 28° for SS and at 37° for Ti. Both SS and Ti bracket slots underwent deformation during torque application. There are variations in the deformations at different locations in the slot walls and between the materials. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Multi-objective optimization of Stirling engine using Finite Physical Dimensions Thermodynamics (FPDT) method

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).

A Global Multi-Objective Optimization Tool for Design of Mechatronic Components using Generalized Differential Evolution

DEFF Research Database (Denmark)

Bech, Michael Møller; Nørgård, Christian; Roemer, Daniel Beck

2016-01-01

This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri-objectiv......This paper illustrates how the relatively simple constrained multi-objective optimization algorithm Generalized Differential Evolution 3 (GDE3), can assist with the practical sizing of mechatronic components used in e.g. digital displacement fluid power machinery. The studied bi- and tri...... different optimization control parameter settings and it is concluded that GDE3 is a reliable optimization tool that can assist mechatronic engineers in the design and decision making process....

Evaluation of detectable angle of mid-infrared slot antennas

Science.gov (United States)

Obara, R.; Horikawa, J.; Shimakage, H.; Kawakami, A.

2017-07-01

For evaluations of a mid-infrared (MIR) detectors with antenna, we constructed an angular dependence measurement system of the antenna properties. The fabricated MIR detector consisted of twin slot antennas and a bolometer. The area of the slot antennas was designed to be 2.6 × 0.2 μm2 as to resonate at 61 THz, and they were located parallel and separated 1.6 μm each other. The bolometer was fabricated using by a 7.0-nm thick NbN thin film, and located at the center of the twin antennas. We measured polarization angle dependence and directivity, and showed that the MIR antennas have polarization dependence and directivity like radiofrequency antennas.

Intersection signal control multi-objective optimization based on genetic algorithm

Directory of Open Access Journals (Sweden)

Zhanhong Zhou

2014-04-01

Full Text Available A signal control intersection increases not only vehicle delay, but also vehicle emissions and fuel consumption in that area. Because more and more fuel and air pollution problems arise recently, an intersection signal control optimization method which aims at reducing vehicle emissions, fuel consumption and vehicle delay is required heavily. This paper proposed a signal control multi-object optimization method to reduce vehicle emissions, fuel consumption and vehicle delay simultaneously at an intersection. The optimization method combined the Paramics microscopic traffic simulation software, Comprehensive Modal Emissions Model (CMEM, and genetic algorithm. An intersection in Haizhu District, Guangzhou, was taken for a case study. The result of the case study shows the optimal timing scheme obtained from this method is better than the Webster timing scheme.

Clean Air Slots Amid Dense Atmospheric Pollution in Southern Africa

Science.gov (United States)

Hobbs, Peter V.

2003-01-01

During the flights of the University of Washington's Convair-580 in the Southern African Regional Science Initiative (SAFARI 2000) in southern Africa, a phenomenon was observed that has not been reported previously. This was the occurrence of thin layers of remarkably clean air, sandwiched between heavily polluted air, which persisted for many hours during the day. Photographs are shown of these clean air slots (CAS), and particle concentrations and light scattering coefficients in and around such slot are presented. An explanation is proposed for the propensity of CAS to form in southern Africa during the dry season.

Wideband, Low-Profile, Dual-Polarized Slot Antenna with an AMC Surface for Wireless Communications

Directory of Open Access Journals (Sweden)

Wei Hu

2016-01-01

Full Text Available A wideband dual-polarized slot antenna loaded with artificial magnetic conductor (AMC is proposed for WLAN/WIMAX and LTE applications. The slot antenna mainly consists of two pairs of arrow-shaped slots along the diagonals of the square patch. Stepped microstrip feedlines are placed orthogonally to excite the horizontal and vertical polarizations of the antenna. To realize unidirectional radiation and low profile, an AMC surface composed of 7 × 7 unit cells is designed underneath a distance of 0.09λ0 (λ0 being the wavelength in free space at 2.25 GHz from the slot antenna. Both the dual-polarized slot antenna and the AMC surface are fabricated and measured. Experimental results demonstrate that the proposed antenna achieves for both polarizations a wide impedance bandwidth (return loss 10 dB of 36.7%, operating from 1.96 to 2.84 GHz. The isolation between the two input ports keeps higher than 29 dB whereas the cross-polarization levels basically maintain lower than −30 dB across the entire frequency band. High front-to-back ratios better than 22 dB and a stable gain higher than 8 dBi are obtained over the whole band.

