Impulsive time-free transfers between halo orbits

NASA Astrophysics Data System (ADS)

Hiday, L. A.; Howell, K. C.

1992-08-01

A methodology is developed to design optimal time-free impulsive transfers between three-dimensional halo orbits in the vicinity of the interior L1 libration point of the sun-earth/moon barycenter system. The transfer trajectories are optimal in the sense that the total characteristics velocity required to implement the transfer exhibits a local minimum. Criteria are established whereby the implementation of a coast in the initial orbit, a coast in the final orbit, or dual coasts accomplishes a reduction in fuel expenditure. The optimality of a reference two-impulse transfer can be determined by examining the slope at the endpoints of a plot of the magnitude of the primer vector on the reference trajectory. If the initial and final slopes of the primer magnitude are zero, the transfer trajectory is optimal; otherwise, the execution of coasts is warranted. The optimal time of flight on the time-free transfer, and consequently, the departure and arrival locations on the halo orbits are determined by the unconstrained minimization of a function of two variables using a multivariable search technique. Results indicate that the cost can be substantially diminished by the allowance for coasts in the initial and final libration-point orbits.

Impulsive Time-Free Transfers Between Halo Orbits

NASA Astrophysics Data System (ADS)

Hiday-Johnston, L. A.; Howell, K. C.

1996-12-01

A methodology is developed to design optimal time-free impulsive transfers between three-dimensional halo orbits in the vicinity of the interior L 1 libration point of the Sun-Earth/Moon barycenter system. The transfer trajectories are optimal in the sense that the total characteristic velocity required to implement the transfer exhibits a local minimum. Criteria are established whereby the implementation of a coast in the initial orbit, a coast in the final orbit, or dual coasts accomplishes a reduction in fuel expenditure. The optimality of a reference two-impulse transfer can be determined by examining the slope at the endpoints of a plot of the magnitude of the primer vector on the reference trajectory. If the initial and final slopes of the primer magnitude are zero, the transfer trajectory is optimal; otherwise, the execution of coasts is warranted. The optimal time of flight on the time-free transfer, and consequently, the departure and arrival locations on the halo orbits are determined by the unconstrained minimization of a function of two variables using a multivariable search technique. Results indicate that the cost can be substantially diminished by the allowance for coasts in the initial and final libration-point orbits.

Symbiotic Optimization of Behavior

DTIC Science & Technology

2015-05-01

SYMBIOTIC OPTIMIZATION OF BEHAVIOR UNIVERSITY OF WASHINGTON MAY 2015 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED...2014 4. TITLE AND SUBTITLE SYMBIOTIC OPTIMIZATION OF BEHAVIOR 5a. CONTRACT NUMBER FA8750-12-1-0304 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT

Algorithm for solving of two-level hierarchical minimax program control problem of final state the regional socio-economic system in the presence of risks

NASA Astrophysics Data System (ADS)

Shorikov, A. F.

2017-10-01

In this paper we study the problem of optimization of guaranteed result for program control by the final state of regional social and economic system in the presence of risks. For this problem we propose a mathematical model in the form of two-level hierarchical minimax program control problem of the final state of this process with incomplete information. For solving of its problem we constructed the common algorithm that has a form of a recurrent procedure of solving a linear programming and a finite optimization problems.

Finite element approximation of an optimal control problem for the von Karman equations

NASA Technical Reports Server (NTRS)

Hou, L. Steven; Turner, James C.

1994-01-01

This paper is concerned with optimal control problems for the von Karman equations with distributed controls. We first show that optimal solutions exist. We then show that Lagrange multipliers may be used to enforce the constraints and derive an optimality system from which optimal states and controls may be deduced. Finally we define finite element approximations of solutions for the optimality system and derive error estimates for the approximations.

Topology-optimized metasurfaces: impact of initial geometric layout.

PubMed

Yang, Jianji; Fan, Jonathan A

2017-08-15

Topology optimization is a powerful iterative inverse design technique in metasurface engineering and can transform an initial layout into a high-performance device. With this method, devices are optimized within a local design phase space, making the identification of suitable initial geometries essential. In this Letter, we examine the impact of initial geometric layout on the performance of large-angle (75 deg) topology-optimized metagrating deflectors. We find that when conventional metasurface designs based on dielectric nanoposts are used as initial layouts for topology optimization, the final devices have efficiencies around 65%. In contrast, when random initial layouts are used, the final devices have ultra-high efficiencies that can reach 94%. Our numerical experiments suggest that device topologies based on conventional metasurface designs may not be suitable to produce ultra-high-efficiency, large-angle metasurfaces. Rather, initial geometric layouts with non-trivial topologies and shapes are required.

Optimal control theory determination of feasible return-to-launch-site aborts for the HL-20 Personnel Launch System vehicle

NASA Technical Reports Server (NTRS)

Dutton, Kevin E.

1994-01-01

The personnel launch system (PLS) being studied by NASA is a system to complement the space shuttle and provide alternative access to space. The PLS consists of a manned spacecraft launched by an expendable launch vehicle (ELV). A candidate for the manned spacecraft is the HL-20 lifting body. In the event of an ELV malfunction during the initial portion of the ascent trajectory, the HL-20 will separate from the rocket and perform an unpowered return to launch site (RTLS) abort. This work details an investigation, using optimal control theory, of the RTLS abort scenario. The objective of the optimization was to maximize final altitude. With final altitude as the cost function, the feasibility of an RTLS abort at different times during the ascent was determined. The method of differential inclusions was used to determine the optimal state trajectories, and the optimal controls were then calculated from the optimal states and state rates.

Supersonic Aerodynamic Design Improvements of an Arrow-Wing HSCT Configuration Using Nonlinear Point Design Methods

NASA Technical Reports Server (NTRS)

Unger, Eric R.; Hager, James O.; Agrawal, Shreekant

1999-01-01

This paper is a discussion of the supersonic nonlinear point design optimization efforts at McDonnell Douglas Aerospace under the High-Speed Research (HSR) program. The baseline for these optimization efforts has been the M2.4-7A configuration which represents an arrow-wing technology for the High-Speed Civil Transport (HSCT). Optimization work on this configuration began in early 1994 and continued into 1996. Initial work focused on optimization of the wing camber and twist on a wing/body configuration and reductions of 3.5 drag counts (Euler) were realized. The next phase of the optimization effort included fuselage camber along with the wing and a drag reduction of 5.0 counts was achieved. Including the effects of the nacelles and diverters into the optimization problem became the next focus where a reduction of 6.6 counts (Euler W/B/N/D) was eventually realized. The final two phases of the effort included a large set of constraints designed to make the final optimized configuration more realistic and they were successful albeit with a loss of performance.

Design optimization of rear uprights for UniMAP Automotive Racing Team Formula SAE racing car

NASA Astrophysics Data System (ADS)

Azmeer, M.; Basha, M. H.; Hamid, M. F.; Rahman, M. T. A.; Hashim, M. S. M.

2017-10-01

In an automobile, the rear upright are used to provide a physical mounting and links the suspension arms to the hub and wheel assembly. In this work, static structural and shape optimization analysis for rear upright for UniMAP’s Formula SAE racing car had been done using ANSYS software with the objective to reduce weight while maintaining the structural strength of the vehicle upright. During the shape optimization process, the component undergoes 25%, 50% and 75 % weight reduction in order to find the best optimal shape of the upright. The final design of the upright is developed considering the weight reduction, structural integrity and the manufacturability. The final design achieved 21 % weight reduction and is able to withstand several loads.

Final Report: Pilot Region-Based Optimization Program for Fund-Lead Sites, EPA Region III

EPA Pesticide Factsheets

This report describes a pilot study for a Region-based optimization program, implemented by a Regional Optimization Evaluation Team (ROET) that was conducted in U.S. EPA Region III at Fund-lead sites with pump-and-treat (P&T) systems.

Design of helicopter rotor blades for optimum dynamic characteristics

NASA Technical Reports Server (NTRS)

Peters, D. A.; Ko, T.; Korn, A.; Rossow, M. P.

1984-01-01

The optimal design of helicopter rotor blades is addressed. The forced response of an initial (i.e., non-optimized) blade to those of a final (optimized) blade are compared. Response of starting design and optimal designs for varying forcing frequencies, blade response to harmonics of rotor speed, and derivation of mass and stiffness matrices or functions of natural frequencies are discussed.

Surface Roughness Optimization Using Taguchi Method of High Speed End Milling For Hardened Steel D2

NASA Astrophysics Data System (ADS)

Hazza Faizi Al-Hazza, Muataz; Ibrahim, Nur Asmawiyah bt; Adesta, Erry T. Y.; Khan, Ahsan Ali; Abdullah Sidek, Atiah Bt.

2017-03-01

The main challenge for any manufacturer is to achieve higher quality of their final products with maintains minimum machining time. In this research final surface roughness analysed and optimized with maximum 0.3 mm flank wear length. The experiment was investigated the effect of cutting speed, feed rate and depth of cut on the final surface roughness using D2 as a work piece hardened to 52-56 HRC, and coated carbide as cutting tool with higher cutting speed 120-240 mm/min. The experiment has been conducted using L9 design of Taguchi collection. The results have been analysed using JMP software.

Heat Sink Design and Optimization

DTIC Science & Technology

2015-12-01

HEAT SINK DESIGN AND OPTIMIZATION I...REPORT DATE (DD-MM-YYYY) December 2015 2. REPORT TYPE Final 3. DATES COVERED (From – To) 4. TITLE AND SUBTITLE HEAT SINK DESIGN AND OPTIMIZATION...distribution is unlimited. 13. SUPPLEMENTARY NOTES 14. ABSTRACT Heat sinks are devices that are used to enhance heat dissipation

LDRD Final Report: Global Optimization for Engineering Science Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.

Processing and plating helical metallic coils

NASA Technical Reports Server (NTRS)

1972-01-01

The results of research efforts to develop an optimized nickel cobalt coating suitable as a recording medium are outlined. The coating is to be used directly on a BeCu helical coil substrate of a helical coil NASA recorder. Specifically, efforts were made to: optimize the coating thickness; establish processes and techniques adaptable for the production of finalized plated helical coils; design and fabricate the equipment required for production and testing of the coils; and deliver finalized helical coils to NASA.

Influence of fronts on the spatial distribution of albacore tuna (Thunnus alalunga) in the Northeast Pacific over the past 30 years (1982-2011)

NASA Astrophysics Data System (ADS)

Xu, Yi; Nieto, Karen; Teo, Steven L. H.; McClatchie, Sam; Holmes, John

2017-01-01

The association of albacore tuna distribution with subtropical fronts in the Northeast Pacific was examined on seasonal and interannual scales from 1982 to 2011. Spatial analyses were performed on commercial logbook data from US and Canadian troll and pole-and-line fisheries targeting albacore tuna that were matched with corresponding satellite images from the Advanced Very High Resolution Radiometer (AVHRR). Subtropical fronts were detected by deriving sea surface temperature (SST) gradients on large basin-scales and by using an improved version of the Cayula-Cornillon frontal detection algorithm. Based on our results, we suggest that areas with high albacore catch-per-unit-effort (CPUE) tend to occur in regions with high SST gradients, such as the North Pacific Transition Zone (NPTZ) and the North American coast. Approaching the North American coast along the NPTZ, SST gradients drop off substantially around 130°W before increasing rapidly near the coast, which corresponded to a similar pattern in albacore CPUE. In the NPTZ, the centroid of albacore CPUE showed a seasonal shift northwards in summer and southwards in fall, which coincided with seasonal spatial shifts of areas with high SST gradients. A similar pattern was found on an interannual scale, with the exception of several years with limited fishery data in the NPTZ due to changes in fishery operations. A fine-scale analysis of frontal locations suggested that areas with high albacore CPUE are associated with oceanic fronts, with the highest albacore CPUEs observed within 100 km of the nearest front. In addition, albacore distribution is related to frontal strength, with the highest CPUE found near fronts with high SST gradient values in the range of 0.12-0.16 °C km-1. Integrating our findings on the influence of frontal areas on albacore distribution and abundance in the NEPO should improve the standardization model used to derive abundance indices for North Pacific albacore stock assessments.

Optimal design of the satellite constellation arrangement reconfiguration process

NASA Astrophysics Data System (ADS)

Fakoor, Mahdi; Bakhtiari, Majid; Soleymani, Mahshid

2016-08-01

In this article, a novel approach is introduced for the satellite constellation reconfiguration based on Lambert's theorem. Some critical problems are raised in reconfiguration phase, such as overall fuel cost minimization, collision avoidance between the satellites on the final orbital pattern, and necessary maneuvers for the satellites in order to be deployed in the desired position on the target constellation. To implement the reconfiguration phase of the satellite constellation arrangement at minimal cost, the hybrid Invasive Weed Optimization/Particle Swarm Optimization (IWO/PSO) algorithm is used to design sub-optimal transfer orbits for the satellites existing in the constellation. Also, the dynamic model of the problem will be modeled in such a way that, optimal assignment of the satellites to the initial and target orbits and optimal orbital transfer are combined in one step. Finally, we claim that our presented idea i.e. coupled non-simultaneous flight of satellites from the initial orbital pattern will lead to minimal cost. The obtained results show that by employing the presented method, the cost of reconfiguration process is reduced obviously.

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Burt, Adam O.; Hull, Patrick V.

2014-01-01

This paper presents a design automation process using optimization via a genetic algorithm to design the conceptual structure of a Lunar Pallet Lander. The goal is to determine a design that will have the primary natural frequencies at or above a target value as well as minimize the total mass. Several iterations of the process are presented. First, a concept optimization is performed to determine what class of structure would produce suitable candidate designs. From this a stiffened sheet metal approach was selected leading to optimization of beam placement through generating a two-dimensional mesh and varying the physical location of reinforcing beams. Finally, the design space is reformulated as a binary problem using 1-dimensional beam elements to truncate the design space to allow faster convergence and additional mechanical failure criteria to be included in the optimization responses. Results are presented for each design space configuration. The final flight design was derived from these results.

Fuel Optimal, Finite Thrust Guidance Methods to Circumnavigate with Lighting Constraints

NASA Astrophysics Data System (ADS)

Prince, E. R.; Carr, R. W.; Cobb, R. G.

This paper details improvements made to the authors' most recent work to find fuel optimal, finite-thrust guidance to inject an inspector satellite into a prescribed natural motion circumnavigation (NMC) orbit about a resident space object (RSO) in geosynchronous orbit (GEO). Better initial guess methodologies are developed for the low-fidelity model nonlinear programming problem (NLP) solver to include using Clohessy- Wiltshire (CW) targeting, a modified particle swarm optimization (PSO), and MATLAB's genetic algorithm (GA). These initial guess solutions may then be fed into the NLP solver as an initial guess, where a different NLP solver, IPOPT, is used. Celestial lighting constraints are taken into account in addition to the sunlight constraint, ensuring that the resulting NMC also adheres to Moon and Earth lighting constraints. The guidance is initially calculated given a fixed final time, and then solutions are also calculated for fixed final times before and after the original fixed final time, allowing mission planners to choose the lowest-cost solution in the resulting range which satisfies all constraints. The developed algorithms provide computationally fast and highly reliable methods for determining fuel optimal guidance for NMC injections while also adhering to multiple lighting constraints.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Efficient dynamic optimization of logic programs

NASA Technical Reports Server (NTRS)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method

NASA Astrophysics Data System (ADS)

Chen, Xiaomin; Wang, Gang

2017-05-01

The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Modelling and kinetics studies of a corn-rape blend combustion in an oxy-fuel atmosphere.

PubMed

López, R; Fernández, C; Martínez, O; Sánchez, M E

2015-05-01

A kinetic oxy-combustion study of a previously optimized lignocellulose blend is proposed. Kinetic and diffusion control mechanism are considered. The proposed correlations fit properly with the experimental results and diffusion effects are identified as be important enough to be taken into account. Afterwards, with the results obtained in the kinetic study, a detailed consecutive and parallel kinetic scheme is proposed for modelling the oxy-combustion of the blend. A discussion of the temperature and concentration profiles are included. Variation of products final distribution is considered. Smaller particles than 0.001 m are proposed for reducing temperature and concentration profiles and obtaining a good final product distribution. CO2-char reaction is identified as one of the most important step to be optimized for obtaining the lowest final residue. In this study, char is mainly oxidised at 950 K and this situation is attributed to an optimized blending of the bioresidues. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sustainability and optimal control of an exploited prey predator system through provision of alternative food to predator.

PubMed

Kar, T K; Ghosh, Bapan

2012-08-01

In the present paper, we develop a simple two species prey-predator model in which the predator is partially coupled with alternative prey. The aim is to study the consequences of providing additional food to the predator as well as the effects of harvesting efforts applied to both the species. It is observed that the provision of alternative food to predator is not always beneficial to the system. A complete picture of the long run dynamics of the system is discussed based on the effort pair as control parameters. Optimal augmentations of prey and predator biomass at final time have been investigated by optimal control theory. Also the short and large time effects of the application of optimal control have been discussed. Finally, some numerical illustrations are given to verify our analytical results with the help of different sets of parameters. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Biologically-Inspired Anisotropic Flexible Wing for Optimal Flapping Flight

DTIC Science & Technology

2013-07-01

AFRL-OSR-VA-TR-2013-0400 Biologically-Inspired, Anisotropic Flexible Wing for Optimal Flapping Flight Luis Bernal, Wei Shyy...Final Report Contract Number: FA9550-07-1-0547 Biologically-Inspired, Anisotropic Flexible Wing for Optimal Flapping Flight University of...minimize power consumption; 2. The interactions of unsteady aerodynamic loading with flexible structures; 3. Flexible , light-weight, multifunctional

Optimization of Biofuel Production From Transgenic Microalgae

DTIC Science & Technology

2013-02-27

AFRL-OSR-VA-TR-2013-0145 OPTIMIZATION OF BIOFUEL PRODUCTION FROM TRANSGENIC MICROALGAE Richard Sayre Donald Danforth...Technical 20080815 to 20120630 OPTIMIZATION OF BIOFUEL PRODUCTION FROM TRANSGENIC MICROALGAE FA9550-08-1-0451 Richard Sayre Donald Danforth Plant...BIOFUEL PRODUCTION FROM TRANSGENIC MICROALGAE Grant/Contract Number: FA9550-08-1-0451 Reporting Period: Final Report Abstract: We have compared the

Optimal perturbations for nonlinear systems using graph-based optimal transport

NASA Astrophysics Data System (ADS)

Grover, Piyush; Elamvazhuthi, Karthik

2018-06-01

We formulate and solve a class of finite-time transport and mixing problems in the set-oriented framework. The aim is to obtain optimal discrete-time perturbations in nonlinear dynamical systems to transport a specified initial measure on the phase space to a final measure in finite time. The measure is propagated under system dynamics in between the perturbations via the associated transfer operator. Each perturbation is described by a deterministic map in the measure space that implements a version of Monge-Kantorovich optimal transport with quadratic cost. Hence, the optimal solution minimizes a sum of quadratic costs on phase space transport due to the perturbations applied at specified times. The action of the transport map is approximated by a continuous pseudo-time flow on a graph, resulting in a tractable convex optimization problem. This problem is solved via state-of-the-art solvers to global optimality. We apply this algorithm to a problem of transport between measures supported on two disjoint almost-invariant sets in a chaotic fluid system, and to a finite-time optimal mixing problem by choosing the final measure to be uniform. In both cases, the optimal perturbations are found to exploit the phase space structures, such as lobe dynamics, leading to efficient global transport. As the time-horizon of the problem is increased, the optimal perturbations become increasingly localized. Hence, by combining the transfer operator approach with ideas from the theory of optimal mass transportation, we obtain a discrete-time graph-based algorithm for optimal transport and mixing in nonlinear systems.

Patterning control strategies for minimum edge placement error in logic devices

NASA Astrophysics Data System (ADS)

Mulkens, Jan; Hanna, Michael; Slachter, Bram; Tel, Wim; Kubis, Michael; Maslow, Mark; Spence, Chris; Timoshkov, Vadim

2017-03-01

In this paper we discuss the edge placement error (EPE) for multi-patterning semiconductor manufacturing. In a multi-patterning scheme the creation of the final pattern is the result of a sequence of lithography and etching steps, and consequently the contour of the final pattern contains error sources of the different process steps. We describe the fidelity of the final pattern in terms of EPE, which is defined as the relative displacement of the edges of two features from their intended target position. We discuss our holistic patterning optimization approach to understand and minimize the EPE of the final pattern. As an experimental test vehicle we use the 7-nm logic device patterning process flow as developed by IMEC. This patterning process is based on Self-Aligned-Quadruple-Patterning (SAQP) using ArF lithography, combined with line cut exposures using EUV lithography. The computational metrology method to determine EPE is explained. It will be shown that ArF to EUV overlay, CDU from the individual process steps, and local CD and placement of the individual pattern features, are the important contributors. Based on the error budget, we developed an optimization strategy for each individual step and for the final pattern. Solutions include overlay and CD metrology based on angle resolved scatterometry, scanner actuator control to enable high order overlay corrections and computational lithography optimization to minimize imaging induced pattern placement errors of devices and metrology targets.

Optimal Control for Quantum Driving of Two-Level Systems

NASA Astrophysics Data System (ADS)

Qi, Xiao-Qiu

2018-01-01

In this paper, the optimal quantum control of two-level systems is studied by the decompositions of SU(2). Using the Pontryagin maximum principle, the minimum time of quantum control is analyzed in detail. The solution scheme of the optimal control function is given in the general case. Finally, two specific cases, which can be applied in many quantum systems, are used to illustrate the scheme, while the corresponding optimal control functions are obtained.

Quality quandaries: Understanding aspects influencing different types of multiple response optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson-Cook, Christine M.; Cao, Yongtao; Lu, Lu

In this study, optimizing with several responses can benefit from an objective approach of eliminating non-contenders, understanding trade-offs between competing responses, and then identifying a final choice that matches optimization priorities. To offer insights that help guide thoughtful decisions, we explore and summarize different patterns of solution sets and their trade-offs for different types of optimization with responses that are to be maximized and/or to achieve a target.

Quality quandaries: Understanding aspects influencing different types of multiple response optimization

DOE PAGES

Anderson-Cook, Christine M.; Cao, Yongtao; Lu, Lu

2016-08-26

In this study, optimizing with several responses can benefit from an objective approach of eliminating non-contenders, understanding trade-offs between competing responses, and then identifying a final choice that matches optimization priorities. To offer insights that help guide thoughtful decisions, we explore and summarize different patterns of solution sets and their trade-offs for different types of optimization with responses that are to be maximized and/or to achieve a target.

A graph decomposition-based approach for water distribution network optimization

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.; Deuerlein, Jochen W.

2013-04-01

A novel optimization approach for water distribution network design is proposed in this paper. Using graph theory algorithms, a full water network is first decomposed into different subnetworks based on the connectivity of the network's components. The original whole network is simplified to a directed augmented tree, in which the subnetworks are substituted by augmented nodes and directed links are created to connect them. Differential evolution (DE) is then employed to optimize each subnetwork based on the sequence specified by the assigned directed links in the augmented tree. Rather than optimizing the original network as a whole, the subnetworks are sequentially optimized by the DE algorithm. A solution choice table is established for each subnetwork (except for the subnetwork that includes a supply node) and the optimal solution of the original whole network is finally obtained by use of the solution choice tables. Furthermore, a preconditioning algorithm is applied to the subnetworks to produce an approximately optimal solution for the original whole network. This solution specifies promising regions for the final optimization algorithm to further optimize the subnetworks. Five water network case studies are used to demonstrate the effectiveness of the proposed optimization method. A standard DE algorithm (SDE) and a genetic algorithm (GA) are applied to each case study without network decomposition to enable a comparison with the proposed method. The results show that the proposed method consistently outperforms the SDE and GA (both with tuned parameters) in terms of both the solution quality and efficiency.

Optimization and management of materials in earthwork construction : final report, April 2010.

DOT National Transportation Integrated Search

2010-04-01

As a result of forensic investigations of problems across Iowa, a research study was developed aimed at providing solutions to identified : problems through better management and optimization of the available pavement geotechnical materials and throu...

Purification optimization for a recombinant single-chain variable fragment against type 1 insulin-like growth factor receptor (IGF-1R) by using design of experiment (DoE).

PubMed

Song, Yong-Hong; Sun, Xue-Wen; Jiang, Bo; Liu, Ji-En; Su, Xian-Hui

2015-12-01

Design of experiment (DoE) is a statistics-based technique for experimental design that could overcome the shortcomings of traditional one-factor-at-a-time (OFAT) approach for protein purification optimization. In this study, a DoE approach was applied for optimizing purification of a recombinant single-chain variable fragment (scFv) against type 1 insulin-like growth factor receptor (IGF-1R) expressed in Escherichia coli. In first capture step using Capto L, a 2-level fractional factorial analysis and successively a central composite circumscribed (CCC) design were used to identify the optimal elution conditions. Two main effects, pH and trehalose, were identified, and high recovery (above 95%) and low aggregates ratio (below 10%) were achieved at the pH range from 2.9 to 3.0 with 32-35% (w/v) trehalose added. In the second step using cation exchange chromatography, an initial screening of media and elution pH and a following CCC design were performed, whereby the optimal selectivity of the scFv was obtained on Capto S at pH near 6.0, and the optimal conditions for fulfilling high DBC and purity were identified as pH range of 5.9-6.1 and loading conductivity range of 5-12.5 mS/cm. Upon a further gel filtration, the final purified scFv with a purity of 98% was obtained. Finally, the optimized conditions were verified by a 20-fold scale-up experiment. The purities and yields of intermediate and final products all fell within the regions predicted by DoE approach, suggesting the robustness of the optimized conditions. We proposed that the DoE approach described here is also applicable in production of other recombinant antibody constructs. Copyright © 2015 Elsevier Inc. All rights reserved.

Simulation Modeling to Compare High-Throughput, Low-Iteration Optimization Strategies for Metabolic Engineering

PubMed Central

Heinsch, Stephen C.; Das, Siba R.; Smanski, Michael J.

2018-01-01

Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems. PMID:29535690

Topology optimized permanent magnet systems

NASA Astrophysics Data System (ADS)

Bjørk, R.; Bahl, C. R. H.; Insinga, A. R.

2017-09-01

Topology optimization of permanent magnet systems consisting of permanent magnets, high permeability iron and air is presented. An implementation of topology optimization for magnetostatics is discussed and three examples are considered. The Halbach cylinder is topology optimized with iron and an increase of 15% in magnetic efficiency is shown. A topology optimized structure to concentrate a homogeneous field is shown to increase the magnitude of the field by 111%. Finally, a permanent magnet with alternating high and low field regions is topology optimized and a Λcool figure of merit of 0.472 is reached, which is an increase of 100% compared to a previous optimized design.

Planning Under Uncertainty: Methods and Applications

DTIC Science & Technology

2010-06-09

begun research into fundamental algorithms for optimization and re?optimization of continuous optimization problems (such as linear and quadratic... algorithm yields a 14.3% improvement over the original design while saving 68.2 % of the simulation evaluations compared to standard sample-path...They provide tools for building and justifying computational algorithms for such problems. Year. 2010 Month: 03 Final Research under this grant

Optimal birth control of age-dependent competitive species

NASA Astrophysics Data System (ADS)

He, Ze-Rong

2005-05-01

We study optimal birth policies for two age-dependent populations in a competing system, which is controlled by fertilities. New results on problems with free final time and integral phase constraints are presented, and the approximate controllability of system is discussed.

Flood frequency analysis using optimization techniques : final report.

DOT National Transportation Integrated Search

1992-10-01

this study consists of three parts. In the first part, a comprehensive investigation was made to find an improved estimation method for the log-Pearson type 3 (LP3) distribution by using optimization techniques. Ninety sets of observed Louisiana floo...

3D highway alignment optimization for Brookeville Bypass : final report.

DOT National Transportation Integrated Search

2005-06-01

This study applies the previously developed Highway Alignment Optimization (HAO) : model to the MD 97 Bypass project in Brookeville, Maryland. The objective of this study is to : demonstrate the applicability of the HAO model to a real highway projec...

Optimization of the Nonradiative Lifetime of Molecular-Beam-Epitaxy (MBE)-Grown Undoped GaAs/AlGaAs Double Heterostructures (DH)

DTIC Science & Technology

2013-09-01

Optimization of the Nonradiative Lifetime of Molecular- Beam-Epitaxy (MBE)-Grown Undoped GaAs/AlGaAs Double Heterostructures (DH) by P...it to the originator. Army Research Laboratory Adelphi, MD 20783-1197 ARL-TR-6660 September 2013 Optimization of the Nonradiative ...REPORT TYPE Final 3. DATES COVERED (From - To) FY2013 4. TITLE AND SUBTITLE Optimization of the Nonradiative Lifetime of Molecular-Beam-Epitaxy

Optimal transfers between unstable periodic orbits using invariant manifolds

NASA Astrophysics Data System (ADS)

Davis, Kathryn E.; Anderson, Rodney L.; Scheeres, Daniel J.; Born, George H.

2011-03-01

This paper presents a method to construct optimal transfers between unstable periodic orbits of differing energies using invariant manifolds. The transfers constructed in this method asymptotically depart the initial orbit on a trajectory contained within the unstable manifold of the initial orbit and later, asymptotically arrive at the final orbit on a trajectory contained within the stable manifold of the final orbit. Primer vector theory is applied to a transfer to determine the optimal maneuvers required to create the bridging trajectory that connects the unstable and stable manifold trajectories. Transfers are constructed between unstable periodic orbits in the Sun-Earth, Earth-Moon, and Jupiter-Europa three-body systems. Multiple solutions are found between the same initial and final orbits, where certain solutions retrace interior portions of the trajectory. All transfers created satisfy the conditions for optimality. The costs of transfers constructed using manifolds are compared to the costs of transfers constructed without the use of manifolds. In all cases, the total cost of the transfer is significantly lower when invariant manifolds are used in the transfer construction. In many cases, the transfers that employ invariant manifolds are three times more efficient, in terms of fuel expenditure, than the transfer that do not. The decrease in transfer cost is accompanied by an increase in transfer time of flight.

Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

PubMed

Heydari, Ali; Balakrishnan, Sivasubramanya N

2013-01-01

To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.

L^1 -optimality conditions for the circular restricted three-body problem

NASA Astrophysics Data System (ADS)

Chen, Zheng

2016-11-01

In this paper, the L^1 -minimization for the translational motion of a spacecraft in the circular restricted three-body problem (CRTBP) is considered. Necessary conditions are derived by using the Pontryagin Maximum Principle (PMP), revealing the existence of bang-bang and singular controls. Singular extremals are analyzed, recalling the existence of the Fuller phenomenon according to the theories developed in (Marchal in J Optim Theory Appl 11(5):441-486, 1973; Zelikin and Borisov in Theory of Chattering Control with Applications to Astronautics, Robotics, Economics, and Engineering. Birkhäuser, Basal 1994; in J Math Sci 114(3):1227-1344, 2003). The sufficient optimality conditions for the L^1 -minimization problem with fixed endpoints have been developed in (Chen et al. in SIAM J Control Optim 54(3):1245-1265, 2016). In the current paper, we establish second-order conditions for optimal control problems with more general final conditions defined by a smooth submanifold target. In addition, the numerical implementation to check these optimality conditions is given. Finally, approximating the Earth-Moon-Spacecraft system by the CRTBP, an L^1 -minimization trajectory for the translational motion of a spacecraft is computed by combining a shooting method with a continuation method in (Caillau et al. in Celest Mech Dyn Astron 114:137-150, 2012; Caillau and Daoud in SIAM J Control Optim 50(6):3178-3202, 2012). The local optimality of the computed trajectory is asserted thanks to the second-order optimality conditions developed.

Functional and Structural Optimality in Plant Growth: A Crop Modelling Case Study

NASA Astrophysics Data System (ADS)

Caldararu, S.; Purves, D. W.; Smith, M. J.

2014-12-01

Simple mechanistic models of vegetation processes are essential both to our understanding of plant behaviour and to our ability to predict future changes in vegetation. One concept that can take us closer to such models is that of plant optimality, the hypothesis that plants aim to achieve an optimal state. Conceptually, plant optimality can be either structural or functional optimality. A structural constraint would mean that plants aim to achieve a certain structural characteristic such as an allometric relationship or nutrient content that allows optimal function. A functional condition refers to plants achieving optimal functionality, in most cases by maximising carbon gain. Functional optimality conditions are applied on shorter time scales and lead to higher plasticity, making plants more adaptable to changes in their environment. In contrast, structural constraints are optimal given the specific environmental conditions that plants are adapted to and offer less flexibility. We exemplify these concepts using a simple model of crop growth. The model represents annual cycles of growth from sowing date to harvest, including both vegetative and reproductive growth and phenology. Structural constraints to growth are represented as an optimal C:N ratio in all plant organs, which drives allocation throughout the vegetative growing stage. Reproductive phenology - i.e. the onset of flowering and grain filling - is determined by a functional optimality condition in the form of maximising final seed mass, so that vegetative growth stops when the plant reaches maximum nitrogen or carbon uptake. We investigate the plants' response to variations in environmental conditions within these two optimality constraints and show that final yield is most affected by changes during vegetative growth which affect the structural constraint.

Technical report on prototype intelligent network flow optimization (INFLO) dynamic speed harmonization and queue warning.

DOT National Transportation Integrated Search

2015-06-01

This Technical Report on Prototype Intelligent Network Flow Optimization (INFLO) Dynamic Speed Harmonization and Queue Warning is the final report for the project. It describes the prototyping, acceptance testing and small-scale demonstration of the ...

Investigation of optimize graded concrete for Oklahoma : phase 1 : final report.

DOT National Transportation Integrated Search

2013-10-01

Optimized Graded Concrete has been a subject widely discussed through the history of concrete. Since aggregates make up over 70% of the volume in a mixture, gradation is critical to the strength, workability, and durability of concrete. In practice o...

A Kind of Nonlinear Programming Problem Based on Mixed Fuzzy Relation Equations Constraints

NASA Astrophysics Data System (ADS)

Li, Jinquan; Feng, Shuang; Mi, Honghai

In this work, a kind of nonlinear programming problem with non-differential objective function and under the constraints expressed by a system of mixed fuzzy relation equations is investigated. First, some properties of this kind of optimization problem are obtained. Then, a polynomial-time algorithm for this kind of optimization problem is proposed based on these properties. Furthermore, we show that this algorithm is optimal for the considered optimization problem in this paper. Finally, numerical examples are provided to illustrate our algorithms.

Self-adaptive multimethod optimization applied to a tailored heating forging process

NASA Astrophysics Data System (ADS)

Baldan, M.; Steinberg, T.; Baake, E.

2018-05-01

The presented paper describes an innovative self-adaptive multi-objective optimization code. Investigation goals concern proving the superiority of this code compared to NGSA-II and applying it to an inductor’s design case study addressed to a “tailored” heating forging application. The choice of the frequency and the heating time are followed by the determination of the turns number and their positions. Finally, a straightforward optimization is performed in order to minimize energy consumption using “optimal control”.

Ant colony system algorithm for the optimization of beer fermentation control.

PubMed

Xiao, Jie; Zhou, Ze-Kui; Zhang, Guang-Xin

2004-12-01

Beer fermentation is a dynamic process that must be guided along a temperature profile to obtain the desired results. Ant colony system algorithm was applied to optimize the kinetic model of this process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture were constructed. An optimal one was chosen at last. Optimal temperature profile maximized the final ethanol production and minimized the byproducts concentration and spoilage risk. The satisfactory results obtained did not require much computation effort.

Transaction fees and optimal rebalancing in the growth-optimal portfolio

NASA Astrophysics Data System (ADS)

Feng, Yu; Medo, Matúš; Zhang, Liang; Zhang, Yi-Cheng

2011-05-01

The growth-optimal portfolio optimization strategy pioneered by Kelly is based on constant portfolio rebalancing which makes it sensitive to transaction fees. We examine the effect of fees on an example of a risky asset with a binary return distribution and show that the fees may give rise to an optimal period of portfolio rebalancing. The optimal period is found analytically in the case of lognormal returns. This result is consequently generalized and numerically verified for broad return distributions and returns generated by a GARCH process. Finally we study the case when investment is rebalanced only partially and show that this strategy can improve the investment long-term growth rate more than optimization of the rebalancing period.

Optimization of spin-torque switching using AC and DC pulses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunn, Tom; Kamenev, Alex; Fine Theoretical Physics Institute, University of Minnesota, Minneapolis, Minnesota 55455

2014-06-21

We explore spin-torque induced magnetic reversal in magnetic tunnel junctions using combined AC and DC spin-current pulses. We calculate the optimal pulse times and current strengths for both AC and DC pulses as well as the optimal AC signal frequency, needed to minimize the Joule heat lost during the switching process. The results of this optimization are compared against numeric simulations. Finally, we show how this optimization leads to different dynamic regimes, where switching is optimized by either a purely AC or DC spin-current, or a combination AC/DC spin-current, depending on the anisotropy energies and the spin-current polarization.

Methodology of shell structure reinforcement layout optimization

NASA Astrophysics Data System (ADS)

Szafrański, Tomasz; Małachowski, Jerzy; Damaziak, Krzysztof

2018-01-01

This paper presents an optimization process of a reinforced shell diffuser intended for a small wind turbine (rated power of 3 kW). The diffuser structure consists of multiple reinforcement and metal skin. This kind of structure is suitable for optimization in terms of selection of reinforcement density, stringers cross sections, sheet thickness, etc. The optimisation approach assumes the reduction of the amount of work to be done between the optimization process and the final product design. The proposed optimization methodology is based on application of a genetic algorithm to generate the optimal reinforcement layout. The obtained results are the basis for modifying the existing Small Wind Turbine (SWT) design.

Algorithm optimization for multitined radiofrequency ablation: comparative study in ex vivo and in vivo bovine liver.

PubMed

Appelbaum, Liat; Sosna, Jacob; Pearson, Robert; Perez, Sarah; Nissenbaum, Yizhak; Mertyna, Pawel; Libson, Eugene; Goldberg, S Nahum

2010-02-01

To prospectively optimize multistep algorithms for largest available multitined radiofrequency (RF) electrode system in ex vivo and in vivo tissues, to determine best energy parameters to achieve large predictable target sizes of coagulation, and to compare these algorithms with manufacturer's recommended algorithms. Institutional animal care and use committee approval was obtained for the in vivo portion of this study. Ablation (n = 473) was performed in ex vivo bovine liver; final tine extension was 5-7 cm. Variables in stepped-deployment RF algorithm were interrogated and included initial current ramping to 105 degrees C (1 degrees C/0.5-5.0 sec), the number of sequential tine extensions (2-7 cm), and duration of application (4-12 minutes) for final two to three tine extensions. Optimal parameters to achieve 5-7 cm of coagulation were compared with recommended algorithms. Optimal settings for 5- and 6-cm final tine extensions were confirmed in in vivo perfused bovine liver (n = 14). Multivariate analysis of variance and/or paired t tests were used. Mean RF ablation zones of 5.1 cm +/- 0.2 (standard deviation), 6.3 cm +/- 0.4, and 7 cm +/- 0.3 were achieved with 5-, 6-, and 7-cm final tine extensions in a mean of 19.5 min +/- 0.5, 27.9 min +/- 6, and 37.1 min +/- 2.3, respectively, at optimal settings. With these algorithms, size of ablation at 6- and 7-cm tine extension significantly increased from mean of 5.4 cm +/- 0.4 and 6.1 cm +/- 0.6 (manufacturer's algorithms) (P <.05, both comparisons); two recommended tine extensions were eliminated. In vivo confirmation produced mean diameter in specified time: 5.5 cm +/- 0.4 in 18.5 min +/- 0.5 (5-cm extensions) and 5.7 cm +/- 0.2 in 21.2 min +/- 0.6 (6-cm extensions). Large zones of coagulation of 5-7 cm can be created with optimized RF algorithms that help reduce number of tine extensions compared with manufacturer's recommendations. Such algorithms are likely to facilitate the utility of these devices for RF ablation of focal tumors in clinical practice. (c) RSNA, 2010.

Freight Advanced Traveler Information System (FRATIS) – Dallas-Fort Worth (DFW) prototype : final report.

DOT National Transportation Integrated Search

2015-05-01

This is the Final Report for the FRATIS Dallas-Fort Worth DFW prototype system. The FRATIS prototype in DFW consisted of the following components: optimization algorithm, terminal wait time, route specific navigation/traffic/weather, and advanced not...

Taking Stock of Unrealistic Optimism.

PubMed

Shepperd, James A; Klein, William M P; Waters, Erika A; Weinstein, Neil D

2013-07-01

Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type-the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention.

Smoothing optimization of supporting quadratic surfaces with Zernike polynomials

NASA Astrophysics Data System (ADS)

Zhang, Hang; Lu, Jiandong; Liu, Rui; Ma, Peifu

2018-03-01

A new optimization method to get a smooth freeform optical surface from an initial surface generated by the supporting quadratic method (SQM) is proposed. To smooth the initial surface, a 9-vertex system from the neighbor quadratic surface and the Zernike polynomials are employed to establish a linear equation system. A local optimized surface to the 9-vertex system can be build by solving the equations. Finally, a continuous smooth optimization surface is constructed by stitching the above algorithm on the whole initial surface. The spot corresponding to the optimized surface is no longer discrete pixels but a continuous distribution.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Lee, Charles H.; Cheung, Kar-Ming

2012-01-01

In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.

Tailoring the Crystal Structure Toward Optimal Super Conductors

DTIC Science & Technology

2016-06-23

AFRL-AFOSR-VA-TR-2016-0210 TAILORING THE CRYSTAL STRUCTURE TOWARD OPTIMAL SUPERCONDUCTORS Emilia Morosan WILLIAM MARSH RICE UNIV HOUSTON TX Final...TAILORING THE CRYSTAL STRUCTURE TOWARD OPTIMAL SUPERCONDUCTORS 5a. CONTRACT NUMBER FA9550-11-1-0023 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...studied the properties of layered transition metal compounds in search of unconventional superconductors . The aim is to identify ground states competing

Application of optimal control theory to the design of the NASA/JPL 70-meter antenna servos

NASA Technical Reports Server (NTRS)

Alvarez, L. S.; Nickerson, J.

1989-01-01

The application of Linear Quadratic Gaussian (LQG) techniques to the design of the 70-m axis servos is described. Linear quadratic optimal control and Kalman filter theory are reviewed, and model development and verification are discussed. Families of optimal controller and Kalman filter gain vectors were generated by varying weight parameters. Performance specifications were used to select final gain vectors.

Thermal Preference of Juvenile Dover Sole (Solea solea) in Relation to Thermal Acclimation and Optimal Growth Temperature

PubMed Central

Schram, Edward; Bierman, Stijn; Teal, Lorna R.; Haenen, Olga; van de Vis, Hans; Rijnsdorp, Adriaan D.

2013-01-01

Dover sole (Solea solea) is an obligate ectotherm with a natural thermal habitat ranging from approximately 5 to 27°C. Thermal optima for growth lie in the range of 20 to 25°C. More precise information on thermal optima for growth is needed for cost-effective Dover sole aquaculture. The main objective of this study was to determine the optimal growth temperature of juvenile Dover sole (Solea solea) and in addition to test the hypothesis that the final preferendum equals the optimal growth temperature. Temperature preference was measured in a circular preference chamber for Dover sole acclimated to 18, 22 and 28°C. Optimal growth temperature was measured by rearing Dover sole at 19, 22, 25 and 28°C. The optimal growth temperature resulting from this growth experiment was 22.7°C for Dover sole with a size between 30 to 50 g. The temperature preferred by juvenile Dover sole increases with acclimation temperature and exceeds the optimal temperature for growth. A final preferendum could not be detected. Although a confounding effect of behavioural fever on temperature preference could not be entirely excluded, thermal preference and thermal optima for physiological processes seem to be unrelated in Dover sole. PMID:23613837

Thermal preference of juvenile Dover sole (Solea solea) in relation to thermal acclimation and optimal growth temperature.

PubMed

Schram, Edward; Bierman, Stijn; Teal, Lorna R; Haenen, Olga; van de Vis, Hans; Rijnsdorp, Adriaan D

2013-01-01

Dover sole (Solea solea) is an obligate ectotherm with a natural thermal habitat ranging from approximately 5 to 27°C. Thermal optima for growth lie in the range of 20 to 25°C. More precise information on thermal optima for growth is needed for cost-effective Dover sole aquaculture. The main objective of this study was to determine the optimal growth temperature of juvenile Dover sole (Solea solea) and in addition to test the hypothesis that the final preferendum equals the optimal growth temperature. Temperature preference was measured in a circular preference chamber for Dover sole acclimated to 18, 22 and 28°C. Optimal growth temperature was measured by rearing Dover sole at 19, 22, 25 and 28°C. The optimal growth temperature resulting from this growth experiment was 22.7°C for Dover sole with a size between 30 to 50 g. The temperature preferred by juvenile Dover sole increases with acclimation temperature and exceeds the optimal temperature for growth. A final preferendum could not be detected. Although a confounding effect of behavioural fever on temperature preference could not be entirely excluded, thermal preference and thermal optima for physiological processes seem to be unrelated in Dover sole.

Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs: An Inverse Optimal Approach.

PubMed

Zhang, Huaguang; Feng, Tao; Yang, Guang-Hong; Liang, Hongjing

2015-07-01

In this paper, the inverse optimal approach is employed to design distributed consensus protocols that guarantee consensus and global optimality with respect to some quadratic performance indexes for identical linear systems on a directed graph. The inverse optimal theory is developed by introducing the notion of partial stability. As a result, the necessary and sufficient conditions for inverse optimality are proposed. By means of the developed inverse optimal theory, the necessary and sufficient conditions are established for globally optimal cooperative control problems on directed graphs. Basic optimal cooperative design procedures are given based on asymptotic properties of the resulting optimal distributed consensus protocols, and the multiagent systems can reach desired consensus performance (convergence rate and damping rate) asymptotically. Finally, two examples are given to illustrate the effectiveness of the proposed methods.

New Multi-objective Uncertainty-based Algorithm for Water Resource Models' Calibration

NASA Astrophysics Data System (ADS)

Keshavarz, Kasra; Alizadeh, Hossein

2017-04-01

Water resource models are powerful tools to support water management decision making process and are developed to deal with a broad range of issues including land use and climate change impacts analysis, water allocation, systems design and operation, waste load control and allocation, etc. These models are divided into two categories of simulation and optimization models whose calibration has been addressed in the literature where great relevant efforts in recent decades have led to two main categories of auto-calibration methods of uncertainty-based algorithms such as GLUE, MCMC and PEST and optimization-based algorithms including single-objective optimization such as SCE-UA and multi-objective optimization such as MOCOM-UA and MOSCEM-UA. Although algorithms which benefit from capabilities of both types, such as SUFI-2, were rather developed, this paper proposes a new auto-calibration algorithm which is capable of both finding optimal parameters values regarding multiple objectives like optimization-based algorithms and providing interval estimations of parameters like uncertainty-based algorithms. The algorithm is actually developed to improve quality of SUFI-2 results. Based on a single-objective, e.g. NSE and RMSE, SUFI-2 proposes a routine to find the best point and interval estimation of parameters and corresponding prediction intervals (95 PPU) of time series of interest. To assess the goodness of calibration, final results are presented using two uncertainty measures of p-factor quantifying percentage of observations covered by 95PPU and r-factor quantifying degree of uncertainty, and the analyst has to select the point and interval estimation of parameters which are actually non-dominated regarding both of the uncertainty measures. Based on the described properties of SUFI-2, two important questions are raised, answering of which are our research motivation: Given that in SUFI-2, final selection is based on the two measures or objectives and on the other hand, knowing that there is no multi-objective optimization mechanism in SUFI-2, are the final estimations Pareto-optimal? Can systematic methods be applied to select the final estimations? Dealing with these questions, a new auto-calibration algorithm was proposed where the uncertainty measures were considered as two objectives to find non-dominated interval estimations of parameters by means of coupling Monte Carlo simulation and Multi-Objective Particle Swarm Optimization. Both the proposed algorithm and SUFI-2 were applied to calibrate parameters of water resources planning model of Helleh river basin, Iran. The model is a comprehensive water quantity-quality model developed in the previous researches using WEAP software in order to analyze the impacts of different water resources management strategies including dam construction, increasing cultivation area, utilization of more efficient irrigation technologies, changing crop pattern, etc. Comparing the Pareto frontier resulted from the proposed auto-calibration algorithm with SUFI-2 results, it was revealed that the new algorithm leads to a better and also continuous Pareto frontier, even though it is more computationally expensive. Finally, Nash and Kalai-Smorodinsky bargaining methods were used to choose compromised interval estimation regarding Pareto frontier.

Final findings on the development and evaluation of an en-route fuel optimal conflict resolution algorithm to support strategic decision-making.

DOT National Transportation Integrated Search

2012-01-01

The novel strategic conflict-resolution algorithm for fuel minimization that is documented in this report : provides air traffic controllers and/or pilots with fuel-optimal heading, speed, and altitude : recommendations in the en route flight phase, ...

Software Partitioning Schemes for Advanced Simulation Computer Systems. Final Report.

ERIC Educational Resources Information Center

Clymer, S. J.

Conducted to design software partitioning techniques for use by the Air Force to partition a large flight simulator program for optimal execution on alternative configurations, this study resulted in a mathematical model which defines characteristics for an optimal partition, and a manually demonstrated partitioning algorithm design which…

An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics

NASA Technical Reports Server (NTRS)

Baluja, Shumeet

1995-01-01

This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.

The Topology Optimization Design Research for Aluminum Inner Panel of Automobile Engine Hood

NASA Astrophysics Data System (ADS)

Li, Minhao; Hu, Dongqing; Liu, Xiangzheng; Yuan, Huanquan

2017-11-01

This article discusses the topology optimization methods for automobile engine hood design. The aluminum inner panel of engine hood and mucilage glue regions are set as design areas, and the static performances of engine hood included modal frequency, lateral stiffness, torsional stiffness and indentation stiffness are set as the optimization objectives. The topology optimization results about different objective functions are contrasted for analysis. And based on the reasonable topology optimization result, a suited automobile engine hood designs are raised to further study. Finally, an automobile engine hood that good at all of static performances is designed, and a favorable topology optimization method is put forward for discussion.

Performance optimization of the power user electric energy data acquire system based on MOEA/D evolutionary algorithm

NASA Astrophysics Data System (ADS)

Ding, Zhongan; Gao, Chen; Yan, Shengteng; Yang, Canrong

2017-10-01

The power user electric energy data acquire system (PUEEDAS) is an important part of smart grid. This paper builds a multi-objective optimization model for the performance of the PUEEADS from the point of view of the combination of the comprehensive benefits and cost. Meanwhile, the Chebyshev decomposition approach is used to decompose the multi-objective optimization problem. We design a MOEA/D evolutionary algorithm to solve the problem. By analyzing the Pareto optimal solution set of multi-objective optimization problem and comparing it with the monitoring value to grasp the direction of optimizing the performance of the PUEEDAS. Finally, an example is designed for specific analysis.

A Review of Industrial Heat Exchange Optimization

NASA Astrophysics Data System (ADS)

Yao, Junjie

2018-01-01

Heat exchanger is an energy exchange equipment, it transfers the heat from a working medium to another working medium, which has been wildly used in petrochemical industry, HVAC refrigeration, aerospace and so many other fields. The optimal design and efficient operation of the heat exchanger and heat transfer network are of great significance to the process industry to realize energy conservation, production cost reduction and energy consumption reduction. In this paper, the optimization of heat exchanger, optimal algorithm and heat exchanger optimization with different objective functions are discussed. Then, optimization of the heat exchanger and the heat exchanger network considering different conditions are compared and analysed. Finally, all the problems discussed are summarized and foresights are proposed.

Geometric versus numerical optimal control of a dissipative spin-(1/2) particle

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lapert, M.; Sugny, D.; Zhang, Y.

2010-12-15

We analyze the saturation of a nuclear magnetic resonance (NMR) signal using optimal magnetic fields. We consider both the problems of minimizing the duration of the control and its energy for a fixed duration. We solve the optimal control problems by using geometric methods and a purely numerical approach, the grape algorithm, the two methods being based on the application of the Pontryagin maximum principle. A very good agreement is obtained between the two results. The optimal solutions for the energy-minimization problem are finally implemented experimentally with available NMR techniques.

Optimization of detectors for the ILC

NASA Astrophysics Data System (ADS)

Suehara, Taikan; ILD Group; SID Group

2016-04-01

International Linear Collider (ILC) is a next-generation e+e- linear collider to explore Higgs, Beyond-Standard-Models, top and electroweak particles with great precision. We are optimizing our two detectors, International Large Detector (ILD) and Silicon Detector (SiD) to maximize the physics reach expected in ILC with reasonable detector cost and good reliability. The optimization study on vertex detectors, main trackers and calorimeters is underway. We aim to conclude the optimization to establish final designs in a few years, to finish detector TDR and proposal in reply to expected ;green sign; of the ILC project.

Multi-objective Optimization Design of Gear Reducer Based on Adaptive Genetic Algorithms

NASA Astrophysics Data System (ADS)

Li, Rui; Chang, Tian; Wang, Jianwei; Wei, Xiaopeng; Wang, Jinming

2008-11-01

An adaptive Genetic Algorithm (GA) is introduced to solve the multi-objective optimized design of the reducer. Firstly, according to the structure, strength, etc. in a reducer, a multi-objective optimized model of the helical gear reducer is established. And then an adaptive GA based on a fuzzy controller is introduced, aiming at the characteristics of multi-objective, multi-parameter, multi-constraint conditions. Finally, a numerical example is illustrated to show the advantages of this approach and the effectiveness of an adaptive genetic algorithm used in optimized design of a reducer.

Optimization and guidance of flight trajectories for the national aerospace plane

NASA Technical Reports Server (NTRS)

Miele, Angelo

1990-01-01

The research on optimal trajectories for the National Aerospace Plane (NASP) performed by the Aero-Astronautics Group of Rice University from June 22, 1989 to December 31, 1990 is summarized. The aerospace plane is assumed to be controlled via the angle of attack and the power setting. The time history of the controls is optimized simultaneously with the switch times from one powerplant to another and the final time. The intent is to arrive at NASP guidance trajectories exhibiting many of the desirable characteristics of NASP optimal trajectories.

Taking Stock of Unrealistic Optimism

PubMed Central

Shepperd, James A.; Klein, William M. P.; Waters, Erika A.; Weinstein, Neil D.

2015-01-01

Researchers have used terms such as unrealistic optimism and optimistic bias to refer to concepts that are similar but not synonymous. Drawing from three decades of research, we critically discuss how researchers define unrealistic optimism and we identify four types that reflect different measurement approaches: unrealistic absolute optimism at the individual and group level and unrealistic comparative optimism at the individual and group level. In addition, we discuss methodological criticisms leveled against research on unrealistic optimism and note that the criticisms are primarily relevant to only one type—the group form of unrealistic comparative optimism. We further clarify how the criticisms are not nearly as problematic even for unrealistic comparative optimism as they might seem. Finally, we note boundary conditions on the different types of unrealistic optimism and reflect on five broad questions that deserve further attention. PMID:26045714

Firefly Algorithm, Lévy Flights and Global Optimization

NASA Astrophysics Data System (ADS)

Yang, Xin-She

Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Lévy flights with the search strategy via the Firefly Algorithm. Numerical studies and results suggest that the proposed Lévy-flight firefly algorithm is superior to existing metaheuristic algorithms. Finally implications for further research and wider applications will be discussed.