A rectangle bin packing optimization approach to the signal scheduling problem in the FlexRay static segment

Institute of Scientific and Technical Information of China (English)

Rui ZHAO; Gui-he QIN; Jia-qiao LIU

2016-01-01

As FlexRay communication protocol is extensively used in distributed real-time applications on vehicles, signal scheduling in FlexRay network becomes a critical issue to ensure the safe and efficient operation of time-critical applications. In this study, we propose a rectangle bin packing optimization approach to schedule communication signals with timing constraints into the FlexRay static segment at minimum bandwidth cost. The proposed approach, which is based on integer linear program-ming (ILP), supports both the slot assignment mechanisms provided by the latest version of the FlexRay specification, namely, the single sender slot multiplexing, and multiple sender slot multiplexing mechanisms. Extensive experiments on a synthetic and an automotive X-by-wire system case study demonstrate that the proposed approach has a well optimized performance.

Probing optimal measurement configuration for optical scatterometry by the multi-objective genetic algorithm

Science.gov (United States)

Chen, Xiuguo; Gu, Honggang; Jiang, Hao; Zhang, Chuanwei; Liu, Shiyuan

2018-04-01

Measurement configuration optimization (MCO) is a ubiquitous and important issue in optical scatterometry, whose aim is to probe the optimal combination of measurement conditions, such as wavelength, incidence angle, azimuthal angle, and/or polarization directions, to achieve a higher measurement precision for a given measuring instrument. In this paper, the MCO problem is investigated and formulated as a multi-objective optimization problem, which is then solved by the multi-objective genetic algorithm (MOGA). The case study on the Mueller matrix scatterometry for the measurement of a Si grating verifies the feasibility of the MOGA in handling the MCO problem in optical scatterometry by making a comparison with the Monte Carlo simulations. Experiments performed at the achieved optimal measurement configuration also show good agreement between the measured and calculated best-fit Mueller matrix spectra. The proposed MCO method based on MOGA is expected to provide a more general and practical means to solve the MCO problem in the state-of-the-art optical scatterometry.

Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

Science.gov (United States)

Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

2017-04-01

In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

Wave Propagation in a coaxial waveguide with a periodic slot array

CERN Document Server

Alesini, D; Garganese, C; Migliorati, M; Palumbo, L

2001-01-01

In this paper we present the numerical and experimental study of the electromagnetic elds that propagate in a coaxial waveguide having periodic slots in the inner conductor. The aim of the work is to estimate the e ects of the holes on the phase velocity of the eld propagating in structures like the LHC liner, and to which extent these elds can be considered synchronous with the generating beam. To this end we have performed a numerical analysis by using the MAFIA simulation code, and have obtained, for a given geometry, the ampli- tude of the slowing down of the phase velocity due to the presence of the slot array. We have then performed a set of measurements of this e ect on a simple coaxial resonator, measuring the shift of the resonance frequencies produced by the slots. This shift, related to the phase velocity, has been compared with the results obtained with the simulations.

Slot-waveguide biochemical sensor.

Science.gov (United States)

Barrios, Carlos A; Gylfason, Kristinn B; Sánchez, Benito; Griol, Amadeu; Sohlström, H; Holgado, M; Casquel, R

2007-11-01

We report an experimental demonstration of an integrated biochemical sensor based on a slot-waveguide microring resonator. The microresonator is fabricated on a Si3N4-SiO2 platform and operates at a wavelength of 1.3 microm. The transmission spectrum of the sensor is measured with different ambient refractive indices ranging from n=1.33 to 1.42. A linear shift of the resonant wavelength with increasing ambient refractive index of 212 nm/refractive index units (RIU) is observed. The sensor detects a minimal refractive index variation of 2x10(-4) RIU.