Performance index and meta-optimization of a direct search optimization method

NASA Astrophysics Data System (ADS)

Krus, P.; Ölvander, J.

2013-10-01

Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannon's information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.

Optimal cost design of water distribution networks using a decomposition approach

NASA Astrophysics Data System (ADS)

Lee, Ho Min; Yoo, Do Guen; Sadollah, Ali; Kim, Joong Hoon

2016-12-01

Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

Optimizing Dynamical Network Structure for Pinning Control

NASA Astrophysics Data System (ADS)

Orouskhani, Yasin; Jalili, Mahdi; Yu, Xinghuo

2016-04-01

Controlling dynamics of a network from any initial state to a final desired state has many applications in different disciplines from engineering to biology and social sciences. In this work, we optimize the network structure for pinning control. The problem is formulated as four optimization tasks: i) optimizing the locations of driver nodes, ii) optimizing the feedback gains, iii) optimizing simultaneously the locations of driver nodes and feedback gains, and iv) optimizing the connection weights. A newly developed population-based optimization technique (cat swarm optimization) is used as the optimization method. In order to verify the methods, we use both real-world networks, and model scale-free and small-world networks. Extensive simulation results show that the optimal placement of driver nodes significantly outperforms heuristic methods including placing drivers based on various centrality measures (degree, betweenness, closeness and clustering coefficient). The pinning controllability is further improved by optimizing the feedback gains. We also show that one can significantly improve the controllability by optimizing the connection weights.

Optimization of Magnet Arrangement in Double-Layer Interior Permanent-Magnet Motors

NASA Astrophysics Data System (ADS)

Yamazaki, Katsumi; Kitayuguchi, Kazuya

The arrangement of permanent magnets in double-layer interior permanent-magnet motors is optimized for variable-speed applications. First, the arrangement of magnets is decided by automatic optimization. Next, the superiority of the optimized motor is discussed by the d- and q-axis equivalent circuits that consider the magnetic saturation of the rotor core. Finally, experimental verification is carried out by using a prototype motor. It is confirmed that the maximum torque of the optimized motor under both low speed and high speed conditions are higher than those of conventional motors because of relatively large q-axis inductance and small d-axis inductance.

Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

NASA Astrophysics Data System (ADS)

Chen, Wei

2015-07-01

In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

Modified harmony search

NASA Astrophysics Data System (ADS)

Mohamed, Najihah; Lutfi Amri Ramli, Ahmad; Majid, Ahmad Abd; Piah, Abd Rahni Mt

2017-09-01

A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. HS is a derivative-free real parameter optimization algorithm, and draws an inspiration from the musical improvisation process of searching for a perfect state of harmony. Propose in this paper Modified Harmony Search for solving optimization problems, which employs a concept from genetic algorithm method and particle swarm optimization for generating new solution vectors that enhances the performance of HS algorithm. The performances of MHS and HS are investigated on ten benchmark optimization problems in order to make a comparison to reflect the efficiency of the MHS in terms of final accuracy, convergence speed and robustness.

Optimization Research of Generation Investment Based on Linear Programming Model

NASA Astrophysics Data System (ADS)

Wu, Juan; Ge, Xueqian

Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.

A general framework for multicharacter segmentation and its application in recognizing multilingual Asian documents

NASA Astrophysics Data System (ADS)

Wen, Di; Ding, Xiaoqing

2003-12-01

In this paper we propose a general framework for character segmentation in complex multilingual documents, which is an endeavor to combine the traditionally separated segmentation and recognition processes into a cooperative system. The framework contains three basic steps: Dissection, Local Optimization and Global Optimization, which are designed to fuse various properties of the segmentation hypotheses hierarchically into a composite evaluation to decide the final recognition results. Experimental results show that this framework is general enough to be applied in variety of documents. A sample system based on this framework to recognize Chinese, Japanese and Korean documents and experimental performance is reported finally.

Naval Postgraduate School Scheduling Support System (NPS4)

DTIC Science & Technology

1992-03-01

NPSS ...... .................. 156 2. Final Exam Scheduler .. .......... 159 F. PRESENTATION SYSTEM ... ............. . 160 G. USER INTERFACE... NPSS ...... .................. 185 2. Final Exam Model ... ............ 186 3. The Class Schedulers .. .......... 186 4. Assessment of Problem Model...Information Distribution ....... 150 4.13 NPSS Optimization Process .... ............ . 157 4.14 NPSS Performance ..... ................ . 159 4.15 Department

Children in Hospitals: A Model Program. Final Report.

ERIC Educational Resources Information Center

Brill, Nancy; Cohen, Sarale

This final report describes the rationale, goals and activities of a federally funded project that was designed to develop a model intervention program for hospitalized chronically ill children between birth and five years. The focus of the program was to promote optimal emotional development: attachment, separation, individualization, and…

Production of footbridge with double curvature made of UHPC

NASA Astrophysics Data System (ADS)

Kolísko, J.; Čítek, D.; Tej, P.; Rydval, M.

2017-09-01

This article present a mix design, preparation and production of thin-walled footbridge made from UHPFRC. In this case an experimental pedestrian bridge was design and prepared. Bridge with span of 10 m and the clear width of 1.50 m designed as single-span bridge. Optimization of UHPFRC matrix and parameters of this material leads to the design of very thin structures. Total thickness of shell structure 30 - 45 mm. Bridge was cast as a prefabricated element in one piece. Self-compacting character of UHPFRC with high flowability allows the production of the final structure. Extensive research was done before production of footbridge. Experimental reached data were compared with extensive numerical analysis and the final design of structure and UHPFRC matrix were optimized in many details. Two versions of large scale mock-ups were casted and tested. According to the complexity of whole experiment a casting technology and production of formwork were tested and optimized many times.

Single-agent parallel window search

NASA Technical Reports Server (NTRS)

Powley, Curt; Korf, Richard E.

1991-01-01

Parallel window search is applied to single-agent problems by having different processes simultaneously perform iterations of Iterative-Deepening-A(asterisk) (IDA-asterisk) on the same problem but with different cost thresholds. This approach is limited by the time to perform the goal iteration. To overcome this disadvantage, the authors consider node ordering. They discuss how global node ordering by minimum h among nodes with equal f = g + h values can reduce the time complexity of serial IDA-asterisk by reducing the time to perform the iterations prior to the goal iteration. Finally, the two ideas of parallel window search and node ordering are combined to eliminate the weaknesses of each approach while retaining the strengths. The resulting approach, called simply parallel window search, can be used to find a near-optimal solution quickly, improve the solution until it is optimal, and then finally guarantee optimality, depending on the amount of time available.

Performance of the Extravehicular Mobility Unit (EMU) Airlock Coolant Loop Remediation (A/L CLR) Hardware - Final

NASA Technical Reports Server (NTRS)

Steele, John W.; Rector, Tony; Gazda, Daniel; Lewis, John

2011-01-01

An EMU water processing kit (Airlock Coolant Loop Recovery -- A/L CLR) was developed as a corrective action to Extravehicular Mobility Unit (EMU) coolant flow disruptions experienced on the International Space Station (ISS) in May of 2004 and thereafter. A conservative duty cycle and set of use parameters for A/L CLR use and component life were initially developed and implemented based on prior analysis results and analytical modeling. Several initiatives were undertaken to optimize the duty cycle and use parameters of the hardware. Examination of post-flight samples and EMU Coolant Loop hardware provided invaluable information on the performance of the A/L CLR and has allowed for an optimization of the process. The intent of this paper is to detail the evolution of the A/L CLR hardware, efforts to optimize the duty cycle and use parameters, and the final recommendations for implementation in the post-Shuttle retirement era.

Optimization of multi-stage dynamic treatment regimes utilizing accumulated data.

PubMed

Huang, Xuelin; Choi, Sangbum; Wang, Lu; Thall, Peter F

2015-11-20

In medical therapies involving multiple stages, a physician's choice of a subject's treatment at each stage depends on the subject's history of previous treatments and outcomes. The sequence of decisions is known as a dynamic treatment regime or treatment policy. We consider dynamic treatment regimes in settings where each subject's final outcome can be defined as the sum of longitudinally observed values, each corresponding to a stage of the regime. Q-learning, which is a backward induction method, is used to first optimize the last stage treatment then sequentially optimize each previous stage treatment until the first stage treatment is optimized. During this process, model-based expectations of outcomes of late stages are used in the optimization of earlier stages. When the outcome models are misspecified, bias can accumulate from stage to stage and become severe, especially when the number of treatment stages is large. We demonstrate that a modification of standard Q-learning can help reduce the accumulated bias. We provide a computational algorithm, estimators, and closed-form variance formulas. Simulation studies show that the modified Q-learning method has a higher probability of identifying the optimal treatment regime even in settings with misspecified models for outcomes. It is applied to identify optimal treatment regimes in a study for advanced prostate cancer and to estimate and compare the final mean rewards of all the possible discrete two-stage treatment sequences. Copyright © 2015 John Wiley & Sons, Ltd.

Tidal Turbine Array Optimization Based on the Discrete Particle Swarm Algorithm

NASA Astrophysics Data System (ADS)

Wu, Guo-wei; Wu, He; Wang, Xiao-yong; Zhou, Qing-wei; Liu, Xiao-man

2018-06-01

In consideration of the resource wasted by unreasonable layout scheme of tidal current turbines, which would influence the ratio of cost and power output, particle swarm optimization algorithm is introduced and improved in the paper. In order to solve the problem of optimal array of tidal turbines, the discrete particle swarm optimization (DPSO) algorithm has been performed by re-defining the updating strategies of particles' velocity and position. This paper analyzes the optimization problem of micrositing of tidal current turbines by adjusting each turbine's position, where the maximum value of total electric power is obtained at the maximum speed in the flood tide and ebb tide. Firstly, the best installed turbine number is generated by maximizing the output energy in the given tidal farm by the Farm/Flux and empirical method. Secondly, considering the wake effect, the reasonable distance between turbines, and the tidal velocities influencing factors in the tidal farm, Jensen wake model and elliptic distribution model are selected for the turbines' total generating capacity calculation at the maximum speed in the flood tide and ebb tide. Finally, the total generating capacity, regarded as objective function, is calculated in the final simulation, thus the DPSO could guide the individuals to the feasible area and optimal position. The results have been concluded that the optimization algorithm, which increased 6.19% more recourse output than experience method, can be thought as a good tool for engineering design of tidal energy demonstration.

Optimal Control Problems with Switching Points. Ph.D. Thesis, 1990 Final Report

NASA Technical Reports Server (NTRS)

Seywald, Hans

1991-01-01

The main idea of this report is to give an overview of the problems and difficulties that arise in solving optimal control problems with switching points. A brief discussion of existing optimality conditions is given and a numerical approach for solving the multipoint boundary value problems associated with the first-order necessary conditions of optimal control is presented. Two real-life aerospace optimization problems are treated explicitly. These are altitude maximization for a sounding rocket (Goddard Problem) in the presence of a dynamic pressure limit, and range maximization for a supersonic aircraft flying in the vertical, also in the presence of a dynamic pressure limit. In the second problem singular control appears along arcs with active dynamic pressure limit, which in the context of optimal control, represents a first-order state inequality constraint. An extension of the Generalized Legendre-Clebsch Condition to the case of singular control along state/control constrained arcs is presented and is applied to the aircraft range maximization problem stated above. A contribution to the field of Jacobi Necessary Conditions is made by giving a new proof for the non-optimality of conjugate paths in the Accessory Minimum Problem. Because of its simple and explicit character, the new proof may provide the basis for an extension of Jacobi's Necessary Condition to the case of the trajectories with interior point constraints. Finally, the result that touch points cannot occur for first-order state inequality constraints is extended to the case of vector valued control functions.

A Portfolio for Optimal Collaboration of Human and Cyber Physical Production Systems in Problem-Solving

ERIC Educational Resources Information Center

Ansari, Fazel; Seidenberg, Ulrich

2016-01-01

This paper discusses the complementarity of human and cyber physical production systems (CPPS). The discourse of complementarity is elaborated by defining five criteria for comparing the characteristics of human and CPPS. Finally, a management portfolio matrix is proposed for examining the feasibility of optimal collaboration between them. The…

Time optimal paths for high speed maneuvering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reister, D.B.; Lenhart, S.M.

1993-01-01

Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature ofmore » the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.« less

Taguchi Method Applied in Optimization of Shipley SJR 5740 Positive Resist Deposition

NASA Technical Reports Server (NTRS)

Hui, A.; Blosiu, J. O.; Wiberg, D. V.

1998-01-01

Taguchi Methods of Robust Design presents a way to optimize output process performance through an organized set of experiments by using orthogonal arrays. Analysis of variance and signal-to-noise ratio is used to evaluate the contribution of each of the process controllable parameters in the realization of the process optimization. In the photoresist deposition process, there are numerous controllable parameters that can affect the surface quality and thickness of the final photoresist layer.

Damage-Survivable and Damage-Tolerant Laminated Composites with Optimally Placed Piezoelectric Layers

DTIC Science & Technology

1992-11-13

AD-A269 879 Damage-Survivable j and Damage-Tolerant Laminated Composites .4.. with Optimally placed Piezoelectric Layers Final Report No. 1 S. P...Damage Surviable and Damage-Tolerant Laminated Composites With Optimally Placed Piezoelectric Layers 12. PERSONAL AUTHOR(S) S.P. Joshi, W.S. Chan ൕa...block number) The main objective of the research is to assure that the embedded sensors/actuators in a smart laminated composite structure are damage

An efficient constraint to account for mistuning effects in the optimal design of engine rotors

NASA Technical Reports Server (NTRS)

Murthy, Durbha V.; Pierre, Christophe; Ottarsson, Gisli

1992-01-01

Blade-to-blade differences in structural properties, unavoidable in practice due to manufacturing tolerances, can have significant influence on the vibratory response of engine rotor blade. Accounting for these differences, also known as mistuning, in design and in optimization procedures is generally not possible. This note presents an easily calculated constraint that can be used in design and optimization procedures to control the sensitivity of final designs to mistuning.

Optimal design of a novel remote center-of-motion mechanism for minimally invasive surgical robot

NASA Astrophysics Data System (ADS)

Sun, Jingyuan; Yan, Zhiyuan; Du, Zhijiang

2017-06-01

Surgical robot with a remote center-of-motion (RCM) plays an important role in minimally invasive surgery (MIS) field. To make the mechanism has high flexibility and meet the demand of movements during processing of operation, an optimized RCM mechanism is proposed in this paper. Then, the kinematic performance and workspace are analyzed. Finally, a new optimization objective function is built by using the condition number index and the workspace index.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reister, D.B.; Pin, F.G.

This paper addresses the problem of time-optional motions for a mobile platform in a planar environment. The platform has two non-steerable independently driven wheels. The overall mission of the robot is expressed in terms of a sequence of via points at which the platform must be at rest in a given configuration (position and orientation). The objective is to plan time-optimal trajectories between these configurations assuming an unobstructed environment. Using Pontryagin's maximum principle (PMP), we formally demonstrate that all time optimal motions of the platform for this problem occur for bang-bang controls on the wheels (at each instant, the accelerationmore » on each wheel is either at its upper or lower limit). The PMP, however, only provides necessary conditions for time optimality. To find the time optimal robot trajectories, we first parameterize the bang-bang trajectories using the switch times on the wheels (the times at which the wheel accelerations change sign). With this parameterization, we can fully search the robot trajectory space and find the switch times that will produce particular paths to a desired final configuration of the platform. We show numerically that robot trajectories with three switch times (two on one wheel, one on the other) can reach any position, while trajectories with four switch times can reach any configuration. By numerical comparison with other trajectories involving similar or greater numbers of switch times, we then identify the sets of time-optimal trajectories. These are uniquely defined using ranges of the parameters, and consist of subsets of trajectories with three switch times for the problem when the final orientation of the robot is not specified, and four switch times when a full final configuration is specified. We conclude with a description of the use of the method for trajectory planning for one of our robots.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reister, D.B.; Pin, F.G.

This paper addresses the problem of time-optional motions for a mobile platform in a planar environment. The platform has two non-steerable independently driven wheels. The overall mission of the robot is expressed in terms of a sequence of via points at which the platform must be at rest in a given configuration (position and orientation). The objective is to plan time-optimal trajectories between these configurations assuming an unobstructed environment. Using Pontryagin`s maximum principle (PMP), we formally demonstrate that all time optimal motions of the platform for this problem occur for bang-bang controls on the wheels (at each instant, the accelerationmore » on each wheel is either at its upper or lower limit). The PMP, however, only provides necessary conditions for time optimality. To find the time optimal robot trajectories, we first parameterize the bang-bang trajectories using the switch times on the wheels (the times at which the wheel accelerations change sign). With this parameterization, we can fully search the robot trajectory space and find the switch times that will produce particular paths to a desired final configuration of the platform. We show numerically that robot trajectories with three switch times (two on one wheel, one on the other) can reach any position, while trajectories with four switch times can reach any configuration. By numerical comparison with other trajectories involving similar or greater numbers of switch times, we then identify the sets of time-optimal trajectories. These are uniquely defined using ranges of the parameters, and consist of subsets of trajectories with three switch times for the problem when the final orientation of the robot is not specified, and four switch times when a full final configuration is specified. We conclude with a description of the use of the method for trajectory planning for one of our robots.« less

Emergency strategy optimization for the environmental control system in manned spacecraft

NASA Astrophysics Data System (ADS)

Li, Guoxiang; Pang, Liping; Liu, Meng; Fang, Yufeng; Zhang, Helin

2018-02-01

It is very important for a manned environmental control system (ECS) to be able to reconfigure its operation strategy in emergency conditions. In this article, a multi-objective optimization is established to design the optimal emergency strategy for an ECS in an insufficient power supply condition. The maximum ECS lifetime and the minimum power consumption are chosen as the optimization objectives. Some adjustable key variables are chosen as the optimization variables, which finally represent the reconfigured emergency strategy. The non-dominated sorting genetic algorithm-II is adopted to solve this multi-objective optimization problem. Optimization processes are conducted at four different carbon dioxide partial pressure control levels. The study results show that the Pareto-optimal frontiers obtained from this multi-objective optimization can represent the relationship between the lifetime and the power consumption of the ECS. Hence, the preferred emergency operation strategy can be recommended for situations when there is suddenly insufficient power.

Optimization of fed-batch enzymatic hydrolysis from alkali-pretreated sugarcane bagasse for high-concentration sugar production.

PubMed

Gao, Yueshu; Xu, Jingliang; Yuan, Zhenhong; Zhang, Yu; Liu, Yunyun; Liang, Cuiyi

2014-09-01

Fed-batch enzymatic hydrolysis process from alkali-pretreated sugarcane bagasse was investigated to increase solids loading, produce high-concentration fermentable sugar and finally to reduce the cost of the production process. The optimal initial solids loading, feeding time and quantities were examined. The hydrolysis system was initiated with 12% (w/v) solids loading in flasks, where 7% fresh solids were fed consecutively at 6h, 12h, 24h to get a final solids loading of 33%. All the requested cellulase loading (10 FPU/g substrate) was added completely at the beginning of hydrolysis reaction. After 120 h of hydrolysis, the maximal concentrations of cellobiose, glucose and xylose obtained were 9.376 g/L, 129.50 g/L, 56.03 g/L, respectively. The final total glucan conversion rate attained to 60% from this fed-batch process. Copyright © 2014. Published by Elsevier Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reister, D.B.; Lenhart, S.M.

Recent theoretical results have completely solved the problem of determining the minimum length path for a vehicle with a minimum turning radius moving from an initial configuration to a final configuration. Time optimal paths for a constant speed vehicle are a subset of the minimum length paths. This paper uses the Pontryagin maximum principle to find time optimal paths for a constant speed vehicle. The time optimal paths consist of sequences of axes of circles and straight lines. The maximum principle introduces concepts (dual variables, bang-bang solutions, singular solutions, and transversality conditions) that provide important insight into the nature ofmore » the time optimal paths. We explore the properties of the optimal paths and present some experimental results for a mobile robot following an optimal path.« less

Two-phase strategy of neural control for planar reaching movements: I. XY coordination variability and its relation to end-point variability.

PubMed

Rand, Miya K; Shimansky, Yury P

2013-03-01

A quantitative model of optimal transport-aperture coordination (TAC) during reach-to-grasp movements has been developed in our previous studies. The utilization of that model for data analysis allowed, for the first time, to examine the phase dependence of the precision demand specified by the CNS for neurocomputational information processing during an ongoing movement. It was shown that the CNS utilizes a two-phase strategy for movement control. That strategy consists of reducing the precision demand for neural computations during the initial phase, which decreases the cost of information processing at the expense of lower extent of control optimality. To successfully grasp the target object, the CNS increases precision demand during the final phase, resulting in higher extent of control optimality. In the present study, we generalized the model of optimal TAC to a model of optimal coordination between X and Y components of point-to-point planar movements (XYC). We investigated whether the CNS uses the two-phase control strategy for controlling those movements, and how the strategy parameters depend on the prescribed movement speed, movement amplitude and the size of the target area. The results indeed revealed a substantial similarity between the CNS's regulation of TAC and XYC. First, the variability of XYC within individual trials was minimal, meaning that execution noise during the movement was insignificant. Second, the inter-trial variability of XYC was considerable during the majority of the movement time, meaning that the precision demand for information processing was lowered, which is characteristic for the initial phase. That variability significantly decreased, indicating higher extent of control optimality, during the shorter final movement phase. The final phase was the longest (shortest) under the most (least) challenging combination of speed and accuracy requirements, fully consistent with the concept of the two-phase control strategy. This paper further discussed the relationship between motor variability and XYC variability.

Universality of optimal measurements

NASA Astrophysics Data System (ADS)

Tarrach, Rolf; Vidal, Guifré

1999-11-01

We present optimal and minimal measurements on identical copies of an unknown state of a quantum bit when the quality of measuring strategies is quantified with the gain of information (Kullback-or mutual information-of probability distributions). We also show that the maximal gain of information occurs, among isotropic priors, when the state is known to be pure. Universality of optimal measurements follows from our results: using the fidelity or the gain of information, two different figures of merits, leads to exactly the same conclusions for isotropic distributions. We finally investigate the optimal capacity of N copies of an unknown state as a quantum channel of information.

Application of Neural Network Optimized by Mind Evolutionary Computation in Building Energy Prediction

NASA Astrophysics Data System (ADS)

Song, Chen; Zhong-Cheng, Wu; Hong, Lv

2018-03-01

Building Energy forecasting plays an important role in energy management and plan. Using mind evolutionary algorithm to find the optimal network weights and threshold, to optimize the BP neural network, can overcome the problem of the BP neural network into a local minimum point. The optimized network is used for time series prediction, and the same month forecast, to get two predictive values. Then two kinds of predictive values are put into neural network, to get the final forecast value. The effectiveness of the method was verified by experiment with the energy value of three buildings in Hefei.

Optimal dynamic pricing for deteriorating items with reference-price effects

NASA Astrophysics Data System (ADS)

Xue, Musen; Tang, Wansheng; Zhang, Jianxiong

2016-07-01

In this paper, a dynamic pricing problem for deteriorating items with the consumers' reference-price effect is studied. An optimal control model is established to maximise the total profit, where the demand not only depends on the current price, but also is sensitive to the historical price. The continuous-time dynamic optimal pricing strategy with reference-price effect is obtained through solving the optimal control model on the basis of Pontryagin's maximum principle. In addition, numerical simulations and sensitivity analysis are carried out. Finally, some managerial suggestions that firm may adopt to formulate its pricing policy are proposed.

Interphase layer optimization for metal matrix composites with fabrication considerations

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, C. C.

1991-01-01

A methodology is presented to reduce the final matrix microstresses for metal matrix composites by concurrently optimizing the interphase characteristics and fabrication process. Application cases include interphase tailoring with and without fabrication considerations for two material systems, graphite/copper and silicon carbide/titanium. Results indicate that concurrent interphase/fabrication optimization produces significant reductions in the matrix residual stresses and strong coupling between interphase and fabrication tailoring. The interphase coefficient of thermal expansion and the fabrication consolidation pressure are the most important design parameters and must be concurrently optimized to further reduce the microstresses to more desirable magnitudes.

Optimizing Nutrient Uptake in Biological Transport Networks

NASA Astrophysics Data System (ADS)

Ronellenfitsch, Henrik; Katifori, Eleni

2013-03-01

Many biological systems employ complex networks of vascular tubes to facilitate transport of solute nutrients, examples include the vascular system of plants (phloem), some fungi, and the slime-mold Physarum. It is believed that such networks are optimized through evolution for carrying out their designated task. We propose a set of hydrodynamic governing equations for solute transport in a complex network, and obtain the optimal network architecture for various classes of optimizing functionals. We finally discuss the topological properties and statistical mechanics of the resulting complex networks, and examine correspondence of the obtained networks to those found in actual biological systems.

Equivalence between entanglement and the optimal fidelity of continuous variable teleportation.

PubMed

Adesso, Gerardo; Illuminati, Fabrizio

2005-10-07

We devise the optimal form of Gaussian resource states enabling continuous-variable teleportation with maximal fidelity. We show that a nonclassical optimal fidelity of N-user teleportation networks is necessary and sufficient for N-party entangled Gaussian resources, yielding an estimator of multipartite entanglement. The entanglement of teleportation is equivalent to the entanglement of formation in a two-user protocol, and to the localizable entanglement in a multiuser one. Finally, we show that the continuous-variable tangle, quantifying entanglement sharing in three-mode Gaussian states, is defined operationally in terms of the optimal fidelity of a tripartite teleportation network.

Further efforts in optimizing nonlinear optical molecules

NASA Astrophysics Data System (ADS)

Dirk, Carl W.; Caballero, Noel; Tan, Alarice; Kuzyk, Mark G.; Cheng, Lap-Tak A.; Katz, Howard E.; Shilling, Marcia; King, Lori A.

1993-02-01

We summarize some of our past work in the field on optimizing molecules for second order and third order nonlinear optical applications. We also present some previously unpublished results suggesting a particular optimization of the popular cyano- and nitrovinyl acceptor groups. In addition we provide some new quadratic electro-optic results which serve to further verify our choice of a restricted three-level model suitable for optimizing third order nonlinearities in molecules. Finally we present a new squarylium dye with a large third order optical nonlinearity (-9.5 X 10-34 cm7/esu2; EFISH (gamma) at 1906 nm).

The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model

NASA Astrophysics Data System (ADS)

Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

2016-05-01

Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.

Discriminating different Z{sup '}'s via asymmetries at the LHC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou Zhongqiu; Xiao Bo; Wang Youkai

2011-05-01

In practice the asymmetry, which is defined based on the angular distribution of the final states in scattering or decay processes, can be utilized to scrutinize underlying dynamics in and/or beyond the standard model (BSM). As one of the possible BSM physics which might be discovered early at the LHC, extra neutral gauge bosons Z{sup '}'s are theoretically well motivated. Once Z{sup '}'s are discovered at the LHC, it is crucial to discriminate different Z{sup '}'s in various BSM. In principle such a task can be accomplished by measuring the angular distribution of the final states which are produced viamore » Z{sup '}-mediated processes. In the real data analysis, asymmetry is always adopted. In the literature several asymmetries have been proposed at the LHC. Based on these works, we stepped further on to study how to optimize the asymmetries in the left-right model and the sequential standard model, as the examples of BSM. In this paper, we examined four kinds of asymmetries, namely, rapidity-dependent forward-backward asymmetry, oneside forward-backward asymmetry, central charge asymmetry, and edge charge asymmetry (see text for details), with l{sup +}l{sup -} (l=e, {mu}), bb, and tt as the final states. In the calculations with bb and tt final states, the QCD-induced higher-order contributions to the asymmetric cross section were also included. For each kind of final state, we estimated the four kinds of asymmetries and especially the optimal cut usually associated with the definition of the asymmetry. Our numerical results indicated that the capacity to discriminate Z{sup '} models can be improved by imposing the optimal cuts.« less

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Techniques for shuttle trajectory optimization

NASA Technical Reports Server (NTRS)

Edge, E. R.; Shieh, C. J.; Powers, W. F.

1973-01-01

The application of recently developed function-space Davidon-type techniques to the shuttle ascent trajectory optimization problem is discussed along with an investigation of the recently developed PRAXIS algorithm for parameter optimization. At the outset of this analysis, the major deficiency of the function-space algorithms was their potential storage problems. Since most previous analyses of the methods were with relatively low-dimension problems, no storage problems were encountered. However, in shuttle trajectory optimization, storage is a problem, and this problem was handled efficiently. Topics discussed include: the shuttle ascent model and the development of the particular optimization equations; the function-space algorithms; the operation of the algorithm and typical simulations; variable final-time problem considerations; and a modification of Powell's algorithm.

Pricing policy for declining demand using item preservation technology.

PubMed

Khedlekar, Uttam Kumar; Shukla, Diwakar; Namdeo, Anubhav

2016-01-01

We have designed an inventory model for seasonal products in which deterioration can be controlled by item preservation technology investment. Demand for the product is considered price sensitive and decreases linearly. This study has shown that the profit is a concave function of optimal selling price, replenishment time and preservation cost parameter. We simultaneously determined the optimal selling price of the product, the replenishment cycle and the cost of item preservation technology. Additionally, this study has shown that there exists an optimal selling price and optimal preservation investment to maximize the profit for every business set-up. Finally, the model is illustrated by numerical examples and sensitive analysis of the optimal solution with respect to major parameters.

Contribution to the optimal shape design of two-dimensional internal flows with embedded shocks

NASA Technical Reports Server (NTRS)

Iollo, Angelo; Salas, Manuel D.

1995-01-01

We explore the practicability of optimal shape design for flows modeled by the Euler equations. We define a functional whose minimum represents the optimality condition. The gradient of the functional with respect to the geometry is calculated with the Lagrange multipliers, which are determined by solving a co-state equation. The optimization problem is then examined by comparing the performance of several gradient-based optimization algorithms. In this formulation, the flow field can be computed to an arbitrary order of accuracy. Finally, some results for internal flows with embedded shocks are presented, including a case for which the solution to the inverse problem does not belong to the design space.

Optimality of Thermal Expansion Bounds in Three Dimensions

DOE PAGES

Watts, Seth E.; Tortorelli, Daniel A.

2015-02-20

In this short note, we use topology optimization to design multi-phase isotropic three-dimensional composite materials with extremal combinations of isotropic thermal expansion and bulk modulus. In so doing, we provide evidence that the theoretical bounds for this combination of material properties are optimal. This has been shown in two dimensions, but not heretofore in three dimensions. Finally, we also show that restricting the design space by enforcing material symmetry by construction does not prevent one from obtaining extremal designs.

Optimizing Motion Planning for Hyper Dynamic Manipulator

NASA Astrophysics Data System (ADS)

Aboura, Souhila; Omari, Abdelhafid; Meguenni, Kadda Zemalache

2012-01-01

This paper investigates the optimal motion planning for an hyper dynamic manipulator. As case study, we consider a golf swing robot which is consisting with two actuated joint and a mechanical stoppers. Genetic Algorithm (GA) technique is proposed to solve the optimal golf swing motion which is generated by Fourier series approximation. The objective function for GA approach is to minimizing the intermediate and final state, minimizing the robot's energy consummation and maximizing the robot's speed. Obtained simulation results show the effectiveness of the proposed scheme.

Research on the optimization of vehicle distribution routes in logistics enterprises

NASA Astrophysics Data System (ADS)

Fan, Zhigou; Ma, Mengkun

2018-01-01

With the rapid development of modern logistics, the vehicle routing problem has become one of the urgent problems in the logistics industry. The rationality of distribution route planning directly affects the efficiency and quality of logistics distribution. This paper first introduces the definition of logistics distribution and the three methods of optimizing the distribution routes, and then analyzes the current vehicle distribution route by using a representative example, finally puts forward the optimization schemes of logistics distribution route.

Optimal impulsive manoeuvres and aerodynamic braking

NASA Technical Reports Server (NTRS)

Jezewski, D. J.

1985-01-01

A method developed for obtaining solutions to the aerodynamic braking problem, using impulses in the exoatmospheric phases is discussed. The solution combines primer vector theory and the results of a suboptimal atmospheric guidance program. For a specified initial and final orbit, the solution determines: (1) the minimum impulsive cost using a maximum of four impulses, (2) the optimal atmospheric entry and exit-state vectors subject to equality and inequality constraints, and (3) the optimal coast times. Numerical solutions which illustrate the characteristics of the solution are presented.

Neighboring extremal optimal control design including model mismatch errors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, T.J.; Hull, D.G.

1994-11-01

The mismatch control technique that is used to simplify model equations of motion in order to determine analytic optimal control laws is extended using neighboring extremal theory. The first variation optimal control equations are linearized about the extremal path to account for perturbations in the initial state and the final constraint manifold. A numerical example demonstrates that the tuning procedure inherent in the mismatch control method increases the performance of the controls to the level of a numerically-determined piecewise-linear controller.

Recovering metabolic pathways via optimization.

PubMed

Beasley, John E; Planes, Francisco J

2007-01-01

A metabolic pathway is a coherent set of enzyme catalysed biochemical reactions by which a living organism transforms an initial (source) compound into a final (target) compound. Some of the different metabolic pathways adopted within organisms have been experimentally determined. In this paper, we show that a number of experimentally determined metabolic pathways can be recovered by a mathematical optimization model.

Improving Environmental Model Calibration and Prediction

DTIC Science & Technology

2011-01-18

REPORT Final Report - Improving Environmental Model Calibration and Prediction 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: First, we have continued to...develop tools for efficient global optimization of environmental models. Our algorithms are hybrid algorithms that combine evolutionary strategies...toward practical hybrid optimization tools for environmental models. 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 18-01-2011 13

Optimizing the Environmental Attitudes Inventory: Establishing a Baseline of Change in Students' Attitudes

ERIC Educational Resources Information Center

Sutton, Stephen G.; Gyuris, Emma

2015-01-01

Purpose: The purpose of this study was twofold: first, to optimize the Environmental Attitudes Inventory (EAI) and second, to establish a baseline of the difference in environmental attitudes between first and final year students, taken at the start of a university's declaration of commitment to EfS. Design/methodology/approach: The…

Task Scheduling in Desktop Grids: Open Problems

NASA Astrophysics Data System (ADS)

Chernov, Ilya; Nikitina, Natalia; Ivashko, Evgeny

2017-12-01

We survey the areas of Desktop Grid task scheduling that seem to be insufficiently studied so far and are promising for efficiency, reliability, and quality of Desktop Grid computing. These topics include optimal task grouping, "needle in a haystack" paradigm, game-theoretical scheduling, domain-imposed approaches, special optimization of the final stage of the batch computation, and Enterprise Desktop Grids.

Improving Evaluation Use in Local School Settings. Optimizing Evaluation Use: Final Report.

ERIC Educational Resources Information Center

King, Jean A.; And Others

A project for studying ways to optimize utilization of evaluation products in public schools is reported. The results indicate that the negative picture of use prevalent in recent literature stems from the unrealistic expectation that local decision-makers will behave in a classically rational manner. Such a view ignores the political settings of…

Heuristic and optimal policy computations in the human brain during sequential decision-making.

PubMed

Korn, Christoph W; Bach, Dominik R

2018-01-23

Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

PubMed

Yang, Shaofu; Liu, Qingshan; Wang, Jun

2018-04-01

This paper is concerned with multiple-objective distributed optimization. Based on objective weighting and decision space decomposition, a collaborative neurodynamic approach to multiobjective distributed optimization is presented. In the approach, a system of collaborative neural networks is developed to search for Pareto optimal solutions, where each neural network is associated with one objective function and given constraints. Sufficient conditions are derived for ascertaining the convergence to a Pareto optimal solution of the collaborative neurodynamic system. In addition, it is proved that each connected subsystem can generate a Pareto optimal solution when the communication topology is disconnected. Then, a switching-topology-based method is proposed to compute multiple Pareto optimal solutions for discretized approximation of Pareto front. Finally, simulation results are discussed to substantiate the performance of the collaborative neurodynamic approach. A portfolio selection application is also given.

Large-scale structural optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.

1983-01-01

Problems encountered by aerospace designers in attempting to optimize whole aircraft are discussed, along with possible solutions. Large scale optimization, as opposed to component-by-component optimization, is hindered by computational costs, software inflexibility, concentration on a single, rather than trade-off, design methodology and the incompatibility of large-scale optimization with single program, single computer methods. The software problem can be approached by placing the full analysis outside of the optimization loop. Full analysis is then performed only periodically. Problem-dependent software can be removed from the generic code using a systems programming technique, and then embody the definitions of design variables, objective function and design constraints. Trade-off algorithms can be used at the design points to obtain quantitative answers. Finally, decomposing the large-scale problem into independent subproblems allows systematic optimization of the problems by an organization of people and machines.

Improved understanding of the searching behavior of ant colony optimization algorithms applied to the water distribution design problem

NASA Astrophysics Data System (ADS)

Zecchin, A. C.; Simpson, A. R.; Maier, H. R.; Marchi, A.; Nixon, J. B.

2012-09-01

Evolutionary algorithms (EAs) have been applied successfully to many water resource problems, such as system design, management decision formulation, and model calibration. The performance of an EA with respect to a particular problem type is dependent on how effectively its internal operators balance the exploitation/exploration trade-off to iteratively find solutions of an increasing quality. For a given problem, different algorithms are observed to produce a variety of different final performances, but there have been surprisingly few investigations into characterizing how the different internal mechanisms alter the algorithm's searching behavior, in both the objective and decision space, to arrive at this final performance. This paper presents metrics for analyzing the searching behavior of ant colony optimization algorithms, a particular type of EA, for the optimal water distribution system design problem, which is a classical NP-hard problem in civil engineering. Using the proposed metrics, behavior is characterized in terms of three different attributes: (1) the effectiveness of the search in improving its solution quality and entering into optimal or near-optimal regions of the search space, (2) the extent to which the algorithm explores as it converges to solutions, and (3) the searching behavior with respect to the feasible and infeasible regions. A range of case studies is considered, where a number of ant colony optimization variants are applied to a selection of water distribution system optimization problems. The results demonstrate the utility of the proposed metrics to give greater insight into how the internal operators affect each algorithm's searching behavior.

Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method.

PubMed

Traneus, Erik; Bizzocchi, Nicola; Fellin, Francesco; Rombi, Barbara; Farace, Paolo

2018-01-01

The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Shuffle Optimizer: A Program to Optimize DNA Shuffling for Protein Engineering.

PubMed

Milligan, John N; Garry, Daniel J

2017-01-01

DNA shuffling is a powerful tool to develop libraries of variants for protein engineering. Here, we present a protocol to use our freely available and easy-to-use computer program, Shuffle Optimizer. Shuffle Optimizer is written in the Python computer language and increases the nucleotide homology between two pieces of DNA desired to be shuffled together without changing the amino acid sequence. In addition we also include sections on optimal primer design for DNA shuffling and library construction, a small-volume ultrasonicator method to create sheared DNA, and finally a method to reassemble the sheared fragments and recover and clone the library. The Shuffle Optimizer program and these protocols will be useful to anyone desiring to perform any of the nucleotide homology-dependent shuffling methods.

Energy-optimal electrical excitation of nerve fibers.

PubMed

Jezernik, Saso; Morari, Manfred

2005-04-01

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

Improving global CD uniformity by optimizing post-exposure bake and develop sequences

NASA Astrophysics Data System (ADS)

Osborne, Stephen P.; Mueller, Mark; Lem, Homer; Reyland, David; Baik, KiHo

2003-12-01

Improvements in the final uniformity of masks can be shrouded by error contributions from many sources. The final Global CD Uniformity (GCDU) of a mask is degraded by individual contributions of the writing tool, the Post Applied Bake (PAB), the Post Exposure Bake (PEB), the Develop sequence and the Etch step. Final global uniformity will improve by isolating and minimizing the variability of the PEB and Develop. We achieved this de-coupling of the PEB and Develop process from the whole process stream by using "dark loss" which is the loss of unexposed resist during the develop process. We confirmed a correspondence between Angstroms of dark loss and nanometer sized deviations in the chrome CD. A plate with a distinctive dark loss pattern was related to a nearly identical pattern in the chrome CD. This pattern was verified to have originated during the PEB process and displayed a [Δ(Final CD)/Δ(Dark Loss)] ratio of 6 for TOK REAP200 resist. Previous papers have reported a sensitive linkage between Angstroms of dark loss and nanometers in the final uniformity of the written plate. These initial studies reported using this method to improve the PAB of resists for greater uniformity of sensitivity and contrast. Similarly, this paper demonstrates an outstanding optimization of PEB and Develop processes.

NARMAX model identification of a palm oil biodiesel engine using multi-objective optimization differential evolution

NASA Astrophysics Data System (ADS)

Mansor, Zakwan; Zakaria, Mohd Zakimi; Nor, Azuwir Mohd; Saad, Mohd Sazli; Ahmad, Robiah; Jamaluddin, Hishamuddin

2017-09-01

This paper presents the black-box modelling of palm oil biodiesel engine (POB) using multi-objective optimization differential evolution (MOODE) algorithm. Two objective functions are considered in the algorithm for optimization; minimizing the number of term of a model structure and minimizing the mean square error between actual and predicted outputs. The mathematical model used in this study to represent the POB system is nonlinear auto-regressive moving average with exogenous input (NARMAX) model. Finally, model validity tests are applied in order to validate the possible models that was obtained from MOODE algorithm and lead to select an optimal model.

Deconflicting Wind-Optimal Aircraft Trajectories in North Atlantic Oceanic Airspace

NASA Technical Reports Server (NTRS)

Rodionova, Olga; Delahaye, Daniel; Sridhar, Banavar; Ng, Hok K.

2016-01-01

North Atlantic oceanic airspace accommodates more than 1000 flights daily, and is subjected to very strong winds. Flying wind-optimal trajectories yields time and fuel savings for each individual flight. However, when taken together, these trajectories induce a large amount of potential en-route conflicts. This paper analyses the detected conflicts, figuring out conflict distribution in time and space. It further describes an optimization algorithm aimed at reducing the number of conflicts for a daily set of flights on strategic level. Several trajectory modification strategies are discussed, followed with simulation results. Finally, an algorithm improvement is presented aiming at better preserving the trajectory optimality.

Minimum-fuel, 3-dimensional flightpath guidance of transfer jets

NASA Technical Reports Server (NTRS)

Neuman, F.; Kreindler, E.

1984-01-01

Minimum fuel, three dimensional flightpaths for commercial jet aircraft are discussed. The theoretical development is divided into two sections. In both sections, the necessary conditions of optimal control, including singular arcs and state constraints, are used. One section treats the initial and final portions (below 10,000 ft) of long optimal flightpaths. Here all possible paths can be derived by generating fields of extremals. Another section treats the complete intermediate length, three dimensional terminal area flightpaths. Here only representative sample flightpaths can be computed. Sufficient detail is provided to give the student of optimal control a complex example of a useful application of optimal control theory.

Optimal and Autonomous Control Using Reinforcement Learning: A Survey.

PubMed

Kiumarsi, Bahare; Vamvoudakis, Kyriakos G; Modares, Hamidreza; Lewis, Frank L

2018-06-01

This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively. Moreover, we discuss a new direction of off-policy RL for both CT and DT systems. Finally, we review several applications.

Optimized Electroactive Polymer Supercapacitors

DTIC Science & Technology

2014-09-08

Final 03/01/2012-05/15/2014 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER OPTIMIZED ELECTROACTIVE POLYMER SUPERCAPACITORS NA Sb. GRANT NUMBER N00014-12-1...highly electroactive, conjugated polymers as the active redox materials in electrochemical supercapacitors . Such materials include electrochemically...ethylenedioxythiophene) (PEDOT) for Type I or Type II supercapacitors , along with donor-acceptor-donor (D-A-D) polymers which provide reductive states for Type

Optimization of an intracavity Q-switched solid-state second order Raman laser

NASA Astrophysics Data System (ADS)

Chen, Zhiqiong; Fu, Xihong; Peng, Hangyu; Zhang, Jun; Qin, Li; Ning, Yongqiang

2017-01-01

In this paper, the model of an intracavity Q-switched second order Raman laser is established, the characteristics of the output 2nd Stokes are simulated. The dynamic balance mechanism among intracavity conversion rates of stimulated emission, first order Raman and second order Raman is obtained. Finally, optimization solutions for increasing output 2nd Stokes pulse energy are proposed.

Final report for project "Next-Generation Semiconductors for Solar Photoelectrolysis"

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khalifah, Peter

2016-09-15

In this paper, effective methods have been developed for preparing high-quality LaTiO 2N films on conductive La 5Ti 5O 17 substrates that can serve as photoanodes for photoelectrochemical water oxidation. One paper has been written by the post-doc who completed this comprehensive, interdisciplinary study, and it is presently being finalized for submission. Our approach to this system integrates expertise that we have developed in single crystal growth, thin film growth, and thin film post-processing. Through this work, LTON films have been fully optimized for light harvesting, as their band gap is optimally matched with the incident solar spectrum and themore » film thicknesses have been optimized based on the absolute absorption coefficients that we have measured for this system. The next step is to optimize the co-catalyst functionalization and the solution conditions to maximize the catalytic activity for water oxidation. Since the preliminary tests described here were done without a water oxidation co-catalyst, and since good water oxidation catalysts have previously been identified based on studies of powder samples, this next step is highly likely to be successful.« less

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Anger and health in dementia caregivers: exploring the mediation effect of optimism.

PubMed

López, J; Romero-Moreno, R; Márquez-González, M; Losada, A

2015-04-01

Although previous studies indicate a negative association between caregivers' anger and health, the potential mechanisms linking this relationship are not yet fully understood. The aim of this study was to explore the potential mediating role of optimism in the relationship between anger and caregivers' physical health. Dementia caregivers (n = 108) were interviewed and filled out instruments assessing their anger (reaction), optimism and health (vitality). A mediational model was tested to determine whether optimism partially mediated the relationship between anger and vitality. Angry reaction was negatively associated with optimism and vitality; optimism was positively associated with vitality. Finally, the relationship between angry reaction and vitality decreased when optimism was entered simultaneously. A non-parametric bootstrap approach confirmed that optimism significantly mediated some of the relationship between angry reaction and vitality. These findings suggest that low optimism may help explain the association between caregivers' anger and reduced sense of vitality. The results provide a specific target for intervention with caregivers. Copyright © 2013 John Wiley & Sons, Ltd.

Process development for automated solar cell and module production. Task 4: Automated array assembly

NASA Technical Reports Server (NTRS)

Hagerty, J. J.

1981-01-01

Progress in the development of automated solar cell and module production is reported. The unimate robot is programmed for the final 35 cell pattern to be used in the fabrication of the deliverable modules. The mechanical construction of the automated lamination station and final assembly station phases are completed and the first operational testing is underway. The final controlling program is written and optimized. The glass reinforced concrete (GRC) panels to be used for testing and deliverables are in production. Test routines are grouped together and defined to produce the final control program.

Optimization of Interior Permanent Magnet Motor by Quality Engineering and Multivariate Analysis

NASA Astrophysics Data System (ADS)

Okada, Yukihiro; Kawase, Yoshihiro

This paper has described the method of optimization based on the finite element method. The quality engineering and the multivariable analysis are used as the optimization technique. This optimizing method consists of two steps. At Step.1, the influence of parameters for output is obtained quantitatively, at Step.2, the number of calculation by the FEM can be cut down. That is, the optimal combination of the design parameters, which satisfies the required characteristic, can be searched for efficiently. In addition, this method is applied to a design of IPM motor to reduce the torque ripple. The final shape can maintain average torque and cut down the torque ripple 65%. Furthermore, the amount of permanent magnets can be reduced.

Hybrid algorithms for fuzzy reverse supply chain network design.

PubMed

Che, Z H; Chiang, Tzu-An; Kuo, Y C; Cui, Zhihua

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods.

A systematic FPGA acceleration design for applications based on convolutional neural networks

NASA Astrophysics Data System (ADS)

Dong, Hao; Jiang, Li; Li, Tianjian; Liang, Xiaoyao

2018-04-01

Most FPGA accelerators for convolutional neural network are designed to optimize the inner acceleration and are ignored of the optimization for the data path between the inner accelerator and the outer system. This could lead to poor performance in applications like real time video object detection. We propose a brand new systematic FPFA acceleration design to solve this problem. This design takes the data path optimization between the inner accelerator and the outer system into consideration and optimizes the data path using techniques like hardware format transformation, frame compression. It also takes fixed-point, new pipeline technique to optimize the inner accelerator. All these make the final system's performance very good, reaching about 10 times the performance comparing with the original system.

Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design

PubMed Central

Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057

Optimal boarding method for airline passengers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Steffen, Jason H.; /Fermilab

2008-02-01

Using a Markov Chain Monte Carlo optimization algorithm and a computer simulation, I find the passenger ordering which minimizes the time required to board the passengers onto an airplane. The model that I employ assumes that the time that a passenger requires to load his or her luggage is the dominant contribution to the time needed to completely fill the aircraft. The optimal boarding strategy may reduce the time required to board and airplane by over a factor of four and possibly more depending upon the dimensions of the aircraft. I explore some features of the optimal boarding method andmore » discuss practical modifications to the optimal. Finally, I mention some of the benefits that could come from implementing an improved passenger boarding scheme.« less

Trajectory optimization for the National Aerospace Plane

NASA Technical Reports Server (NTRS)

Lu, Ping

1992-01-01

The primary objective of this research is to develop an efficient and robust trajectory optimization tool for the optimal ascent problem of the National Aerospace Plane (NASP). This report is organized in the following order to summarize the complete work: Section two states the formulation and models of the trajectory optimization problem. An inverse dynamics approach to the problem is introduced in Section three. Optimal trajectories corresponding to various conditions and performance parameters are presented in Section four. A midcourse nonlinear feedback controller is developed in Section five. Section six demonstrates the performance of the inverse dynamics approach and midcourse controller during disturbances. Section seven discusses rocket assisted ascent which may be beneficial when orbital altitude is high. Finally, Section eight recommends areas of future research.

Structural optimization of structured carbon-based energy-storing composite materials used in space vehicles.

PubMed

Yu, Jia; Yu, Zhichao; Tang, Chenlong

2016-07-04

The hot work environment of electronic components in the instrument cabin of spacecraft was researched, and a new thermal protection structure, namely graphite carbon foam, which is an impregnated phase-transition material, was adopted to implement the thermal control on the electronic components. We used the optimized parameters obtained from ANSYS to conduct 2D optimization, 3-D modeling and simulation, as well as the strength check. Finally, the optimization results were verified by experiments. The results showed that after optimization, the structured carbon-based energy-storing composite material could reduce the mass and realize the thermal control over electronic components. This phase-transition composite material still possesses excellent temperature control performance after its repeated melting and solidifying.

Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell-Boltzmann gases

NASA Astrophysics Data System (ADS)

Ahmadi, Mohammad H.; Amin Nabakhteh, Mohammad; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah; Bidi, Mokhtar

2017-10-01

The motivation behind this work is to explore a nanoscale irreversible Stirling refrigerator with respect to size impacts and shows two novel thermo-ecological criteria. Two distinct strategies were suggested in the optimization process and the consequences of every strategy were examined independently. In the primary strategy, with the purpose of maximizing the energetic sustainability index and modified the ecological coefficient of performance (MECOP) and minimizing the dimensionless Ecological function, a multi-objective optimization algorithm (MOEA) was used. In the second strategy, with the purpose of maximizing the ECOP and MECOP and minimizing the dimensionless Ecological function, a MOEA was used. To conclude the final solution from each strategy, three proficient decision makers were utilized. Additionally, to quantify the deviation of the results gained from each decision makers, two different statistical error indexes were employed. Finally, based on the comparison between the results achieved from proposed scenarios reveals that by maximizing the MECOP the maximum values of ESI, ECOP, and a minimum of ecfare achieved.

Optimizing the parameters of heat transmission in a small heat exchanger with spiral tapes cut as triangles and Aluminum oxide nanofluid using central composite design method

NASA Astrophysics Data System (ADS)

Ghasemi, Nahid; Aghayari, Reza; Maddah, Heydar

2018-07-01

The present study aims at optimizing the heat transmission parameters such as Nusselt number and friction factor in a small double pipe heat exchanger equipped with rotating spiral tapes cut as triangles and filled with aluminum oxide nanofluid. The effects of Reynolds number, twist ratio (y/w), rotating twisted tape and concentration (w%) on the Nusselt number and friction factor are also investigated. The central composite design and the response surface methodology are used for evaluating the responses necessary for optimization. According to the optimal curves, the most optimized value obtained for Nusselt number and friction factor was 146.6675 and 0.06020, respectively. Finally, an appropriate correlation is also provided to achieve the optimal model of the minimum cost. Optimization results showed that the cost has decreased in the best case.

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

PubMed Central

Jin, Junchen

2016-01-01

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

Optimizing the parameters of heat transmission in a small heat exchanger with spiral tapes cut as triangles and Aluminum oxide nanofluid using central composite design method

NASA Astrophysics Data System (ADS)

Ghasemi, Nahid; Aghayari, Reza; Maddah, Heydar

2018-02-01

The present study aims at optimizing the heat transmission parameters such as Nusselt number and friction factor in a small double pipe heat exchanger equipped with rotating spiral tapes cut as triangles and filled with aluminum oxide nanofluid. The effects of Reynolds number, twist ratio (y/w), rotating twisted tape and concentration (w%) on the Nusselt number and friction factor are also investigated. The central composite design and the response surface methodology are used for evaluating the responses necessary for optimization. According to the optimal curves, the most optimized value obtained for Nusselt number and friction factor was 146.6675 and 0.06020, respectively. Finally, an appropriate correlation is also provided to achieve the optimal model of the minimum cost. Optimization results showed that the cost has decreased in the best case.

Experimental validation of structural optimization methods

NASA Technical Reports Server (NTRS)

Adelman, Howard M.

1992-01-01

The topic of validating structural optimization methods by use of experimental results is addressed. The need for validating the methods as a way of effecting a greater and an accelerated acceptance of formal optimization methods by practicing engineering designers is described. The range of validation strategies is defined which includes comparison of optimization results with more traditional design approaches, establishing the accuracy of analyses used, and finally experimental validation of the optimization results. Examples of the use of experimental results to validate optimization techniques are described. The examples include experimental validation of the following: optimum design of a trussed beam; combined control-structure design of a cable-supported beam simulating an actively controlled space structure; minimum weight design of a beam with frequency constraints; minimization of the vibration response of helicopter rotor blade; minimum weight design of a turbine blade disk; aeroelastic optimization of an aircraft vertical fin; airfoil shape optimization for drag minimization; optimization of the shape of a hole in a plate for stress minimization; optimization to minimize beam dynamic response; and structural optimization of a low vibration helicopter rotor.

Uncertainty Aware Structural Topology Optimization Via a Stochastic Reduced Order Model Approach

NASA Technical Reports Server (NTRS)

Aguilo, Miguel A.; Warner, James E.