Fuzzy preference based interactive fuzzy physical programming and its application in multi-objective optimization

International Nuclear Information System (INIS)

Zhang, Xu; Huang, Hong Zhong; Yu, Lanfeng

2006-01-01

Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer

Optimal maintenance of a multi-unit system under dependencies

Science.gov (United States)

Sung, Ho-Joon

The availability, or reliability, of an engineering component greatly influences the operational cost and safety characteristics of a modern system over its life-cycle. Until recently, the reliance on past empirical data has been the industry-standard practice to develop maintenance policies that provide the minimum level of system reliability. Because such empirically-derived policies are vulnerable to unforeseen or fast-changing external factors, recent advancements in the study of topic on maintenance, which is known as optimal maintenance problem, has gained considerable interest as a legitimate area of research. An extensive body of applicable work is available, ranging from those concerned with identifying maintenance policies aimed at providing required system availability at minimum possible cost, to topics on imperfect maintenance of multi-unit system under dependencies. Nonetheless, these existing mathematical approaches to solve for optimal maintenance policies must be treated with caution when considered for broader applications, as they are accompanied by specialized treatments to ease the mathematical derivation of unknown functions in both objective function and constraint for a given optimal maintenance problem. These unknown functions are defined as reliability measures in this thesis, and theses measures (e.g., expected number of failures, system renewal cycle, expected system up time, etc.) do not often lend themselves to possess closed-form formulas. It is thus quite common to impose simplifying assumptions on input probability distributions of components' lifetime or repair policies. Simplifying the complex structure of a multi-unit system to a k-out-of-n system by neglecting any sources of dependencies is another commonly practiced technique intended to increase the mathematical tractability of a particular model. This dissertation presents a proposal for an alternative methodology to solve optimal maintenance problems by aiming to achieve the

A modified teaching–learning based optimization for multi-objective optimal power flow problem

International Nuclear Information System (INIS)

Shabanpour-Haghighi, Amin; Seifi, Ali Reza; Niknam, Taher

2014-01-01

Highlights: • A new modified teaching–learning based algorithm is proposed. • A self-adaptive wavelet mutation strategy is used to enhance the performance. • To avoid reaching a large repository size, a fuzzy clustering technique is used. • An efficiently smart population selection is utilized. • Simulations show the superiority of this algorithm compared with other ones. - Abstract: In this paper, a modified teaching–learning based optimization algorithm is analyzed to solve the multi-objective optimal power flow problem considering the total fuel cost and total emission of the units. The modified phase of the optimization algorithm utilizes a self-adapting wavelet mutation strategy. Moreover, a fuzzy clustering technique is proposed to avoid extremely large repository size besides a smart population selection for the next iteration. These techniques make the algorithm searching a larger space to find the optimal solutions while speed of the convergence remains good. The IEEE 30-Bus and 57-Bus systems are used to illustrate performance of the proposed algorithm and results are compared with those in literatures. It is verified that the proposed approach has better performance over other techniques

Discrepancies between selected Pareto optimal plans and final deliverable plans in radiotherapy multi-criteria optimization.

Science.gov (United States)

Kyroudi, Archonteia; Petersson, Kristoffer; Ghandour, Sarah; Pachoud, Marc; Matzinger, Oscar; Ozsahin, Mahmut; Bourhis, Jean; Bochud, François; Moeckli, Raphaël

2016-08-01

Multi-criteria optimization provides decision makers with a range of clinical choices through Pareto plans that can be explored during real time navigation and then converted into deliverable plans. Our study shows that dosimetric differences can arise between the two steps, which could compromise the clinical choices made during navigation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Adaptive multi-objective Optimization scheme for cognitive radio resource management

KAUST Repository

Alqerm, Ismail

2014-12-01

Cognitive Radio is an intelligent Software Defined Radio that is capable to alter its transmission parameters according to predefined objectives and wireless environment conditions. Cognitive engine is the actuator that performs radio parameters configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance. The optimization relies on adapting radio transmission parameters to environment conditions using constrained optimization modeling called fitness functions in an iterative manner. These functions include minimizing power consumption, Bit Error Rate, delay and interference. On the other hand, maximizing throughput and spectral efficiency. Cross-layer optimization is exploited to access environmental parameters from all TCP/IP stack layers. AMOS uses adaptive Genetic Algorithm in terms of its parameters and objective weights as the vehicle of optimization. The proposed scheme has demonstrated quick response and efficiency in three different scenarios compared to other schemes. In addition, it shows its capability to optimize the performance of TCP/IP layers as whole not only the physical layer.