2017-01-01

This work presents a stochastic reduced order modeling strategy for the quantification and propagation of uncertainties in topology optimization. Uncertainty aware optimization problems can be computationally complex due to the substantial number of model evaluations that are necessary to accurately quantify and propagate uncertainties. This computational complexity is greatly magnified if a high-fidelity, physics-based numerical model is used for the topology optimization calculations. Stochastic reduced order model (SROM) methods are applied here to effectively 1) alleviate the prohibitive computational cost associated with an uncertainty aware topology optimization problem; and 2) quantify and propagate the inherent uncertainties due to design imperfections. A generic SROM framework that transforms the uncertainty aware, stochastic topology optimization problem into a deterministic optimization problem that relies only on independent calls to a deterministic numerical model is presented. This approach facilitates the use of existing optimization and modeling tools to accurately solve the uncertainty aware topology optimization problems in a fraction of the computational demand required by Monte Carlo methods. Finally, an example in structural topology optimization is presented to demonstrate the effectiveness of the proposed uncertainty aware structural topology optimization approach.

Optimal policy for mitigating emissions in the European transport sector

NASA Astrophysics Data System (ADS)

Leduc, Sylvain; Piera, Patrizio; Sennai, Mesfun; Igor, Staritsky; Berien, Elbersen; Tijs, Lammens; Florian, Kraxner

2017-04-01

A geographic explicit techno-economic model, BeWhere (www.iiasa.ac.at/bewhere), has been developed at the European scale (Europe 28, the Balkans countries, Turkey, Moldavia and Ukraine) at a 40km grid size, to assess the potential of bioenergy from non-food feedstock. Based on the minimization of the supply chain from feedstock collection to the final energy product distribution, the model identifies the optimal bioenergy production plants in terms of spatial location, technology and capacity. The feedstock of interests are woody biomass (divided into eight types from conifers and non-conifers) and five different crop residuals. For each type of feedstock, one or multiple technologies can be applied for either heat, electricity or biofuel production. The model is run for different policy tools such as carbon cost, biofuel support, or subsidies, and the optimal mix of technologies and biomass needed is optimized to reach a production cost competitive against the actual reference system which is fossil fuel based. From this approach, the optimal mix of policy tools that can be applied country wide in Europe will be identified. The preliminary results show that high carbon tax and biofuel support contribute to the development of large scale biofuel production based on woody biomass plants mainly located in the northern part of Europe. Finally the highest emission reduction is reached with low biofuel support and high carbon tax evenly distributed in Europe.

Warpage improvement on wheel caster by optimizing the process parameters using genetic algorithm (GA)

NASA Astrophysics Data System (ADS)

Safuan, N. S.; Fathullah, M.; Shayfull, Z.; Nasir, S. M.; Hazwan, M. H. M.

2017-09-01

In injection moulding process, the defects will always encountered and affected the final product shape and functionality. This study is concerning on minimizing warpage and optimizing the process parameter of injection moulding part. Apart from eliminating product wastes, this project also giving out best recommended parameters setting. This research studied on five parameters. The optimization showed that warpage have been improved 42.64% from 0.6524 mm to 0.30879 mm in Autodesk Moldflow Insight (AMI) simulation result and Genetic Algorithm (GA) respectively.

Optimal Harvesting in a Periodic Food Chain Model with Size Structures in Predators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Feng-Qin, E-mail: zhafq@263.net; Liu, Rong; Chen, Yuming, E-mail: ychen@wlu.ca

In this paper, we investigate a periodic food chain model with harvesting, where the predators have size structures and are described by first-order partial differential equations. First, we establish the existence of a unique non-negative solution by using the Banach fixed point theorem. Then, we provide optimality conditions by means of normal cone and adjoint system. Finally, we derive the existence of an optimal strategy by means of Ekeland’s variational principle. Here the objective functional represents the net economic benefit yielded from harvesting.

Optimal rail container shipment planning problem in multimodal transportation

NASA Astrophysics Data System (ADS)

Cao, Chengxuan; Gao, Ziyou; Li, Keping

2012-09-01

The optimal rail container shipment planning problem in multimodal transportation is studied in this article. The characteristics of the multi-period planning problem is presented and the problem is formulated as a large-scale 0-1 integer programming model, which maximizes the total profit generated by all freight bookings accepted in a multi-period planning horizon subject to the limited capacities. Two heuristic algorithms are proposed to obtain an approximate optimal solution of the problem. Finally, numerical experiments are conducted to demonstrate the proposed formulation and heuristic algorithms.

A dual method for optimal control problems with initial and final boundary constraints.

NASA Technical Reports Server (NTRS)

Pironneau, O.; Polak, E.

1973-01-01

This paper presents two new algorithms belonging to the family of dual methods of centers. The first can be used for solving fixed time optimal control problems with inequality constraints on the initial and terminal states. The second one can be used for solving fixed time optimal control problems with inequality constraints on the initial and terminal states and with affine instantaneous inequality constraints on the control. Convergence is established for both algorithms. Qualitative reasoning indicates that the rate of convergence is linear.

Design and optimization of a fiber optic data link for new generation on-board SAR processing architectures

NASA Astrophysics Data System (ADS)

Ciminelli, Caterina; Dell'Olio, Francesco; Armenise, Mario N.; Iacomacci, Francesco; Pasquali, Franca; Formaro, Roberto

2017-11-01

A fiber optic digital link for on-board data handling is modeled, designed and optimized in this paper. Design requirements and constraints relevant to the link, which is in the frame of novel on-board processing architectures, are discussed. Two possible link configurations are investigated, showing their advantages and disadvantages. An accurate mathematical model of each link component and the entire system is reported and results of link simulation based on those models are presented. Finally, some details on the optimized design are provided.

Closed-Form and Numerically-Stable Solutions to Problems Related to the Optimal Two-Impulse Transfer Between Specified Terminal States of Keplerian Orbits

NASA Technical Reports Server (NTRS)

Senent, Juan

2011-01-01

The first part of the paper presents some closed-form solutions to the optimal two-impulse transfer between fixed position and velocity vectors on Keplerian orbits when some constraints are imposed on the magnitude of the initial and final impulses. Additionally, a numerically-stable gradient-free algorithm with guaranteed convergence is presented for the minimum delta-v two-impulse transfer. In the second part of the paper, cooperative bargaining theory is used to solve some two-impulse transfer problems when the initial and final impulses are carried by different vehicles or when the goal is to minimize the delta-v and the time-of-flight at the same time.

Optimal Operation and Dispatch of Voltage Regulation Devices Considering High Penetrations of Distributed Photovoltaic Generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mather, Barry A; Hodge, Brian S; Cho, Gyu-Jung

Voltage regulation devices have been traditionally installed and utilized to support distribution voltages. Installations of distributed energy resources (DERs) in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile for a feeder; therefore, in the distribution system planning stage of the optimal operation and dispatch of voltage regulation devices, possible high penetrations of DERs should be considered. In this paper, we model the IEEE 34-bus test feeder, including all essential equipment. An optimization method is adopted to determine the optimal siting and operation ofmore » the voltage regulation devices in the presence of distributed solar power generation. Finally, we verify the optimal configuration of the entire system through the optimization and simulation results.« less

The potential application of the blackboard model of problem solving to multidisciplinary design

NASA Technical Reports Server (NTRS)

Rogers, James L.

1989-01-01

The potential application of the blackboard model of problem solving to multidisciplinary design is discussed. Multidisciplinary design problems are complex, poorly structured, and lack a predetermined decision path from the initial starting point to the final solution. The final solution is achieved using data from different engineering disciplines. Ideally, for the final solution to be the optimum solution, there must be a significant amount of communication among the different disciplines plus intradisciplinary and interdisciplinary optimization. In reality, this is not what happens in today's sequential approach to multidisciplinary design. Therefore it is highly unlikely that the final solution is the true optimum solution from an interdisciplinary optimization standpoint. A multilevel decomposition approach is suggested as a technique to overcome the problems associated with the sequential approach, but no tool currently exists with which to fully implement this technique. A system based on the blackboard model of problem solving appears to be an ideal tool for implementing this technique because it offers an incremental problem solving approach that requires no a priori determined reasoning path. Thus it has the potential of finding a more optimum solution for the multidisciplinary design problems found in today's aerospace industries.

Topology Optimization - Engineering Contribution to Architectural Design

NASA Astrophysics Data System (ADS)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

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

Taboo Search: An Approach to the Multiple Minima Problem

NASA Astrophysics Data System (ADS)

Cvijovic, Djurdje; Klinowski, Jacek

1995-02-01

Described here is a method, based on Glover's taboo search for discrete functions, of solving the multiple minima problem for continuous functions. As demonstrated by model calculations, the algorithm avoids entrapment in local minima and continues the search to give a near-optimal final solution. Unlike other methods of global optimization, this procedure is generally applicable, easy to implement, derivative-free, and conceptually simple.

Decision Through Optimism: The North Peruvian Pipeline.

DTIC Science & Technology

1987-05-01

corporations. Another factor, optimism, is more intangible, but influenced the decision strongly. This paper discusses the need for, construction of...decision, the construction effort, and financing to accomplish this endeavor. Finally, it notes Peru’s oil situation after completion of the pipeline and...decision strongly. This paper discusses the need for, construction of, and results of building the Northern Peru Oil Pipeline. The paper reviews the

Contingency Contractor Optimization Phase 3 Sustainment Software Design Document - Contingency Contractor Optimization Tool - Prototype

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durfee, Justin David; Frazier, Christopher Rawls; Bandlow, Alisa

This document describes the final software design of the Contingency Contractor Optimization Tool - Prototype. Its purpose is to provide the overall architecture of the software and the logic behind this architecture. Documentation for the individual classes is provided in the application Javadoc. The Contingency Contractor Optimization project is intended to address Department of Defense mandates by delivering a centralized strategic planning tool that allows senior decision makers to quickly and accurately assess the impacts, risks, and mitigation strategies associated with utilizing contract support. The Contingency Contractor Optimization Tool - Prototype was developed in Phase 3 of the OSD ATLmore » Contingency Contractor Optimization project to support strategic planning for contingency contractors. The planning tool uses a model to optimize the Total Force mix by minimizing the combined total costs for selected mission scenarios. The model optimizes the match of personnel types (military, DoD civilian, and contractors) and capabilities to meet mission requirements as effectively as possible, based on risk, cost, and other requirements.« less

Rapid design and optimization of low-thrust rendezvous/interception trajectory for asteroid deflection missions

NASA Astrophysics Data System (ADS)

Li, Shuang; Zhu, Yongsheng; Wang, Yukai

2014-02-01

Asteroid deflection techniques are essential in order to protect the Earth from catastrophic impacts by hazardous asteroids. Rapid design and optimization of low-thrust rendezvous/interception trajectories is considered as one of the key technologies to successfully deflect potentially hazardous asteroids. In this paper, we address a general framework for the rapid design and optimization of low-thrust rendezvous/interception trajectories for future asteroid deflection missions. The design and optimization process includes three closely associated steps. Firstly, shape-based approaches and genetic algorithm (GA) are adopted to perform preliminary design, which provides a reasonable initial guess for subsequent accurate optimization. Secondly, Radau pseudospectral method is utilized to transcribe the low-thrust trajectory optimization problem into a discrete nonlinear programming (NLP) problem. Finally, sequential quadratic programming (SQP) is used to efficiently solve the nonlinear programming problem and obtain the optimal low-thrust rendezvous/interception trajectories. The rapid design and optimization algorithms developed in this paper are validated by three simulation cases with different performance indexes and boundary constraints.

Optimal design of experiments applied to headspace solid phase microextraction for the quantification of vicinal diketones in beer through gas chromatography-mass spectrometric detection.

PubMed

Leça, João M; Pereira, Ana C; Vieira, Ana C; Reis, Marco S; Marques, José C

2015-08-05

Vicinal diketones, namely diacetyl (DC) and pentanedione (PN), are compounds naturally found in beer that play a key role in the definition of its aroma. In lager beer, they are responsible for off-flavors (buttery flavor) and therefore their presence and quantification is of paramount importance to beer producers. Aiming at developing an accurate quantitative monitoring scheme to follow these off-flavor compounds during beer production and in the final product, the head space solid-phase microextraction (HS-SPME) analytical procedure was tuned through experiments planned in an optimal way and the final settings were fully validated. Optimal design of experiments (O-DOE) is a computational, statistically-oriented approach for designing experiences that are most informative according to a well-defined criterion. This methodology was applied for HS-SPME optimization, leading to the following optimal extraction conditions for the quantification of VDK: use a CAR/PDMS fiber, 5 ml of samples in 20 ml vial, 5 min of pre-incubation time followed by 25 min of extraction at 30 °C, with agitation. The validation of the final analytical methodology was performed using a matrix-matched calibration, in order to minimize matrix effects. The following key features were obtained: linearity (R(2) > 0.999, both for diacetyl and 2,3-pentanedione), high sensitivity (LOD of 0.92 μg L(-1) and 2.80 μg L(-1), and LOQ of 3.30 μg L(-1) and 10.01 μg L(-1), for diacetyl and 2,3-pentanedione, respectively), recoveries of approximately 100% and suitable precision (repeatability and reproducibility lower than 3% and 7.5%, respectively). The applicability of the methodology was fully confirmed through an independent analysis of several beer samples, with analyte concentrations ranging from 4 to 200 g L(-1). Copyright © 2015 Elsevier B.V. All rights reserved.

Comparative Analysis of Sequential Proximal Optimizing Technique Versus Kissing Balloon Inflation Technique in Provisional Bifurcation Stenting: Fractal Coronary Bifurcation Bench Test.

PubMed

Finet, Gérard; Derimay, François; Motreff, Pascal; Guerin, Patrice; Pilet, Paul; Ohayon, Jacques; Darremont, Olivier; Rioufol, Gilles

2015-08-24

This study used a fractal bifurcation bench model to compare 6 optimization sequences for coronary bifurcation provisional stenting, including 1 novel sequence without kissing balloon inflation (KBI), comprising initial proximal optimizing technique (POT) + side-branch inflation (SBI) + final POT, called "re-POT." In provisional bifurcation stenting, KBI fails to improve the rate of major adverse cardiac events. Proximal geometric deformation increases the rate of in-stent restenosis and target lesion revascularization. A bifurcation bench model was used to compare KBI alone, KBI after POT, KBI with asymmetric inflation pressure after POT, and 2 sequences without KBI: initial POT plus SBI, and initial POT plus SBI with final POT (called "re-POT"). For each protocol, 5 stents were tested using 2 different drug-eluting stent designs: that is, a total of 60 tests. Compared with the classic KBI-only sequence and those associating POT with modified KBI, the re-POT sequence gave significantly (p < 0.05) better geometric results: it reduced SB ostium stent-strut obstruction from 23.2 ± 6.0% to 5.6 ± 8.3%, provided perfect proximal stent apposition with almost perfect circularity (ellipticity index reduced from 1.23 ± 0.02 to 1.04 ± 0.01), reduced proximal area overstretch from 24.2 ± 7.6% to 8.0 ± 0.4%, and reduced global strut malapposition from 40 ± 6.2% to 2.6 ± 1.4%. In comparison with 5 other techniques, the re-POT sequence significantly optimized the final result of provisional coronary bifurcation stenting, maintaining circular geometry while significantly reducing SB ostium strut obstruction and global strut malapposition. These experimental findings confirm that provisional stenting may be optimized more effectively without KBI using re-POT. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Optimal Control for Fast and Robust Generation of Entangled States in Anisotropic Heisenberg Chains

NASA Astrophysics Data System (ADS)

Zhang, Xiong-Peng; Shao, Bin; Zou, Jian

2017-05-01

Motivated by some recent results of the optimal control (OC) theory, we study anisotropic XXZ Heisenberg spin-1/2 chains with control fields acting on a single spin, with the aim of exploring how maximally entangled state can be prepared. To achieve the goal, we use a numerical optimization algorithm (e.g., the Krotov algorithm, which was shown to be capable of reaching the quantum speed limit) to search an optimal set of control parameters, and then obtain OC pulses corresponding to the target fidelity. We find that the minimum time for implementing our target state depending on the anisotropy parameter Δ of the model. Finally, we analyze the robustness of the obtained results for the optimal fidelities and the effectiveness of the Krotov method under some realistic conditions.

A Method of Trajectory Design for Manned Asteroid Explorations1,2

NASA Astrophysics Data System (ADS)

Gan, Qing-Bo; Zhang, Yang; Zhu, Zheng-Fan; Han, Wei-Hua; Dong, Xin

2015-07-01

A trajectory optimization method for the nuclear-electric propulsion manned asteroid explorations is presented. In the case of launching between 2035 and 2065, based on the two-pulse single-cycle Lambert transfer orbit, the phases of departure from and return to the Earth are searched at first. Then the optimal flight trajectory is selected by pruning the flight sequences in two feasible regions. Setting the flight strategy of propelling-taxiing-propelling, and taking the minimal fuel consumption as the performance index, the nuclear-electric propulsion flight trajectory is optimized using the hybrid method. Finally, taking the segmentally optimized parameters as the initial values, in accordance with the overall mission constraints, the globally optimized parameters are obtained. And the numerical and diagrammatical results are given at the same time.

Optimal strategy for controlling the spread of Plasmodium Knowlesi malaria: Treatment and culling

NASA Astrophysics Data System (ADS)

Abdullahi, Mohammed Baba; Hasan, Yahya Abu; Abdullah, Farah Aini

2015-05-01

Plasmodium Knowlesi malaria is a parasitic mosquito-borne disease caused by a eukaryotic protist of genus Plasmodium Knowlesi transmitted by mosquito, Anopheles leucosphyrus to human and macaques. We developed and analyzed a deterministic Mathematical model for the transmission of Plasmodium Knowlesi malaria in human and macaques. The optimal control theory is applied to investigate optimal strategies for controlling the spread of Plasmodium Knowlesi malaria using treatment and culling as control strategies. The conditions for optimal control of the Plasmodium Knowlesi malaria are derived using Pontryagin's Maximum Principle. Finally, numerical simulations suggested that the combination of the control strategies is the best way to control the disease in any community.

Supply chain optimization: a practitioner's perspective on the next logistics breakthrough.

PubMed

Schlegel, G L

2000-08-01

The objective of this paper is to profile a practitioner's perspective on supply chain optimization and highlight the critical elements of this potential new logistics breakthrough idea. The introduction will briefly describe the existing distribution network, and business environment. This will include operational statistics, manufacturing software, and hardware configurations. The first segment will cover the critical success factors or foundations elements that are prerequisites for success. The second segment will give you a glimpse of a "working game plan" for successful migration to supply chain optimization. The final segment will briefly profile "bottom-line" benefits to be derived from the use of supply chain optimization as a strategy, tactical tool, and competitive advantage.

Complex optimization for big computational and experimental neutron datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bao, Feng; Oak Ridge National Lab.; Archibald, Richard

Here, we present a framework to use high performance computing to determine accurate solutions to the inverse optimization problem of big experimental data against computational models. We demonstrate how image processing, mathematical regularization, and hierarchical modeling can be used to solve complex optimization problems on big data. We also demonstrate how both model and data information can be used to further increase solution accuracy of optimization by providing confidence regions for the processing and regularization algorithms. Finally, we use the framework in conjunction with the software package SIMPHONIES to analyze results from neutron scattering experiments on silicon single crystals, andmore » refine first principles calculations to better describe the experimental data.« less

Selecting the selector: Comparison of update rules for discrete global optimization

DOE PAGES

Theiler, James; Zimmer, Beate G.

2017-05-24

In this paper, we compare some well-known Bayesian global optimization methods in four distinct regimes, corresponding to high and low levels of measurement noise and to high and low levels of “quenched noise” (which term we use to describe the roughness of the function we are trying to optimize). We isolate the two stages of this optimization in terms of a “regressor,” which fits a model to the data measured so far, and a “selector,” which identifies the next point to be measured. Finally, the focus of this paper is to investigate the choice of selector when the regressor ismore » well matched to the data.« less

Design Optimization of Gas Generator Hybrid Propulsion Boosters

NASA Technical Reports Server (NTRS)

Weldon, Vincent; Phillips, Dwight; Fink, Larry

1990-01-01

A methodology used in support of a study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specific optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates.

Construction of Pancreatic Cancer Classifier Based on SVM Optimized by Improved FOA

PubMed Central

Ma, Xiaoqi

2015-01-01

A novel method is proposed to establish the pancreatic cancer classifier. Firstly, the concept of quantum and fruit fly optimal algorithm (FOA) are introduced, respectively. Then FOA is improved by quantum coding and quantum operation, and a new smell concentration determination function is defined. Finally, the improved FOA is used to optimize the parameters of support vector machine (SVM) and the classifier is established by optimized SVM. In order to verify the effectiveness of the proposed method, SVM and other classification methods have been chosen as the comparing methods. The experimental results show that the proposed method can improve the classifier performance and cost less time. PMID:26543867

Complex optimization for big computational and experimental neutron datasets

DOE PAGES

Bao, Feng; Oak Ridge National Lab.; Archibald, Richard; ...

2016-11-07

Here, we present a framework to use high performance computing to determine accurate solutions to the inverse optimization problem of big experimental data against computational models. We demonstrate how image processing, mathematical regularization, and hierarchical modeling can be used to solve complex optimization problems on big data. We also demonstrate how both model and data information can be used to further increase solution accuracy of optimization by providing confidence regions for the processing and regularization algorithms. Finally, we use the framework in conjunction with the software package SIMPHONIES to analyze results from neutron scattering experiments on silicon single crystals, andmore » refine first principles calculations to better describe the experimental data.« less

Exact solution for an optimal impermeable parachute problem

NASA Astrophysics Data System (ADS)

Lupu, Mircea; Scheiber, Ernest

2002-10-01

In the paper there are solved direct and inverse boundary problems and analytical solutions are obtained for optimization problems in the case of some nonlinear integral operators. It is modeled the plane potential flow of an inviscid, incompressible and nonlimited fluid jet, witch encounters a symmetrical, curvilinear obstacle--the deflector of maximal drag. There are derived integral singular equations, for direct and inverse problems and the movement in the auxiliary canonical half-plane is obtained. Next, the optimization problem is solved in an analytical manner. The design of the optimal airfoil is performed and finally, numerical computations concerning the drag coefficient and other geometrical and aerodynamical parameters are carried out. This model corresponds to the Helmholtz impermeable parachute problem.

Towards Excellence in Asthma Management: final report of an eight-year program aimed at reducing care gaps in asthma management in Quebec.

PubMed

Boulet, Louis-Philippe; Dorval, E; Labrecque, M; Turgeon, M; Montague, T; Thivierge, R L

2008-09-01

Asthma care in Canada and around the world persistently falls short of optimal treatment. To optimize care, a systematic approach to identifying such shortfalls or 'care gaps', in which all stakeholders of the health care system (including patients) are involved, was proposed. Several projects of a multipartner, multidisciplinary disease management program, developed to optimize asthma care in Quebec, was conducted in a period of eight years. First, two population maps were produced to identify regional variations in asthma-related morbidity and to prioritize interventions for improving treatment. Second, current care was evaluated in a physician-patient cohort, confirming the many care gaps in asthma management. Third, two series of peer-reviewed outcome studies, targeting high-risk populations and specific asthma care gaps, were conducted. Finally, a process to integrate the best interventions into the health care system and an agenda for further research on optimal asthma management were proposed. Key observations from these studies included the identification of specific patterns of noncompliance in using inhaled corticosteroids, the failure of increased access to spirometry in asthma education centres to increase the number of education referrals, the transient improvement in educational abilities of nurses involved with an asthma hotline telephone service, and the beneficial effects of practice tools aimed at facilitating the assessment of asthma control and treatment needs by general practitioners. Disease management programs such as Towards Excellence in Asthma Management can provide valuable information on optimal strategies for improving treatment of asthma and other chronic diseases by identifying care gaps, improving guidelines implementation and optimizing care.

Simulation-Driven Design Approach for Design and Optimization of Blankholder

NASA Astrophysics Data System (ADS)

Sravan, Tatipala; Suddapalli, Nikshep R.; Johan, Pilthammar; Mats, Sigvant; Christian, Johansson

2017-09-01

Reliable design of stamping dies is desired for efficient and safe production. The design of stamping dies are today mostly based on casting feasibility, although it can also be based on criteria for fatigue, stiffness, safety, economy. Current work presents an approach that is built on Simulation Driven Design, enabling Design Optimization to address this issue. A structural finite element model of a stamping die, used to produce doors for Volvo V70/S80 car models, is studied. This die had developed cracks during its usage. To understand the behaviour of stress distribution in the stamping die, structural analysis of the die is conducted and critical regions with high stresses are identified. The results from structural FE-models are compared with analytical calculations pertaining to fatigue properties of the material. To arrive at an optimum design with increased stiffness and lifetime, topology and free-shape optimization are performed. In the optimization routine, identified critical regions of the die are set as design variables. Other optimization variables are set to maintain manufacturability of the resultant stamping die. Thereafter a CAD model is built based on geometrical results from topology and free-shape optimizations. Then the CAD model is subjected to structural analysis to visualize the new stress distribution. This process is iterated until a satisfactory result is obtained. The final results show reduction in stress levels by 70% with a more homogeneous distribution. Even though mass of the die is increased by 17 %, overall, a stiffer die with better lifetime is obtained. Finally, by reflecting on the entire process, a coordinated approach to handle such situations efficiently is presented.

Crash pulse optimization for occupant protection at various impact velocities.

PubMed

Ito, Daisuke; Yokoi, Yusuke; Mizuno, Koji

2015-01-01

Vehicle deceleration has a large influence on occupant kinematic behavior and injury risks in crashes, and the optimization of the vehicle crash pulse that mitigates occupant loadings has been the subject of substantial research. These optimization research efforts focused on only high-velocity impact in regulatory or new car assessment programs though vehicle collisions occur over a wide range of velocities. In this study, the vehicle crash pulse was optimized for various velocities with a genetic algorithm. Vehicle deceleration was optimized in a full-frontal rigid barrier crash with a simple spring-mass model that represents the vehicle-occupant interaction and a Hybrid III 50th percentile male multibody model. To examine whether the vehicle crash pulse optimized at the high impact velocity is useful for reducing occupant loading at all impact velocities less than the optimized velocity, the occupant deceleration was calculated at various velocities for the optimized crash pulse determined at a high speed. The optimized vehicle deceleration-deformation characteristics that are effective for various velocities were investigated with 2 approaches. The optimized vehicle crash pulse at a single impact velocity consists of a high initial impulse followed by zero deceleration and then constant deceleration in the final stage. The vehicle deceleration optimized with the Hybrid III model was comparable to that determined from the spring-mass model. The optimized vehicle deceleration-deformation characteristics determined at a high speed did not necessarily lead to an occupant deceleration reduction at a lower velocity. The maximum occupant deceleration at each velocity was normalized by the maximum deceleration determined in the single impact velocity optimization. The resulting vehicle deceleration-deformation characteristic was a square crash pulse. The objective function was defined as the number of injuries, which was the product of the number of collisions at the velocity and the probability of occupant injury. The optimized vehicle deceleration consisted of a high deceleration in the initial phase, a small deceleration in the middle phase, and then a high deceleration in the final phase. The optimized vehicle crash pulse at a single impact velocity is effective for reducing occupant deceleration in a crash at the specific impact velocity. However, the crash pulse does not necessarily lead to occupant deceleration reduction at a lower velocity. The optimized vehicle deceleration-deformation characteristics, which are effective for all impact velocities, depend on the weighting of the occupant injury measures at each impact velocity.

Joint global optimization of tomographic data based on particle swarm optimization and decision theory

NASA Astrophysics Data System (ADS)

Paasche, H.; Tronicke, J.

2012-04-01

In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto optimality of the found solutions can be made. Identification of the leading particle traditionally requires a costly combination of ranking and niching techniques. In our approach, we use a decision rule under uncertainty to identify the currently leading particle of the swarm. In doing so, we consider the different objectives of our optimization problem as competing agents with partially conflicting interests. Analysis of the maximin fitness function allows for robust and cheap identification of the currently leading particle. The final optimization result comprises a set of possible models spread along the Pareto front. For convex Pareto fronts, solution density is expected to be maximal in the region ideally compromising all objectives, i.e. the region of highest curvature.

Full-Carpet Design of a Low-Boom Demonstrator Concept

NASA Technical Reports Server (NTRS)

Ordaz, Irian; Wintzer, Mathias; Rallabhandi, Sriram K.

2015-01-01

The Cart3D adjoint-based design framework is used to mitigate the undesirable o -track sonic boom properties of a demonstrator concept designed for low-boom directly under the flight path. First, the requirements of a Cart3D design mesh are determined using a high-fidelity mesh adapted to minimize the discretization error of the CFD analysis. Low-boom equivalent area targets are then generated at the under-track and one off-track azimuthal position for the baseline configuration. The under-track target is generated using a trim- feasible low-boom target generation process, ensuring that the final design is not only low-boom, but also trimmed at the specified flight condition. The o -track equivalent area target is generated by minimizing the A-weighted loudness using an efficient adjoint-based approach. The configuration outer mold line is then parameterized and optimized to match the off-body pressure distributions prescribed by the low-boom targets. The numerical optimizer uses design gradients which are calculated using the Cart3D adjoint- based design capability. Optimization constraints are placed on the geometry to satisfy structural feasibility. The low-boom properties of the final design are verified using the adaptive meshing approach. This analysis quantifies the error associated with the CFD mesh that is used for design. Finally, an alternate mesh construction and target positioning approach offering greater computational efficiency is demonstrated and verified.

Advanced and Hybrid Powertrains

Science.gov Websites

and analysis, and to create methodologies for evaluating the true potential of proposed advanced architectures, and optimal control strategies. Finally, experimental studies are being conducted to support

Analysis of static and dynamic characteristic of spindle system and its structure optimization in camshaft grinding machine

NASA Astrophysics Data System (ADS)

Feng, Jianjun; Li, Chengzhe; Wu, Zhi

2017-08-01

As an important part of the valve opening and closing controller in engine, camshaft has high machining accuracy requirement in designing. Taking the high-speed camshaft grinder spindle system as the research object and the spindle system performance as the optimizing target, this paper firstly uses Solidworks to establish the three-dimensional finite element model (FEM) of spindle system, then conducts static analysis and the modal analysis by applying the established FEM in ANSYS Workbench, and finally uses the design optimization function of the ANSYS Workbench to optimize the structure parameter in the spindle system. The study results prove that the design of the spindle system fully meets the production requirements, and the performance of the optimized spindle system is promoted. Besides, this paper provides an analysis and optimization method for other grinder spindle systems.

Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality.

PubMed

Otero-Muras, Irene; Banga, Julio R

2017-07-21

In this work we consider Pareto optimality for automated design in synthetic biology. We present a generalized framework based on a mixed-integer dynamic optimization formulation that, given design specifications, allows the computation of Pareto optimal sets of designs, that is, the set of best trade-offs for the metrics of interest. We show how this framework can be used for (i) forward design, that is, finding the Pareto optimal set of synthetic designs for implementation, and (ii) reverse design, that is, analyzing and inferring motifs and/or design principles of gene regulatory networks from the Pareto set of optimal circuits. Finally, we illustrate the capabilities and performance of this framework considering four case studies. In the first problem we consider the forward design of an oscillator. In the remaining problems, we illustrate how to apply the reverse design approach to find motifs for stripe formation, rapid adaption, and fold-change detection, respectively.

Topology optimization of finite strain viscoplastic systems under transient loads [Dynamic topology optimization based on finite strain visco-plasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Topology optimization of finite strain viscoplastic systems under transient loads [Dynamic topology optimization based on finite strain visco-plasticity

DOE PAGES

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

2018-02-08

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Study on loading path optimization of internal high pressure forming process

NASA Astrophysics Data System (ADS)

Jiang, Shufeng; Zhu, Hengda; Gao, Fusheng

2017-09-01

In the process of internal high pressure forming, there is no formula to describe the process parameters and forming results. The article use numerical simulation to obtain several input parameters and corresponding output result, use the BP neural network to found their mapping relationship, and with weighted summing method make each evaluating parameters to set up a formula which can evaluate quality. Then put the training BP neural network into the particle swarm optimization, and take the evaluating formula of the quality as adapting formula of particle swarm optimization, finally do the optimization and research at the range of each parameters. The results show that the parameters obtained by the BP neural network algorithm and the particle swarm optimization algorithm can meet the practical requirements. The method can solve the optimization of the process parameters in the internal high pressure forming process.

Optimization of end-pumped, actively Q-switched quasi-III-level lasers.

PubMed

Jabczynski, Jan K; Gorajek, Lukasz; Kwiatkowski, Jacek; Kaskow, Mateusz; Zendzian, Waldemar

2011-08-15

The new model of end-pumped quasi-III-level laser considering transient pumping processes, ground-state-depletion and up-conversion effects was developed. The model consists of two parts: pumping stage and Q-switched part, which can be separated in a case of active Q-switching regime. For pumping stage the semi-analytical model was developed, enabling the calculations for final occupation of upper laser level for given pump power and duration, spatial profile of pump beam, length and dopant level of gain medium. For quasi-stationary inversion, the optimization procedure of Q-switching regime based on Lagrange multiplier technique was developed. The new approach for optimization of CW regime of quasi-three-level lasers was developed to optimize the Q-switched lasers operating with high repetition rates. Both methods of optimizations enable calculation of optimal absorbance of gain medium and output losses for given pump rate. © 2011 Optical Society of America

Research on damping properties optimization of variable-stiffness plate

NASA Astrophysics Data System (ADS)

Wen-kai, QI; Xian-tao, YIN; Cheng, SHEN

2016-09-01

This paper investigates damping optimization design of variable-stiffness composite laminated plate, which means fibre paths can be continuously curved and fibre angles are distinct for different regions. First, damping prediction model is developed based on modal dissipative energy principle and verified by comparing with modal testing results. Then, instead of fibre angles, the element stiffness and damping matrixes are translated to be design variables on the basis of novel Discrete Material Optimization (DMO) formulation, thus reducing the computation time greatly. Finally, the modal damping capacity of arbitrary order is optimized using MMA (Method of Moving Asymptotes) method. Meanwhile, mode tracking technique is employed to investigate the variation of modal shape. The convergent performance of interpolation function, first order specific damping capacity (SDC) optimization results and variation of modal shape in different penalty factor are discussed. The results show that the damping properties of the variable-stiffness plate can be increased by 50%-70% after optimization.

Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach

NASA Astrophysics Data System (ADS)

Lu, Yanrong; Liao, Fucheng; Deng, Jiamei; Liu, Huiyang

2017-09-01

This paper investigates the cooperative global optimal preview tracking problem of linear multi-agent systems under the assumption that the output of a leader is a previewable periodic signal and the topology graph contains a directed spanning tree. First, a type of distributed internal model is introduced, and the cooperative preview tracking problem is converted to a global optimal regulation problem of an augmented system. Second, an optimal controller, which can guarantee the asymptotic stability of the augmented system, is obtained by means of the standard linear quadratic optimal preview control theory. Third, on the basis of proving the existence conditions of the controller, sufficient conditions are given for the original problem to be solvable, meanwhile a cooperative global optimal controller with error integral and preview compensation is derived. Finally, the validity of theoretical results is demonstrated by a numerical simulation.

Fatigue design of a cellular phone folder using regression model-based multi-objective optimization

NASA Astrophysics Data System (ADS)

Kim, Young Gyun; Lee, Jongsoo

2016-08-01

In a folding cellular phone, the folding device is repeatedly opened and closed by the user, which eventually results in fatigue damage, particularly to the front of the folder. Hence, it is important to improve the safety and endurance of the folder while also reducing its weight. This article presents an optimal design for the folder front that maximizes its fatigue endurance while minimizing its thickness. Design data for analysis and optimization were obtained experimentally using a test jig. Multi-objective optimization was carried out using a nonlinear regression model. Three regression methods were employed: back-propagation neural networks, logistic regression and support vector machines. The AdaBoost ensemble technique was also used to improve the approximation. Two-objective Pareto-optimal solutions were identified using the non-dominated sorting genetic algorithm (NSGA-II). Finally, a numerically optimized solution was validated against experimental product data, in terms of both fatigue endurance and thickness index.

[Not Available].

PubMed

Mokeddem, Diab; Khellaf, Abdelhafid

2009-01-01

Optimal design problem are widely known by their multiple performance measures that are often competing with each other. In this paper, an optimal multiproduct batch chemical plant design is presented. The design is firstly formulated as a multiobjective optimization problem, to be solved using the well suited non dominating sorting genetic algorithm (NSGA-II). The NSGA-II have capability to achieve fine tuning of variables in determining a set of non dominating solutions distributed along the Pareto front in a single run of the algorithm. The NSGA-II ability to identify a set of optimal solutions provides the decision-maker DM with a complete picture of the optimal solution space to gain better and appropriate choices. Then an outranking with PROMETHEE II helps the decision-maker to finalize the selection of a best compromise. The effectiveness of NSGA-II method with multiojective optimization problem is illustrated through two carefully referenced examples.

Stochastic Hybrid Systems Modeling and Middleware-enabled DDDAS for Next-generation US Air Force Systems

DTIC Science & Technology

2017-03-30

experimental evaluations for hosting DDDAS-like applications in public cloud infrastructures . Finally, we report on ongoing work towards using the DDDAS...developed and their experimental evaluations for hosting DDDAS-like applications in public cloud infrastructures . Finally, we report on ongoing work towards...Dynamic resource management, model learning, simulation-based optimizations, cloud infrastructures for DDDAS applications. I. INTRODUCTION Critical cyber

Fuel-optimal low-thrust formation reconfiguration via Radau pseudospectral method

NASA Astrophysics Data System (ADS)

Li, Jing

2016-07-01

This paper investigates fuel-optimal low-thrust formation reconfiguration near circular orbit. Based on the Clohessy-Wiltshire equations, first-order necessary optimality conditions are derived from the Pontryagin's maximum principle. The fuel-optimal impulsive solution is utilized to divide the low-thrust trajectory into thrust and coast arcs. By introducing the switching times as optimization variables, the fuel-optimal low-thrust formation reconfiguration is posed as a nonlinear programming problem (NLP) via direct transcription using multiple-phase Radau pseudospectral method (RPM), which is then solved by a sparse nonlinear optimization software SNOPT. To facilitate optimality verification and, if necessary, further refinement of the optimized solution of the NLP, formulas for mass costate estimation and initial costates scaling are presented. Numerical examples are given to show the application of the proposed optimization method. To fix the problem, generic fuel-optimal low-thrust formation reconfiguration can be simplified as reconfiguration without any initial and terminal coast arcs, whose optimal solutions can be efficiently obtained from the multiple-phase RPM at the cost of a slight fuel increment. Finally, influence of the specific impulse and maximum thrust magnitude on the fuel-optimal low-thrust formation reconfiguration is analyzed. Numerical results shown the links and differences between the fuel-optimal impulsive and low-thrust solutions.

Optimization in the systems engineering process

NASA Technical Reports Server (NTRS)

Lemmerman, L. A.

1984-01-01

The objective is to look at optimization as it applies to the design process at a large aircraft company. The design process at Lockheed-Georgia is described. Some examples of the impact that optimization has had on that process are given, and then some areas that must be considered if optimization is to be successful and supportive in the total design process are indicated. Optimization must continue to be sold and this selling is best done by consistent good performance. For this good performance to occur, the future approaches must be clearly thought out so that the optimization methods solve the problems that actually occur during design. The visibility of the design process must be maintained as further developments are proposed. Careful attention must be given to the management of data in the optimization process, both for technical reasons and for administrative purposes. Finally, to satisfy program needs, provisions must be included to supply data to support program decisions, and to communicate with design processes outside of the optimization process. If designers fail to adequately consider all of these needs, the future acceptance of optimization will be impeded.

Linear Optimization and Image Reconstruction

DTIC Science & Technology

1994-06-01

final example is again a novel one. We formulate the problem of computer assisted tomographic ( CAT ) image reconstruction as a linear optimization...possibility that a patient, Fred, suffers from a brain tumor. Further, the physician opts to make use of the CAT (Computer Aided Tomography) scan device...and examine the inside of Fred’s head without exploratory surgery. The CAT scan machine works by projecting a finite number of X-rays of known

Optimization of Breast Tomosynthesis Imaging Systems for Computer-Aided Detection

DTIC Science & Technology

2011-05-01

R. Saunders, E. Samei, C. Badea, H. Yuan, K. Ghaghada, Y. Qi, L. Hedlund, and S. Mukundan, “Optimization of dual energy contrast enhanced breast...14 4 1 Introduction This is the final report for this body of research. Screen-film mammography and...digital mammography have been used for over 30 years in the early detection of cancer. The combination of screening and adjuvant therapies have led to

Optimizing Operational Physical Fitness (Optimisation de L’Aptitude Physique Operationnelle)

DTIC Science & Technology

2009-01-01

NORTH ATLANTIC TREATY ORGANISATION RESEARCH AND TECHNOLOGY ORGANISATION AC/323(HFM-080)TP/200 www.rto.nato.int RTO TECHNICAL REPORT TR... RESEARCH AND TECHNOLOGY ORGANISATION AC/323(HFM-080)TP/200 www.rto.nato.int RTO TECHNICAL REPORT TR-HFM-080 Optimizing Operational Physical...Fitness (Optimisation de l’aptitude physique opérationnelle) Final Report of Task Group 019. ii RTO-TR-HFM-080 The Research and

Research and Development of Heavy Gauge X80 Pipeline Plate Utilizing Optimized Rolling and Cooling Process

NASA Astrophysics Data System (ADS)

Li, Shaopo; Li, Jiading; Ding, Wenhua; Zhang, Hai

This paper reports on the experience with the production of 27/33 mm X80 heavy wall thicknesses, large OD (48") in Shouqin Steel Co., Ltd. (SQS). Considering the technology capability of the plate mill in SQS, a optimized rolling and cooling process was developed to achieve stable heavy gauge X80 mechanical properties. The importance of the slab reheating process and rolling schedule will be discussed in the paper. In addition, the per pass reductions logic used during recrystallized rough rolling, and special emphasis on the reduction of the final roughing pass prior to the intermediate holding resulting in a fine uniform prior austenite microstructure will be discussed. The optimized cooling process application after finish rolling guarantees the steady control of the final bainitic microstructure with optimum M/A phase for heavy gauge X80 plates. The plates produced by this process achieved good flatness and excellent mechanical properties. SQS has produced 10000 tons 27mm X80 for the Middle Asia C Line Project and 1000 tons 33mm X80 for the 3rd West-to-East Natural Gas Transmission Pipeline Project in 2013-2014. The products utilizing optimized rolling and cooling process showed extremely excellent low temperature toughness.

Collaboration Mechanism for Equipment Instruction of Multiple Energy Systems

NASA Astrophysics Data System (ADS)

Wang, Dong; Wang, Tuo; Wang, Qi; Zhang, Zhao; Zhao, Mingyu; Wang, Yinghui

2018-01-01

When multiple energy systems execute optimization instructions simultaneously, and the same equipment is Shared, the instruction conflict may occur. Aiming at the above problems, taking into account the control objectives of each system, the characteristics of different systems, such as comprehensive clean energy, energy efficiency, and peak filling, etc., designed the instruction coordination mechanism for the daemon. This mechanism mainly acts on the main station of the system, and form a final optimization instruction. For some specific scenarios, the collaboration mechanism of unlocking the terminal is supplemented. The mechanism determines the specific execution instructions based on the arrival time of the instruction. Finally, the experiment in Tianjin eco-city shows that this algorithm can meet the instruction and collaboration requirements of multi-energy systems, and ensure the safe operation of the equipment.

Fractional-order TV-L2 model for image denoising

NASA Astrophysics Data System (ADS)

Chen, Dali; Sun, Shenshen; Zhang, Congrong; Chen, YangQuan; Xue, Dingyu

2013-10-01

This paper proposes a new fractional order total variation (TV) denoising method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, regularization parameter selection and blocky effect. Two fractional order TV-L2 models are constructed for image denoising. The majorization-minimization (MM) algorithm is used to decompose these two complex fractional TV optimization problems into a set of linear optimization problems which can be solved by the conjugate gradient algorithm. The final adaptive numerical procedure is given. Finally, we report experimental results which show that the proposed methodology avoids the blocky effect and achieves state-of-the-art performance. In addition, two medical image processing experiments are presented to demonstrate the validity of the proposed methodology.

The effect of different control point sampling sequences on convergence of VMAT inverse planning

NASA Astrophysics Data System (ADS)

Pardo Montero, Juan; Fenwick, John D.

2011-04-01

A key component of some volumetric-modulated arc therapy (VMAT) optimization algorithms is the progressive addition of control points to the optimization. This idea was introduced in Otto's seminal VMAT paper, in which a coarse sampling of control points was used at the beginning of the optimization and new control points were progressively added one at a time. A different form of the methodology is also present in the RapidArc optimizer, which adds new control points in groups called 'multiresolution levels', each doubling the number of control points in the optimization. This progressive sampling accelerates convergence, improving the results obtained, and has similarities with the ordered subset algorithm used to accelerate iterative image reconstruction. In this work we have used a VMAT optimizer developed in-house to study the performance of optimization algorithms which use different control point sampling sequences, most of which fall into three different classes: doubling sequences, which add new control points in groups such that the number of control points in the optimization is (roughly) doubled; Otto-like progressive sampling which adds one control point at a time, and equi-length sequences which contain several multiresolution levels each with the same number of control points. Results are presented in this study for two clinical geometries, prostate and head-and-neck treatments. A dependence of the quality of the final solution on the number of starting control points has been observed, in agreement with previous works. We have found that some sequences, especially E20 and E30 (equi-length sequences with 20 and 30 multiresolution levels, respectively), generate better results than a 5 multiresolution level RapidArc-like sequence. The final value of the cost function is reduced up to 20%, such reductions leading to small improvements in dosimetric parameters characterizing the treatments—slightly more homogeneous target doses and better sparing of the organs at risk.

Optimization of conventional Fenton and ultraviolet-assisted oxidation processes for the treatment of reverse osmosis retentate from a paper mill.

PubMed

Hermosilla, Daphne; Merayo, Noemí; Ordóñez, Ruth; Blanco, Angeles

2012-06-01

According to current environmental legislation concerned with water scarcity, paper industry is being forced to adopt a zero liquid effluent policy. In consequence, reverse osmosis (RO) systems are being assessed as the final step of effluent treatment trains aiming to recover final wastewater and reuse it as process water. One of the most important drawbacks of these treatments is the production of a retentated stream, which is usually highly loaded with biorecalcitrant organic matter and inorganics; and this effluent must meet current legislation stringent constraints before being ultimately disposed. The treatment of biorefractory RO retentate from a paper mill by several promising advanced oxidation processes (AOPs) - conventional Fenton, photo-Fenton and photocatalysis - was optimized considering the effect and interaction of reaction parameters; particularly using response surface methodology (RSM) when appropriate (Fenton processes). The economical cost of these treatments was also comparatively assessed. Photo-Fenton process was able to totally remove the COD of the retentate, and resulted even operatively cheaper at high COD removal levels than conventional Fenton, which achieved an 80% reduction of the COD at best. In addition, although these optimal results were produced at pH=2.8, it was also tested that Fenton processes are able to achieve good COD reduction efficiencies (>60%) without adjusting the initial pH value, provided the natural pH of this wastewater was close to neutral. Finally, although TiO(2)-photocatalysis showed the least efficient and most expensive figures, it improved the biodegradability of the retentate, so its combination with a final biological step almost achieved the total removal of the COD. Copyright © 2011 Elsevier Ltd. All rights reserved.

Recent developments in the structural design and optimization of ITER neutral beam manifold

NASA Astrophysics Data System (ADS)

Chengzhi, CAO; Yudong, PAN; Zhiwei, XIA; Bo, LI; Tao, JIANG; Wei, LI

2018-02-01

This paper describes a new design of the neutral beam manifold based on a more optimized support system. A proposed alternative scheme has presented to replace the former complex manifold supports and internal pipe supports in the final design phase. Both the structural reliability and feasibility were confirmed with detailed analyses. Comparative analyses between two typical types of manifold support scheme were performed. All relevant results of mechanical analyses for typical operation scenarios and fault conditions are presented. Future optimization activities are described, which will give useful information for a refined setting of components in the next phase.

Thickness optimization of auricular silicone scaffold based on finite element analysis.

PubMed

Jiang, Tao; Shang, Jianzhong; Tang, Li; Wang, Zhuo

2016-01-01

An optimized thickness of a transplantable auricular silicone scaffold was researched. The original image data were acquired from CT scans, and reverse modeling technology was used to build a digital 3D model of an auricle. The transplant process was simulated in ANSYS Workbench by finite element analysis (FEA), solid scaffolds were manufactured based on the FEA results, and the transplantable artificial auricle was finally obtained with an optimized thickness, as well as sufficient intensity and hardness. This paper provides a reference for clinical transplant surgery. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural networks for structural design - An integrated system implementation

NASA Technical Reports Server (NTRS)

Berke, Laszlo; Hafez, Wassim; Pao, Yoh-Han

1992-01-01

The development of powerful automated procedures to aid the creative designer is becoming increasingly critical for complex design tasks. In the work described here Artificial Neural Nets are applied to acquire structural analysis and optimization domain expertise. Based on initial instructions from the user an automated procedure generates random instances of structural analysis and/or optimization 'experiences' that cover a desired domain. It extracts training patterns from the created instances, constructs and trains an appropriate network architecture and checks the accuracy of net predictions. The final product is a trained neural net that can estimate analysis and/or optimization results instantaneously.

Final Report---Optimization Under Nonconvexity and Uncertainty: Algorithms and Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeff Linderoth

2011-11-06

the goal of this work was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems. The focus of the work done in the continuation was on Mixed Integer Nonlinear Programs (MINLP)s and Mixed Integer Linear Programs (MILP)s, especially those containing a great deal of symmetry.

Simplified Numerical Analysis of ECT Probe - Eddy Current Benchmark Problem 3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sikora, R.; Chady, T.; Gratkowski, S.

2005-04-09

In this paper a third eddy current benchmark problem is considered. The objective of the benchmark is to determine optimal operating frequency and size of the pancake coil designated for testing tubes made of Inconel. It can be achieved by maximization of the change in impedance of the coil due to a flaw. Approximation functions of the probe (coil) characteristic were developed and used in order to reduce number of required calculations. It results in significant speed up of the optimization process. An optimal testing frequency and size of the probe were achieved as a final result of the calculation.

An Optimized Control for LLC Resonant Converter with Wide Load Range

NASA Astrophysics Data System (ADS)

Xi, Xia; Qian, Qinsong

2017-05-01

This paper presents an optimized control which makes LLC resonant converters operate with a wider load range and provides good closed-loop performance. The proposed control employs two paralleled digital compensations to guarantee the good closed-loop performance in a wide load range during the steady state, an optimized trajectory control will take over to change the gate-driving signals immediately at the load transients. Finally, the proposed control has been implemented and tested on a 150W 200kHz 400V/24V LLC resonant converter and the result validates the proposed method.

Analysis and optimization of gyrokinetic toroidal simulations on homogenous and heterogenous platforms

DOE PAGES

Ibrahim, Khaled Z.; Madduri, Kamesh; Williams, Samuel; ...

2013-07-18

The Gyrokinetic Toroidal Code (GTC) uses the particle-in-cell method to efficiently simulate plasma microturbulence. This paper presents novel analysis and optimization techniques to enhance the performance of GTC on large-scale machines. We introduce cell access analysis to better manage locality vs. synchronization tradeoffs on CPU and GPU-based architectures. Finally, our optimized hybrid parallel implementation of GTC uses MPI, OpenMP, and NVIDIA CUDA, achieves up to a 2× speedup over the reference Fortran version on multiple parallel systems, and scales efficiently to tens of thousands of cores.

Theory and computation of optimal low- and medium-thrust transfers

NASA Technical Reports Server (NTRS)

Chuang, C.-H.

1994-01-01

This report describes the current state of development of methods for calculating optimal orbital transfers with large numbers of burns. Reported on first is the homotopy-motivated and so-called direction correction method. So far this method has been partially tested with one solver; the final step has yet to be implemented. Second is the patched transfer method. This method is rooted in some simplifying approximations made on the original optimal control problem. The transfer is broken up into single-burn segments, each single-burn solved as a predictor step and the whole problem then solved with a corrector step.

Approximate dynamic programming for optimal stationary control with control-dependent noise.

PubMed

Jiang, Yu; Jiang, Zhong-Ping

2011-12-01

This brief studies the stochastic optimal control problem via reinforcement learning and approximate/adaptive dynamic programming (ADP). A policy iteration algorithm is derived in the presence of both additive and multiplicative noise using Itô calculus. The expectation of the approximated cost matrix is guaranteed to converge to the solution of some algebraic Riccati equation that gives rise to the optimal cost value. Moreover, the covariance of the approximated cost matrix can be reduced by increasing the length of time interval between two consecutive iterations. Finally, a numerical example is given to illustrate the efficiency of the proposed ADP methodology.

Metaheuristic Optimization and its Applications in Earth Sciences

NASA Astrophysics Data System (ADS)

Yang, Xin-She

2010-05-01

A common but challenging task in modelling geophysical and geological processes is to handle massive data and to minimize certain objectives. This can essentially be considered as an optimization problem, and thus many new efficient metaheuristic optimization algorithms can be used. In this paper, we will introduce some modern metaheuristic optimization algorithms such as genetic algorithms, harmony search, firefly algorithm, particle swarm optimization and simulated annealing. We will also discuss how these algorithms can be applied to various applications in earth sciences, including nonlinear least-squares, support vector machine, Kriging, inverse finite element analysis, and data-mining. We will present a few examples to show how different problems can be reformulated as optimization. Finally, we will make some recommendations for choosing various algorithms to suit various problems. References 1) D. H. Wolpert and W. G. Macready, No free lunch theorems for optimization, IEEE Trans. Evolutionary Computation, Vol. 1, 67-82 (1997). 2) X. S. Yang, Nature-Inspired Metaheuristic Algorithms, Luniver Press, (2008). 3) X. S. Yang, Mathematical Modelling for Earth Sciences, Dunedin Academic Press, (2008).

Improving scanner wafer alignment performance by target optimization

NASA Astrophysics Data System (ADS)

Leray, Philippe; Jehoul, Christiane; Socha, Robert; Menchtchikov, Boris; Raghunathan, Sudhar; Kent, Eric; Schoonewelle, Hielke; Tinnemans, Patrick; Tuffy, Paul; Belen, Jun; Wise, Rich

2016-03-01

In the process nodes of 10nm and below, the patterning complexity along with the processing and materials required has resulted in a need to optimize alignment targets in order to achieve the required precision, accuracy and throughput performance. Recent industry publications on the metrology target optimization process have shown a move from the expensive and time consuming empirical methodologies, towards a faster computational approach. ASML's Design for Control (D4C) application, which is currently used to optimize YieldStar diffraction based overlay (DBO) metrology targets, has been extended to support the optimization of scanner wafer alignment targets. This allows the necessary process information and design methodology, used for DBO target designs, to be leveraged for the optimization of alignment targets. In this paper, we show how we applied this computational approach to wafer alignment target design. We verify the correlation between predictions and measurements for the key alignment performance metrics and finally show the potential alignment and overlay performance improvements that an optimized alignment target could achieve.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

Optimal Solutions of Multiproduct Batch Chemical Process Using Multiobjective Genetic Algorithm with Expert Decision System

PubMed Central

Mokeddem, Diab; Khellaf, Abdelhafid

2009-01-01

Optimal design problem are widely known by their multiple performance measures that are often competing with each other. In this paper, an optimal multiproduct batch chemical plant design is presented. The design is firstly formulated as a multiobjective optimization problem, to be solved using the well suited non dominating sorting genetic algorithm (NSGA-II). The NSGA-II have capability to achieve fine tuning of variables in determining a set of non dominating solutions distributed along the Pareto front in a single run of the algorithm. The NSGA-II ability to identify a set of optimal solutions provides the decision-maker DM with a complete picture of the optimal solution space to gain better and appropriate choices. Then an outranking with PROMETHEE II helps the decision-maker to finalize the selection of a best compromise. The effectiveness of NSGA-II method with multiojective optimization problem is illustrated through two carefully referenced examples. PMID:19543537

Design of freeze-drying processes for pharmaceuticals: practical advice.

PubMed

Tang, Xiaolin; Pikal, Michael J

2004-02-01

Design of freeze-drying processes is often approached with a "trial and error" experimental plan or, worse yet, the protocol used in the first laboratory run is adopted without further attempts at optimization. Consequently, commercial freeze-drying processes are often neither robust nor efficient. It is our thesis that design of an "optimized" freeze-drying process is not particularly difficult for most products, as long as some simple rules based on well-accepted scientific principles are followed. It is the purpose of this review to discuss the scientific foundations of the freeze-drying process design and then to consolidate these principles into a set of guidelines for rational process design and optimization. General advice is given concerning common stability issues with proteins, but unusual and difficult stability issues are beyond the scope of this review. Control of ice nucleation and crystallization during the freezing step is discussed, and the impact of freezing on the rest of the process and final product quality is reviewed. Representative freezing protocols are presented. The significance of the collapse temperature and the thermal transition, denoted Tg', are discussed, and procedures for the selection of the "target product temperature" for primary drying are presented. Furthermore, guidelines are given for selection of the optimal shelf temperature and chamber pressure settings required to achieve the target product temperature without thermal and/or mass transfer overload of the freeze dryer. Finally, guidelines and "rules" for optimization of secondary drying and representative secondary drying protocols are presented.

Bicycle and pedestrian detection : final report

DOT National Transportation Integrated Search

2003-02-27

With the development of ITS applications, automated pedestrian detectors are beginning to compliment the existing pushbutton detectors. These applications optimize intersection operations and improve safety by reducing the conflicts between vehicles ...

A multi-objective optimization model for hub network design under uncertainty: An inexact rough-interval fuzzy approach

NASA Astrophysics Data System (ADS)

Niakan, F.; Vahdani, B.; Mohammadi, M.

2015-12-01

This article proposes a multi-objective mixed-integer model to optimize the location of hubs within a hub network design problem under uncertainty. The considered objectives include minimizing the maximum accumulated travel time, minimizing the total costs including transportation, fuel consumption and greenhouse emissions costs, and finally maximizing the minimum service reliability. In the proposed model, it is assumed that for connecting two nodes, there are several types of arc in which their capacity, transportation mode, travel time, and transportation and construction costs are different. Moreover, in this model, determining the capacity of the hubs is part of the decision-making procedure and balancing requirements are imposed on the network. To solve the model, a hybrid solution approach is utilized based on inexact programming, interval-valued fuzzy programming and rough interval programming. Furthermore, a hybrid multi-objective metaheuristic algorithm, namely multi-objective invasive weed optimization (MOIWO), is developed for the given problem. Finally, various computational experiments are carried out to assess the proposed model and solution approaches.

Optimization the composition of sand-lime products modified of diabase aggregate

NASA Astrophysics Data System (ADS)

Komisarczyk, K.; Stępień, A.

2017-10-01

The problem of optimizing the composition of building materials is currently of great importance due to the increasing competitiveness and technological development in the construction industry. This phenomenon also applies to catalog sand-lime. The respective arrangement of individual components or their equivalents, and linking them with the main parameters of the composition of the mixture, i.e. The lime/sand/water should lead to the intended purpose. The introduction of sand-lime diabase aggregate is concluded with a positive effect of final products. The paper presents the results of optimization with the addition of diabase aggregate. The constant value was the amount of water, variable - the mass of the dry ingredients. The program of experimental studies was taken for 6 series of silicates made in industrial conditions. Final samples were tested for mechanical and physico-chemical expanding the analysis of the mercury intrusion porosimetry, SEM and XRD. The results show that, depending on the aggregate’s contribution, exhibit differences. The sample in an amount of 10% diabase aggregate the compressive strength was higher than in the case of reference sample, while modified samples absorbed less water.

Modelling mid-course corrections for optimality conditions along interplanetary transfers

NASA Astrophysics Data System (ADS)

Iorfida, Elisabetta; Palmer, Phil; Roberts, Mark

2014-12-01

Within the field of trajectory optimisation, Lawden developed the primer vector theory, which defines a set of necessary conditions to characterise whether a transfer trajectory, in the two-body problem context, is optimum with respect to propellant usage. If the conditions are not satisfied, a region of the transfer trajectory is identified in which one or more potential intermediate impulses are performed in order to lower the overall cost. The method is computationally complex owing to having to solve a boundary value problem. In this paper is presented a new propagator that reduces the mathematical complexity and the computational cost of the problem, in particular it exploits a separation between the in-plane and out-of-plane components of the primer vector along the transfer trajectory. Using this propagator, the optimality of the transfer arc has been investigated, varying the departure and arrival orbits. In particular, keeping fixed the transfer trajectory, the optimality has been extensively analysed varying both the initial and final positions on the orbit, together with the directions of the initial and final thrust impulses.

Linear state feedback, quadratic weights, and closed loop eigenstructures. M.S. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1980-01-01

Equations are derived for the angles of general multivariable root loci and linear quadratic optimal root loci, including angles of departure and approach. The generalized eigenvalue problem is used to compute angles of approach. Equations are also derived to find the sensitivity of closed loop eigenvalue and the directional derivatives of closed loop eigenvectors. An equivalence class of quadratic weights that produce the same asymptotic eigenstructure is defined, a canonical element is defined, and an algorithm to find it is given. The behavior of the optimal root locus in the nonasymptotic region is shown to be different for quadratic weights with the same asymptotic properties. An algorithm is presented that can be used to select a feedback gain matrix for the linear state feedback problem which produces a specified asymptotic eigenstructure. Another algorithm is given to compute the asymptotic eigenstructure properties inherent in a given set of quadratic weights. Finally, it is shown that optimal root loci for nongeneric problems can be approximated by generic ones in the nonasymptotic region.

Simultaneous recovery of Ni and Cu from computer-printed circuit boards using bioleaching: statistical evaluation and optimization.

PubMed

Arshadi, M; Mousavi, S M

2014-12-01

Computer printed circuit boards (CPCBs) have a rich metal content and are produced in high volume, making them an important component of electronic waste. The present study used a pure culture of Acidithiobacillus ferrooxidans to leach Cu and Ni from CPCBs waste. The adaptation phase began at 1g/l CPCBs powder with 10% inoculation and final pulp density was reached at 20g/l after about 80d. Four effective factors including initial pH, particle size, pulp density, and initial Fe(3+) concentration were optimized to achieve maximum simultaneous recovery of Cu and Ni. Their interactions were also identified using central composite design in response surface methodology. The suggested optimal conditions were initial pH 3, initial Fe(3+) 8.4g/l, pulp density 20g/l and particle size 95μm. Nearly 100% of Cu and Ni were simultaneously recovered under optimum conditions. Finally, bacterial growth characteristics versus time at optimum conditions were plotted. Copyright © 2014 Elsevier Ltd. All rights reserved.

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Rajeeva; Kumar, Aditya; Dai, Dan

2012-12-31

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developedmore » will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.« less

An Optimization-based Atomistic-to-Continuum Coupling Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olson, Derek; Bochev, Pavel B.; Luskin, Mitchell

2014-08-21

In this paper, we present a new optimization-based method for atomistic-to-continuum (AtC) coupling. The main idea is to cast the latter as a constrained optimization problem with virtual Dirichlet controls on the interfaces between the atomistic and continuum subdomains. The optimization objective is to minimize the error between the atomistic and continuum solutions on the overlap between the two subdomains, while the atomistic and continuum force balance equations provide the constraints. Separation, rather then blending of the atomistic and continuum problems, and their subsequent use as constraints in the optimization problem distinguishes our approach from the existing AtC formulations. Finally,more » we present and analyze the method in the context of a one-dimensional chain of atoms modeled using a linearized two-body potential with next-nearest neighbor interactions.« less

Integration of Mesh Optimization with 3D All-Hex Mesh Generation, LDRD Subcase 3504340000, Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

KNUPP,PATRICK; MITCHELL,SCOTT A.

1999-11-01

In an attempt to automatically produce high-quality all-hex meshes, we investigated a mesh improvement strategy: given an initial poor-quality all-hex mesh, we iteratively changed the element connectivity, adding and deleting elements and nodes, and optimized the node positions. We found a set of hex reconnection primitives. We improved the optimization algorithms so they can untangle a negative-Jacobian mesh, even considering Jacobians on the boundary, and subsequently optimize the condition number of elements in an untangled mesh. However, even after applying both the primitives and optimization we were unable to produce high-quality meshes in certain regions. Our experiences suggest that manymore » boundary configurations of quadrilaterals admit no hexahedral mesh with positive Jacobians, although we have no proof of this.« less

Optimal Capacitor Bank Capacity and Placement in Distribution Systems with High Distributed Solar Power Penetration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodge, Brian S; Mather, Barry A; Cho, Gyu-Jung

Capacitor banks have been generally installed and utilized to support distribution voltage during period of higher load or on longer, higher impedance, feeders. Installations of distributed energy resources in distribution systems are rapidly increasing, and many of these generation resources have variable and uncertain power output. These generators can significantly change the voltage profile across a feeder, and therefore when a new capacitor bank is needed analysis of optimal capacity and location of the capacitor bank is required. In this paper, we model a particular distribution system including essential equipment. An optimization method is adopted to determine the best capacitymore » and location sets of the newly installed capacitor banks, in the presence of distributed solar power generation. Finally we analyze the optimal capacitor banks configuration through the optimization and simulation results.« less

Topology optimization of finite strain viscoplastic systems under transient loads

DOE PAGES

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

2018-02-08

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Structural Performance’s Optimally Analysing and Implementing Based on ANSYS Technology

NASA Astrophysics Data System (ADS)

Han, Na; Wang, Xuquan; Yue, Haifang; Sun, Jiandong; Wu, Yongchun

2017-06-01

Computer-aided Engineering (CAE) is a hotspot both in academic field and in modern engineering practice. Analysis System(ANSYS) simulation software for its excellent performance become outstanding one in CAE family, it is committed to the innovation of engineering simulation to help users to shorten the design process, improve product innovation and performance. Aimed to explore a structural performance’s optimally analyzing model for engineering enterprises, this paper introduced CAE and its development, analyzed the necessity for structural optimal analysis as well as the framework of structural optimal analysis on ANSYS Technology, used ANSYS to implement a reinforced concrete slab structural performance’s optimal analysis, which was display the chart of displacement vector and the chart of stress intensity. Finally, this paper compared ANSYS software simulation results with the measured results,expounded that ANSYS is indispensable engineering calculation tools.

Optimal modified tracking performance for MIMO networked control systems with communication constraints.

PubMed

Wu, Jie; Zhou, Zhu-Jun; Zhan, Xi-Sheng; Yan, Huai-Cheng; Ge, Ming-Feng

2017-05-01

This paper investigates the optimal modified tracking performance of multi-input multi-output (MIMO) networked control systems (NCSs) with packet dropouts and bandwidth constraints. Some explicit expressions are obtained by using co-prime factorization and the spectral decomposition technique. The obtained results show that the optimal modified tracking performance is related to the intrinsic properties of a given plant such as non-minimum phase (NMP) zeros, unstable poles, and their directions. Furthermore, the modified factor, packet dropouts probability and bandwidth also impact the optimal modified tracking performance of the NCSs. The optimal modified tracking performance with channel input power constraint is obtained by searching through all stabilizing two-parameter compensator. Finally, some typical examples are given to illustrate the effectiveness of the theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Optimized Solvent for Energy-Efficient, Environmentally-Friendly Capture of CO{sub 2} at Coal-Fired Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farthing, G. A.; Rimpf, L. M.

The overall goal of this project, as originally proposed, was to optimize the formulation of a novel solvent as a critical enabler for the cost-effective, energy-efficient, environmentally-friendly capture of CO{sub 2} at coal-fired utility plants. Aqueous blends of concentrated piperazine (PZ) with other compounds had been shown to exhibit high rates of CO{sub 2} absorption, low regeneration energy, and other desirable performance characteristics during an earlier 5-year development program conducted by B&W. The specific objective of this project was to identify PZ-based solvent formulations that globally optimize the performance of coal-fired power plants equipped with CO{sub 2} scrubbing systems. Whilemore » previous solvent development studies have tended to focus on energy consumption and absorber size, important issues to be sure, the current work seeks to explore, understand, and optimize solvent formulation across the full gamut of issues related to commercial application of the technology: capital and operating costs, operability, reliability, environmental, health and safety (EH&S), etc. Work on the project was intended to be performed under four budget periods. The objective of the work in the first budget period has been to identify several candidate formulations of a concentrated PZ-based solvent for detailed characterization and evaluation. Work in the second budget period would generate reliable and comprehensive property and performance data for the identified formulations. Work in the third budget period would quantify the expected performance of the selected formulations in a commercial CO{sub 2} scrubbing process. Finally, work in the fourth budget period would provide a final technology feasibility study and a preliminary technology EH&S assessment. Due to other business priorities, however, B&W has requested that this project be terminated at the end of the first budget period. This document therefore serves as the final report for this project. It is the first volume of the two-volume final report and summarizes Budget Period 1 accomplishments under Tasks 1-5 of the project, including the selection of four solvent formulations for further study.« less

Mission Operations Planning with Preferences: An Empirical Study

NASA Technical Reports Server (NTRS)

Bresina, John L.; Khatib, Lina; McGann, Conor

2006-01-01

This paper presents an empirical study of some nonexhaustive approaches to optimizing preferences within the context of constraint-based, mixed-initiative planning for mission operations. This work is motivated by the experience of deploying and operating the MAPGEN (Mixed-initiative Activity Plan GENerator) system for the Mars Exploration Rover Mission. Responsiveness to the user is one of the important requirements for MAPGEN, hence, the additional computation time needed to optimize preferences must be kept within reasonabble bounds. This was the primary motivation for studying non-exhaustive optimization approaches. The specific goals of rhe empirical study are to assess the impact on solution quality of two greedy heuristics used in MAPGEN and to assess the improvement gained by applying a linear programming optimization technique to the final solution.

On the use of topology optimization for improving heat transfer in molding process

NASA Astrophysics Data System (ADS)

Agazzi, A.; LeGoff, R.; Truc-Vu, C.

2016-10-01

In the plastic industry, one of the key factor is to control heat transfer. One way to achieve that goal is to design an effective cooling system. But in some area of the mold, where it is not possible to design cooling system, the use of a highly conductive material, such as copper pin, is often used. Most of the time, the location, the size and the quantity of the copper pin are made by empirical considerations, without using optimization procedures. In this article, it is proposed to use topology optimization, in order to improve transient conductive heat transfer in an injection/blowing mold. Two methodologies are applied and compared. Finally, the optimal distribution of cooper pin in the mold is given.

A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy.

PubMed

Sans, Victor; Porwol, Luzian; Dragone, Vincenza; Cronin, Leroy

2015-02-01

A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a modular LabView software control system for the hardware, NMR, data analysis and feedback optimization. Using this platform we report the real-time advanced structural characterization of reaction mixtures, including 19 F, 13 C, DEPT, 2D NMR spectroscopy (COSY, HSQC and 19 F-COSY) for the first time. Finally, the potential of this technique is demonstrated through the optimization of a catalytic organic reaction in real-time, showing its applicability to self-optimizing systems using criteria such as stereoselectivity, multi-nuclear measurements or 2D correlations.

Optimal impulsive time-fixed orbital rendezvous and interception with path constraints

NASA Technical Reports Server (NTRS)

Taur, D.-R.; Prussing, J. E.; Coverstone-Carroll, V.

1990-01-01

Minimum-fuel, impulsive, time-fixed solutions are obtained for the problem of orbital rendezvous and interception with interior path constraints. Transfers between coplanar circular orbits in an inverse-square gravitational field are considered, subject to a circular path constraint representing a minimum or maximum permissible orbital radius. Primer vector theory is extended to incorporate path constraints. The optimal number of impulses, their times and positions, and the presence of initial or final coasting arcs are determined. The existence of constraint boundary arcs and boundary points is investigated as well as the optimality of a class of singular arc solutions. To illustrate the complexities introduced by path constraints, an analysis is made of optimal rendezvous in field-free space subject to a minimum radius constraint.

Design optimization of gas generator hybrid propulsion boosters

NASA Technical Reports Server (NTRS)

Weldon, Vincent; Phillips, Dwight U.; Fink, Lawrence E.

1990-01-01

A methodology used in support of a contract study for NASA/MSFC to optimize the design of gas generator hybrid propulsion booster for uprating the National Space Transportation System (NSTS) is presented. The objective was to compare alternative configurations for this booster approach, optimizing each candidate concept on different bases, in order to develop data for a trade table on which a final decision was based. The methodology is capable of processing a large number of independent and dependent variables, adjusting the overall subsystems characteristics to arrive at a best compromise integrated design to meet various specified optimization criteria subject to selected constraints. For each system considered, a detailed weight statement was generated along with preliminary cost and reliability estimates.

Reliability-based trajectory optimization using nonintrusive polynomial chaos for Mars entry mission

NASA Astrophysics Data System (ADS)

Huang, Yuechen; Li, Haiyang

2018-06-01

This paper presents the reliability-based sequential optimization (RBSO) method to settle the trajectory optimization problem with parametric uncertainties in entry dynamics for Mars entry mission. First, the deterministic entry trajectory optimization model is reviewed, and then the reliability-based optimization model is formulated. In addition, the modified sequential optimization method, in which the nonintrusive polynomial chaos expansion (PCE) method and the most probable point (MPP) searching method are employed, is proposed to solve the reliability-based optimization problem efficiently. The nonintrusive PCE method contributes to the transformation between the stochastic optimization (SO) and the deterministic optimization (DO) and to the approximation of trajectory solution efficiently. The MPP method, which is used for assessing the reliability of constraints satisfaction only up to the necessary level, is employed to further improve the computational efficiency. The cycle including SO, reliability assessment and constraints update is repeated in the RBSO until the reliability requirements of constraints satisfaction are satisfied. Finally, the RBSO is compared with the traditional DO and the traditional sequential optimization based on Monte Carlo (MC) simulation in a specific Mars entry mission to demonstrate the effectiveness and the efficiency of the proposed method.

On-Board Real-Time Optimization Control for Turbo-Fan Engine Life Extending

NASA Astrophysics Data System (ADS)

Zheng, Qiangang; Zhang, Haibo; Miao, Lizhen; Sun, Fengyong

2017-11-01

A real-time optimization control method is proposed to extend turbo-fan engine service life. This real-time optimization control is based on an on-board engine mode, which is devised by a MRR-LSSVR (multi-input multi-output recursive reduced least squares support vector regression method). To solve the optimization problem, a FSQP (feasible sequential quadratic programming) algorithm is utilized. The thermal mechanical fatigue is taken into account during the optimization process. Furthermore, to describe the engine life decaying, a thermal mechanical fatigue model of engine acceleration process is established. The optimization objective function not only contains the sub-item which can get fast response of the engine, but also concludes the sub-item of the total mechanical strain range which has positive relationship to engine fatigue life. Finally, the simulations of the conventional optimization control which just consider engine acceleration performance or the proposed optimization method have been conducted. The simulations demonstrate that the time of the two control methods from idle to 99.5 % of the maximum power are equal. However, the engine life using the proposed optimization method could be surprisingly increased by 36.17 % compared with that using conventional optimization control.

Thermally Optimized Paradigm of Thermal Management (TOP-M)

DTIC Science & Technology

2017-07-18

ELEMENT NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 6. AUTHOR(S) 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) 8...19b. TELEPHONE NUMBER (Include area code) 18-07-2017 Final Technical Jul 2015 - Jul 2017 NICOP - Thermally Optimized Paradigm of Thermal Management ...The main goal of this research was to present a New Thermal Management Approach, which combines thermally aware Very/Ultra Large Scale Integration

Evaluation of Environmental Information Products for Search and Rescue Optimal Planning System (SAROPS) - Version for Public Release

DTIC Science & Technology

2008-02-01

is called EFS-POM. EFS-POM is forced by surface atmospheric forcing (wind, heating / cooling , sea level pressure) and by boundary forcing derived from...Peter Olsson, University of Alaska Anchorage. Heating and cooling is given by the climatological monthly heat flux from COADS (Comprehensive Ocean...Environmental Information Products for Search and Rescue Optimal Planning System (SAROPS) - Version for Public Release FINAL REPORT February

Multidisciplinary Shape Optimization of a Composite Blended Wing Body Aircraft

NASA Astrophysics Data System (ADS)

Boozer, Charles Maxwell

A multidisciplinary shape optimization tool coupling aerodynamics, structure, and performance was developed for battery powered aircraft. Utilizing high-fidelity computational fluid dynamics analysis tools and a structural wing weight tool, coupled based on the multidisciplinary feasible optimization architecture; aircraft geometry is modified in the optimization of the aircraft's range or endurance. The developed tool is applied to three geometries: a hybrid blended wing body, delta wing UAS, the ONERA M6 wing, and a modified ONERA M6 wing. First, the optimization problem is presented with the objective function, constraints, and design vector. Next, the tool's architecture and the analysis tools that are utilized are described. Finally, various optimizations are described and their results analyzed for all test subjects. Results show that less computationally expensive inviscid optimizations yield positive performance improvements using planform, airfoil, and three-dimensional degrees of freedom. From the results obtained through a series of optimizations, it is concluded that the newly developed tool is both effective at improving performance and serves as a platform ready to receive additional performance modules, further improving its computational design support potential.

Genetic algorithm to optimize the design of main combustor and gas generator in liquid rocket engines

NASA Astrophysics Data System (ADS)

Son, Min; Ko, Sangho; Koo, Jaye

2014-06-01

A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was applied, and the profile was calculated using Rao's method. One-dimensional heat transfer was assumed along the profile, and cooling channels were designed. For the gas-generator design, non-equilibrium properties were derived from a counterflow analysis, and a vaporization model for the fuel droplet was adopted to calculate residence time. Finally, a genetic algorithm was adopted to optimize the designs. The combustor and gas generator were optimally designed for 30-tonf, 75-tonf, and 150-tonf engines. The optimized combustors demonstrated superior design characteristics when compared with previous non-optimized results. Wall temperatures at the nozzle throat were optimized to satisfy the requirement of 800 K, and specific impulses were maximized. In addition, the target turbine power and a burned-gas temperature of 1000 K were obtained from the optimized gas-generator design.

Trajectory Design Employing Convex Optimization for Landing on Irregularly Shaped Asteroids

NASA Technical Reports Server (NTRS)

Pinson, Robin M.; Lu, Ping

2016-01-01

Mission proposals that land spacecraft on asteroids are becoming increasingly popular. However, in order to have a successful mission the spacecraft must reliably and softly land at the intended landing site with pinpoint precision. The problem under investigation is how to design a propellant optimal powered descent trajectory that can be quickly computed onboard the spacecraft, without interaction from the ground control. The propellant optimal control problem in this work is to determine the optimal finite thrust vector to land the spacecraft at a specified location, in the presence of a highly nonlinear gravity field, subject to various mission and operational constraints. The proposed solution uses convex optimization, a gravity model with higher fidelity than Newtonian, and an iterative solution process for a fixed final time problem. In addition, a second optimization method is wrapped around the convex optimization problem to determine the optimal flight time that yields the lowest propellant usage over all flight times. Gravity models designed for irregularly shaped asteroids are investigated. Success of the algorithm is demonstrated by designing powered descent trajectories for the elongated binary asteroid Castalia.

Towards Excellence in Asthma Management: Final report of an eight-year program aimed at reducing care gaps in asthma management in Quebec

PubMed Central

Boulet, Louis-Philippe; Dorval, Eileen; Labrecque, Manon; Turgeon, Michel; Montague, Terrence; Thivierge, Robert L

2008-01-01

BACKGROUND AND OBJECTIVES: Asthma care in Canada and around the world persistently falls short of optimal treatment. To optimize care, a systematic approach to identifying such shortfalls or ‘care gaps’, in which all stakeholders of the health care system (including patients) are involved, was proposed. METHODS: Several projects of a multipartner, multidisciplinary disease management program, developed to optimize asthma care in Quebec, was conducted in a period of eight years. First, two population maps were produced to identify regional variations in asthma-related morbidity and to prioritize interventions for improving treatment. Second, current care was evaluated in a physician-patient cohort, confirming the many care gaps in asthma management. Third, two series of peer-reviewed outcome studies, targeting high-risk populations and specific asthma care gaps, were conducted. Finally, a process to integrate the best interventions into the health care system and an agenda for further research on optimal asthma management were proposed. RESULTS: Key observations from these studies included the identification of specific patterns of noncompliance in using inhaled corticosteroids, the failure of increased access to spirometry in asthma education centres to increase the number of education referrals, the transient improvement in educational abilities of nurses involved with an asthma hotline telephone service, and the beneficial effects of practice tools aimed at facilitating the assessment of asthma control and treatment needs by general practitioners. CONCLUSIONS: Disease management programs such as Towards Excellence in Asthma Management can provide valuable information on optimal strategies for improving treatment of asthma and other chronic diseases by identifying care gaps, improving guidelines implementation and optimizing care. PMID:18818784

A Framework for Final Drive Simultaneous Failure Diagnosis Based on Fuzzy Entropy and Sparse Bayesian Extreme Learning Machine

PubMed Central

Ye, Qing; Pan, Hao; Liu, Changhua

2015-01-01

This research proposes a novel framework of final drive simultaneous failure diagnosis containing feature extraction, training paired diagnostic models, generating decision threshold, and recognizing simultaneous failure modes. In feature extraction module, adopt wavelet package transform and fuzzy entropy to reduce noise interference and extract representative features of failure mode. Use single failure sample to construct probability classifiers based on paired sparse Bayesian extreme learning machine which is trained only by single failure modes and have high generalization and sparsity of sparse Bayesian learning approach. To generate optimal decision threshold which can convert probability output obtained from classifiers into final simultaneous failure modes, this research proposes using samples containing both single and simultaneous failure modes and Grid search method which is superior to traditional techniques in global optimization. Compared with other frequently used diagnostic approaches based on support vector machine and probability neural networks, experiment results based on F 1-measure value verify that the diagnostic accuracy and efficiency of the proposed framework which are crucial for simultaneous failure diagnosis are superior to the existing approach. PMID:25722717

Ultrasound-assisted extraction of amino acids from grapes.

PubMed

Carrera, Ceferino; Ruiz-Rodríguez, Ana; Palma, Miguel; Barroso, Carmelo G

2015-01-01

Recent cultivar techniques on vineyards can have a marked influence on the final nitrogen content of grapes, specifically individual amino acid contents. Furthermore, individual amino acid contents in grapes are related to the final aromatic composition of wines. A new ultrasound-assisted method for the extraction of amino acids from grapes has been developed. Several extraction variables, including solvent (water/ethanol mixtures), solvent pH (2-7), temperature (10-70°C), ultrasonic power (20-70%) and ultrasonic frequency (0.2-1.0s(-)(1)), were optimized to guarantee full recovery of the amino acids from grapes. An experimental design was employed to optimize the extraction parameters. The surface response methodology was used to evaluate the effects of the extraction variables. The analytical properties of the new method were established, including limit of detection (average value 1.4mmolkg(-)(1)), limit of quantification (average value 2.6mmolkg(-)(1)), repeatability (average RSD=12.9%) and reproducibility (average RSD=15.7%). Finally, the new method was applied to three cultivars of white grape throughout the ripening period. Copyright © 2014 Elsevier B.V. All rights reserved.

Constrained simultaneous multi-state reconfigurable wing structure configuration optimization

NASA Astrophysics Data System (ADS)

Snyder, Matthew

A reconfigurable aircraft is capable of in-flight shape change to increase mission performance or provide multi-mission capability. Reconfigurability has always been a consideration in aircraft design, from the Wright Flyer, to the F-14, and most recently the Lockheed-Martin folding wing concept. The Wright Flyer used wing-warping for roll control, the F-14 had a variable-sweep wing to improve supersonic flight capabilities, and the Lockheed-Martin folding wing demonstrated radical in-flight shape change. This dissertation will examine two questions that aircraft reconfigurability raises, especially as reconfiguration increases in complexity. First, is there an efficient method to develop a light weight structure which supports all the loads generated by each configuration? Second, can this method include the capability to propose a sub-structure topology that weighs less than other considered designs? The first question requires a method that will design and optimize multiple configurations of a reconfigurable aerostructure. Three options exist, this dissertation will show one is better than the others. Simultaneous optimization considers all configurations and their respective load cases and constraints at the same time. Another method is sequential optimization which considers each configuration of the vehicle one after the other - with the optimum design variable values from the first configuration becoming the lower bounds for subsequent configurations. This process repeats for each considered configuration and the lower bounds update as necessary. The third approach is aggregate combination — this method keeps the thickness or area of each member for the most critical configuration, the configuration that requires the largest cross-section. This research will show that simultaneous optimization produces a lower weight and different topology for the considered structures when compared to the sequential and aggregate techniques. To answer the second question, the developed optimization algorithm combines simultaneous optimization with a new method for determining the optimum location of the structural members of the sub-structure. The method proposed here considers an over-populated structural model, one in which there are initially more members than necessary. Using a unique iterative process, the optimization algorithm removes members from the design if they do not carry enough load to justify their presence. The initial set of members includes ribs, spars and a series of cross-members that diagonally connect the ribs and spars. The final result is a different structure, which is lower weight than one developed from sequential optimization or aggregate combination, and suggests the primary load paths. Chapter 1 contains background information on reconfigurable aircraft and a description of the new reconfigurable air vehicle being considered by the Air Vehicles Directorate of the Air Force Research Laboratory. This vehicle serves as a platform to test the proposed optimization process. Chapters 2 and 3 overview the optimization method and Chapter 4 provides some background analysis which is unique to this particular reconfigurable air vehicle. Chapter 5 contains the results of the optimizations and demonstrates how changing constraints or initial configuration impacts the final weight and topology of the wing structure. The final chapter contains conclusions and comments on some future work which would further enhance the effectiveness of the simultaneous reconfigurable structural topology optimization process developed and used in this dissertation.

A combined NLP-differential evolution algorithm approach for the optimization of looped water distribution systems

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.

2011-08-01

This paper proposes a novel optimization approach for the least cost design of looped water distribution systems (WDSs). Three distinct steps are involved in the proposed optimization approach. In the first step, the shortest-distance tree within the looped network is identified using the Dijkstra graph theory algorithm, for which an extension is proposed to find the shortest-distance tree for multisource WDSs. In the second step, a nonlinear programming (NLP) solver is employed to optimize the pipe diameters for the shortest-distance tree (chords of the shortest-distance tree are allocated the minimum allowable pipe sizes). Finally, in the third step, the original looped water network is optimized using a differential evolution (DE) algorithm seeded with diameters in the proximity of the continuous pipe sizes obtained in step two. As such, the proposed optimization approach combines the traditional deterministic optimization technique of NLP with the emerging evolutionary algorithm DE via the proposed network decomposition. The proposed methodology has been tested on four looped WDSs with the number of decision variables ranging from 21 to 454. Results obtained show the proposed approach is able to find optimal solutions with significantly less computational effort than other optimization techniques.

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

NASA Astrophysics Data System (ADS)

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.

Near-Optimal Guidance Method for Maximizing the Reachable Domain of Gliding Aircraft

NASA Astrophysics Data System (ADS)

Tsuchiya, Takeshi

This paper proposes a guidance method for gliding aircraft by using onboard computers to calculate a near-optimal trajectory in real-time, and thereby expanding the reachable domain. The results are applicable to advanced aircraft and future space transportation systems that require high safety. The calculation load of the optimal control problem that is used to maximize the reachable domain is too large for current computers to calculate in real-time. Thus the optimal control problem is divided into two problems: a gliding distance maximization problem in which the aircraft motion is limited to a vertical plane, and an optimal turning flight problem in a horizontal direction. First, the former problem is solved using a shooting method. It can be solved easily because its scale is smaller than that of the original problem, and because some of the features of the optimal solution are obtained in the first part of this paper. Next, in the latter problem, the optimal bank angle is computed from the solution of the former; this is an analytical computation, rather than an iterative computation. Finally, the reachable domain obtained from the proposed near-optimal guidance method is compared with that obtained from the original optimal control problem.

SoMIR framework for designing high-NDBP photonic crystal waveguides.

PubMed

Mirjalili, Seyed Mohammad

2014-06-20

This work proposes a modularized framework for designing the structure of photonic crystal waveguides (PCWs) and reducing human involvement during the design process. The proposed framework consists of three main modules: parameters module, constraints module, and optimizer module. The first module is responsible for defining the structural parameters of a given PCW. The second module defines various limitations in order to achieve desirable optimum designs. The third module is the optimizer, in which a numerical optimization method is employed to perform optimization. As case studies, two new structures called Ellipse PCW (EPCW) and Hypoellipse PCW (HPCW) with different shape of holes in each row are proposed and optimized by the framework. The calculation results show that the proposed framework is able to successfully optimize the structures of the new EPCW and HPCW. In addition, the results demonstrate the applicability of the proposed framework for optimizing different PCWs. The results of the comparative study show that the optimized EPCW and HPCW provide 18% and 9% significant improvements in normalized delay-bandwidth product (NDBP), respectively, compared to the ring-shape-hole PCW, which has the highest NDBP in the literature. Finally, the simulations of pulse propagation confirm the manufacturing feasibility of both optimized structures.

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

An Optimization System with Parallel Processing for Reducing Common-Mode Current on Electronic Control Unit

NASA Astrophysics Data System (ADS)

Okazaki, Yuji; Uno, Takanori; Asai, Hideki

In this paper, we propose an optimization system with parallel processing for reducing electromagnetic interference (EMI) on electronic control unit (ECU). We adopt simulated annealing (SA), genetic algorithm (GA) and taboo search (TS) to seek optimal solutions, and a Spice-like circuit simulator to analyze common-mode current. Therefore, the proposed system can determine the adequate combinations of the parasitic inductance and capacitance values on printed circuit board (PCB) efficiently and practically, to reduce EMI caused by the common-mode current. Finally, we apply the proposed system to an example circuit to verify the validity and efficiency of the system.

Process-time Optimization of Vacuum Degassing Using a Genetic Alloy Design Approach

PubMed Central

Dilner, David; Lu, Qi; Mao, Huahai; Xu, Wei; van der Zwaag, Sybrand; Selleby, Malin

2014-01-01

This paper demonstrates the use of a new model consisting of a genetic algorithm in combination with thermodynamic calculations and analytical process models to minimize the processing time during a vacuum degassing treatment of liquid steel. The model sets multiple simultaneous targets for final S, N, O, Si and Al levels and uses the total slag mass, the slag composition, the steel composition and the start temperature as optimization variables. The predicted optimal conditions agree well with industrial practice. For those conditions leading to the shortest process time the target compositions for S, N and O are reached almost simultaneously. PMID:28788286

Optimal Sensor Location Design for Reliable Fault Detection in Presence of False Alarms

PubMed Central

Yang, Fan; Xiao, Deyun; Shah, Sirish L.

2009-01-01

To improve fault detection reliability, sensor location should be designed according to an optimization criterion with constraints imposed by issues of detectability and identifiability. Reliability requires the minimization of undetectability and false alarm probability due to random factors on sensor readings, which is not only related with sensor readings but also affected by fault propagation. This paper introduces the reliability criteria expression based on the missed/false alarm probability of each sensor and system topology or connectivity derived from the directed graph. The algorithm for the optimization problem is presented as a heuristic procedure. Finally, a boiler system is illustrated using the proposed method. PMID:22291524

Analysis and optimization of hybrid excitation permanent magnet synchronous generator for stand-alone power system

NASA Astrophysics Data System (ADS)

Wang, Huijun; Qu, Zheng; Tang, Shaofei; Pang, Mingqi; Zhang, Mingju

2017-08-01

In this paper, electromagnetic design and permanent magnet shape optimization for permanent magnet synchronous generator with hybrid excitation are investigated. Based on generator structure and principle, design outline is presented for obtaining high efficiency and low voltage fluctuation. In order to realize rapid design, equivalent magnetic circuits for permanent magnet and iron poles are developed. At the same time, finite element analysis is employed. Furthermore, by means of design of experiment (DOE) method, permanent magnet is optimized to reduce voltage waveform distortion. Finally, the validity of proposed design methods is validated by the analytical and experimental results.

Sculpt test problem analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sweetser, John David

2013-10-01

This report details Sculpt's implementation from a user's perspective. Sculpt is an automatic hexahedral mesh generation tool developed at Sandia National Labs by Steve Owen. 54 predetermined test cases are studied while varying the input parameters (Laplace iterations, optimization iterations, optimization threshold, number of processors) and measuring the quality of the resultant mesh. This information is used to determine the optimal input parameters to use for an unknown input geometry. The overall characteristics are covered in Chapter 1. The speci c details of every case are then given in Appendix A. Finally, example Sculpt inputs are given in B.1 andmore » B.2.« less

Optimal control strategy for an impulsive stochastic competition system with time delays and jumps

NASA Astrophysics Data System (ADS)

Liu, Lidan; Meng, Xinzhu; Zhang, Tonghua

2017-07-01

Driven by both white and jump noises, a stochastic delayed model with two competitive species in a polluted environment is proposed and investigated. By using the comparison theorem of stochastic differential equations and limit superior theory, sufficient conditions for persistence in mean and extinction of two species are established. In addition, we obtain that the system is asymptotically stable in distribution by using ergodic method. Furthermore, the optimal harvesting effort and the maximum of expectation of sustainable yield (ESY) are derived from Hessian matrix method and optimal harvesting theory of differential equations. Finally, some numerical simulations are provided to illustrate the theoretical results.

Design of spoke type motor and magnetizer for improving efficiency based rare-earth-free permanent-magnet motor

NASA Astrophysics Data System (ADS)

Kim, Young Hyun; Cheon, Byung Chul; Lee, Jung Ho

2018-05-01

This study proposes criteria for both optimal-shape and magnetizer-system designs to be used for a high-output spoke-type motor. The study also examines methods of reducing high-cogging torque and torque ripple, to prevent noise and vibration. The optimal design of the stator and rotor can be enhanced using both a response surface method and finite element method. In addition, a magnetizer system is optimally designed for the magnetization of permanent magnets for use in the motor. Finally, this study verifies that the proposed motor can efficiently replace interior permanent magnet synchronous motor in many industries.

Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling

PubMed Central

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220

Discrete bat algorithm for optimal problem of permutation flow shop scheduling.

PubMed

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.

Aerodynamic Shape Optimization Using Hybridized Differential Evolution

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2003-01-01

An aerodynamic shape optimization method that uses an evolutionary algorithm known at Differential Evolution (DE) in conjunction with various hybridization strategies is described. DE is a simple and robust evolutionary strategy that has been proven effective in determining the global optimum for several difficult optimization problems. Various hybridization strategies for DE are explored, including the use of neural networks as well as traditional local search methods. A Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the hybrid DE optimizer. The method is implemented on distributed parallel computers so that new designs can be obtained within reasonable turnaround times. Results are presented for the inverse design of a turbine airfoil from a modern jet engine. (The final paper will include at least one other aerodynamic design application). The capability of the method to search large design spaces and obtain the optimal airfoils in an automatic fashion is demonstrated.

Data-driven sensor placement from coherent fluid structures

NASA Astrophysics Data System (ADS)

Manohar, Krithika; Kaiser, Eurika; Brunton, Bingni W.; Kutz, J. Nathan; Brunton, Steven L.

2017-11-01

Optimal sensor placement is a central challenge in the prediction, estimation and control of fluid flows. We reinterpret sensor placement as optimizing discrete samples of coherent fluid structures for full state reconstruction. This permits a drastic reduction in the number of sensors required for faithful reconstruction, since complex fluid interactions can often be described by a small number of coherent structures. Our work optimizes point sensors using the pivoted matrix QR factorization to sample coherent structures directly computed from flow data. We apply this sampling technique in conjunction with various data-driven modal identification methods, including the proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD). In contrast to POD-based sensors, DMD demonstrably enables the optimization of sensors for prediction in systems exhibiting multiple scales of dynamics. Finally, reconstruction accuracy from pivot sensors is shown to be competitive with sensors obtained using traditional computationally prohibitive optimization methods.

Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles

NASA Astrophysics Data System (ADS)

Aghababa, Mohammad Pourmahmood; Amrollahi, Mohammad Hossein; Borjkhani, Mehdi

2012-09-01

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Efficient Coproduction of Mannanase and Cellulase by the Transformation of a Codon-Optimized Endomannanase Gene from Aspergillus niger into Trichoderma reesei.

PubMed

Sun, Xianhua; Xue, Xianli; Li, Mengzhu; Gao, Fei; Hao, Zhenzhen; Huang, Huoqing; Luo, Huiying; Qin, Lina; Yao, Bin; Su, Xiaoyun

2017-12-20

Cellulase and mannanase are both important enzyme additives in animal feeds. Expressing the two enzymes simultaneously within one microbial host could potentially lead to cost reductions in the feeding of animals. For this purpose, we codon-optimized the Aspergillus niger Man5A gene to the codon-usage bias of Trichoderma reesei. By comparing the free energies and the local structures of the nucleotide sequences, one optimized sequence was finally selected and transformed into the T. reesei pyridine-auxotrophic strain TU-6. The codon-optimized gene was expressed to a higher level than the original one. Further expressing the codon-optimized gene in a mutated T. reesei strain through fed-batch cultivation resulted in coproduction of cellulase and mannanase up to 1376 U·mL -1 and 1204 U·mL -1 , respectively.

Robust Optimization Design for Turbine Blade-Tip Radial Running Clearance using Hierarchically Response Surface Method

NASA Astrophysics Data System (ADS)

Zhiying, Chen; Ping, Zhou

2017-11-01

Considering the robust optimization computational precision and efficiency for complex mechanical assembly relationship like turbine blade-tip radial running clearance, a hierarchically response surface robust optimization algorithm is proposed. The distribute collaborative response surface method is used to generate assembly system level approximation model of overall parameters and blade-tip clearance, and then a set samples of design parameters and objective response mean and/or standard deviation is generated by using system approximation model and design of experiment method. Finally, a new response surface approximation model is constructed by using those samples, and this approximation model is used for robust optimization process. The analyses results demonstrate the proposed method can dramatic reduce the computational cost and ensure the computational precision. The presented research offers an effective way for the robust optimization design of turbine blade-tip radial running clearance.

Customer demand prediction of service-oriented manufacturing using the least square support vector machine optimized by particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Cao, Jin; Jiang, Zhibin; Wang, Kangzhou

2017-07-01

Many nonlinear customer satisfaction-related factors significantly influence the future customer demand for service-oriented manufacturing (SOM). To address this issue and enhance the prediction accuracy, this article develops a novel customer demand prediction approach for SOM. The approach combines the phase space reconstruction (PSR) technique with the optimized least square support vector machine (LSSVM). First, the prediction sample space is reconstructed by the PSR to enrich the time-series dynamics of the limited data sample. Then, the generalization and learning ability of the LSSVM are improved by the hybrid polynomial and radial basis function kernel. Finally, the key parameters of the LSSVM are optimized by the particle swarm optimization algorithm. In a real case study, the customer demand prediction of an air conditioner compressor is implemented. Furthermore, the effectiveness and validity of the proposed approach are demonstrated by comparison with other classical predication approaches.

Vitamin B12 production from crude glycerol by Propionibacterium freudenreichii ssp. shermanii: optimization of medium composition through statistical experimental designs.

PubMed

Kośmider, Alicja; Białas, Wojciech; Kubiak, Piotr; Drożdżyńska, Agnieszka; Czaczyk, Katarzyna

2012-02-01

A two-step statistical experimental design was employed to optimize the medium for vitamin B(12) production from crude glycerol by Propionibacterium freudenreichii ssp. shermanii. In the first step, using Plackett-Burman design, five of 13 tested medium components (calcium pantothenate, NaH(2)PO(4)·2H(2)O, casein hydrolysate, glycerol and FeSO(4)·7H(2)O) were identified as factors having significant influence on vitamin production. In the second step, a central composite design was used to optimize levels of medium components selected in the first step. Valid statistical models describing the influence of significant factors on vitamin B(12) production were established for each optimization phase. The optimized medium provided a 93% increase in final vitamin concentration compared to the original medium. Copyright © 2011 Elsevier Ltd. All rights reserved.

Cuckoo Search Algorithm Based on Repeat-Cycle Asymptotic Self-Learning and Self-Evolving Disturbance for Function Optimization

PubMed Central

Wang, Jie-sheng; Li, Shu-xia; Song, Jiang-di

2015-01-01

In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more careful and thorough search near the bird's nests location. In order to select a reasonable repeat-cycled disturbance number, a further study on the choice of disturbance times is made. Finally, six typical test functions are adopted to carry out simulation experiments, meanwhile, compare algorithms of this paper with two typical swarm intelligence algorithms particle swarm optimization (PSO) algorithm and artificial bee colony (ABC) algorithm. The results show that the improved cuckoo search algorithm has better convergence velocity and optimization accuracy. PMID:26366164

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

PubMed Central

Wang, Jie-Sheng; Han, Shuang

2015-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:26583034

Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

PubMed

Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

2017-02-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

Optimization study on the primary mirror lightweighting of a remote sensing instrument

NASA Astrophysics Data System (ADS)

Chan, Chia-Yen; Huang, Bo-Kai; You, Zhen-Ting; Chen, Yi-Cheng; Huang, Ting-Ming

2015-07-01

Remote sensing instrument (RSI) is used to take images for ground surface observation, which will be exposed to high vacuum, high temperature difference, gravity, 15 g-force and random vibration conditions and other harsh environments during operation. While designing a RSI optical system, not only the optical quality but also the strength of mechanical structure we should be considered. As a result, an optimization method is adopted to solve this engineering problem. In the study, a ZERODUR® mirror with a diameter of 466 mm has been chosen as the model and the optimization has been executed by combining the computer-aided design, finite element analysis, and parameter optimization software. The optimization is aimed to obtain the most lightweight mirror with maintaining structural rigidity and good optical quality. Finally, the optimum optical mirror with a lightweight ratio of 0.55 is attained successfully.

Optimal charge control strategies for stationary photovoltaic battery systems

NASA Astrophysics Data System (ADS)

Li, Jiahao; Danzer, Michael A.

2014-07-01

Battery systems coupled to photovoltaic (PV) modules for example fulfill one major function: they locally decouple PV generation and consumption of electrical power leading to two major effects. First, they reduce the grid load, especially at peak times and therewith reduce the necessity of a network expansion. And second, they increase the self-consumption in households and therewith help to reduce energy expenses. For the management of PV batteries charge control strategies need to be developed to reach the goals of both the distribution system operators and the local power producer. In this work optimal control strategies regarding various optimization goals are developed on the basis of the predicted household loads and PV generation profiles using the method of dynamic programming. The resulting charge curves are compared and essential differences discussed. Finally, a multi-objective optimization shows that charge control strategies can be derived that take all optimization goals into account.

Optimal mode transformations for linear-optical cluster-state generation

DOE PAGES

Uskov, Dmitry B.; Lougovski, Pavel; Alsing, Paul M.; ...

2015-06-15

In this paper, we analyze the generation of linear-optical cluster states (LOCSs) via sequential addition of one and two qubits. Existing approaches employ the stochastic linear-optical two-qubit controlled-Z (CZ) gate with success rate of 1/9 per operation. The question of optimality of the CZ gate with respect to LOCS generation has remained open. We report that there are alternative schemes to the CZ gate that are exponentially more efficient and show that sequential LOCS growth is indeed globally optimal. We find that the optimal cluster growth operation is a state transformation on a subspace of the full Hilbert space. Finally,more » we show that the maximal success rate of postselected entangling n photonic qubits or m Bell pairs into a cluster is (1/2) n-1 and (1/4) m-1, respectively, with no ancilla photons, and we give an explicit optical description of the optimal mode transformations.« less

Homotopy approach to optimal, linear quadratic, fixed architecture compensation

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1991-01-01

Optimal linear quadratic Gaussian compensators with constrained architecture are a sensible way to generate good multivariable feedback systems meeting strict implementation requirements. The optimality conditions obtained from the constrained linear quadratic Gaussian are a set of highly coupled matrix equations that cannot be solved algebraically except when the compensator is centralized and full order. An alternative to the use of general parameter optimization methods for solving the problem is to use homotopy. The benefit of the method is that it uses the solution to a simplified problem as a starting point and the final solution is then obtained by solving a simple differential equation. This paper investigates the convergence properties and the limitation of such an approach and sheds some light on the nature and the number of solutions of the constrained linear quadratic Gaussian problem. It also demonstrates the usefulness of homotopy on an example of an optimal decentralized compensator.

Simulation Research on Vehicle Active Suspension Controller Based on G1 Method

NASA Astrophysics Data System (ADS)

Li, Gen; Li, Hang; Zhang, Shuaiyang; Luo, Qiuhui

2017-09-01

Based on the order relation analysis method (G1 method), the optimal linear controller of vehicle active suspension is designed. The system of the main and passive suspension of the single wheel vehicle is modeled and the system input signal model is determined. Secondly, the system motion state space equation is established by the kinetic knowledge and the optimal linear controller design is completed with the optimal control theory. The weighting coefficient of the performance index coefficients of the main passive suspension is determined by the relational analysis method. Finally, the model is simulated in Simulink. The simulation results show that: the optimal weight value is determined by using the sequence relation analysis method under the condition of given road conditions, and the vehicle acceleration, suspension stroke and tire motion displacement are optimized to improve the comprehensive performance of the vehicle, and the active control is controlled within the requirements.

Adaptive dynamic programming for finite-horizon optimal control of discrete-time nonlinear systems with ε-error bound.

PubMed

Wang, Fei-Yue; Jin, Ning; Liu, Derong; Wei, Qinglai

2011-01-01

In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an ε-error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method.

Active and Reactive Power Optimal Dispatch Associated with Load and DG Uncertainties in Active Distribution Network

NASA Astrophysics Data System (ADS)

Gao, F.; Song, X. H.; Zhang, Y.; Li, J. F.; Zhao, S. S.; Ma, W. Q.; Jia, Z. Y.

2017-05-01

In order to reduce the adverse effects of uncertainty on optimal dispatch in active distribution network, an optimal dispatch model based on chance-constrained programming is proposed in this paper. In this model, the active and reactive power of DG can be dispatched at the aim of reducing the operating cost. The effect of operation strategy on the cost can be reflected in the objective which contains the cost of network loss, DG curtailment, DG reactive power ancillary service, and power quality compensation. At the same time, the probabilistic constraints can reflect the operation risk degree. Then the optimal dispatch model is simplified as a series of single stage model which can avoid large variable dimension and improve the convergence speed. And the single stage model is solved using a combination of particle swarm optimization (PSO) and point estimate method (PEM). Finally, the proposed optimal dispatch model and method is verified by the IEEE33 test system.

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment

PubMed Central

Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution. PMID:29186166

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.

PubMed

Li, Jianjun; Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution.

A theoretical measure technique for determining 3D symmetric nearly optimal shapes with a given center of mass

NASA Astrophysics Data System (ADS)

Alimorad D., H.; Fakharzadeh J., A.

2017-07-01

In this paper, a new approach is proposed for designing the nearly-optimal three dimensional symmetric shapes with desired physical center of mass. Herein, the main goal is to find such a shape whose image in ( r, θ)-plane is a divided region into a fixed and variable part. The nearly optimal shape is characterized in two stages. Firstly, for each given domain, the nearly optimal surface is determined by changing the problem into a measure-theoretical one, replacing this with an equivalent infinite dimensional linear programming problem and approximating schemes; then, a suitable function that offers the optimal value of the objective function for any admissible given domain is defined. In the second stage, by applying a standard optimization method, the global minimizer surface and its related domain will be obtained whose smoothness is considered by applying outlier detection and smooth fitting methods. Finally, numerical examples are presented and the results are compared to show the advantages of the proposed approach.

Data mining-based coefficient of influence factors optimization of test paper reliability

NASA Astrophysics Data System (ADS)

Xu, Peiyao; Jiang, Huiping; Wei, Jieyao

2018-05-01

Test is a significant part of the teaching process. It demonstrates the final outcome of school teaching through teachers' teaching level and students' scores. The analysis of test paper is a complex operation that has the characteristics of non-linear relation in the length of the paper, time duration and the degree of difficulty. It is therefore difficult to optimize the coefficient of influence factors under different conditions in order to get text papers with clearly higher reliability with general methods [1]. With data mining techniques like Support Vector Regression (SVR) and Genetic Algorithm (GA), we can model the test paper analysis and optimize the coefficient of impact factors for higher reliability. It's easy to find that the combination of SVR and GA can get an effective advance in reliability from the test results. The optimal coefficient of influence factors optimization has a practicability in actual application, and the whole optimizing operation can offer model basis for test paper analysis.

A Decision-making Model for a Two-stage Production-delivery System in SCM Environment

NASA Astrophysics Data System (ADS)

Feng, Ding-Zhong; Yamashiro, Mitsuo

A decision-making model is developed for an optimal production policy in a two-stage production-delivery system that incorporates a fixed quantity supply of finished goods to a buyer at a fixed interval of time. First, a general cost model is formulated considering both supplier (of raw materials) and buyer (of finished products) sides. Then an optimal solution to the problem is derived on basis of the cost model. Using the proposed model and its optimal solution, one can determine optimal production lot size for each stage, optimal number of transportation for semi-finished goods, and optimal quantity of semi-finished goods transported each time to meet the lumpy demand of consumers. Also, we examine the sensitivity of raw materials ordering and production lot size to changes in ordering cost, transportation cost and manufacturing setup cost. A pragmatic computation approach for operational situations is proposed to solve integer approximation solution. Finally, we give some numerical examples.

Optimal Low Energy Earth-Moon Transfers

NASA Technical Reports Server (NTRS)

Griesemer, Paul Ricord; Ocampo, Cesar; Cooley, D. S.

2010-01-01

The optimality of a low-energy Earth-Moon transfer is examined for the first time using primer vector theory. An optimal control problem is formed with the following free variables: the location, time, and magnitude of the transfer insertion burn, and the transfer time. A constraint is placed on the initial state of the spacecraft to bind it to a given initial orbit around a first body, and on the final state of the spacecraft to limit its Keplerian energy with respect to a second body. Optimal transfers in the system are shown to meet certain conditions placed on the primer vector and its time derivative. A two point boundary value problem containing these necessary conditions is created for use in targeting optimal transfers. The two point boundary value problem is then applied to the ballistic lunar capture problem, and an optimal trajectory is shown. Additionally, the ballistic lunar capture trajectory is examined to determine whether one or more additional impulses may improve on the cost of the transfer.

An optimization method for condition based maintenance of aircraft fleet considering prognostics uncertainty.

PubMed

Feng, Qiang; Chen, Yiran; Sun, Bo; Li, Songjie

2014-01-01

An optimization method for condition based maintenance (CBM) of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL) distribution of the key line replaceable Module (LRM) has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success.

H∞ memory feedback control with input limitation minimization for offshore jacket platform stabilization

NASA Astrophysics Data System (ADS)

Yang, Jia Sheng

2018-06-01

In this paper, we investigate a H∞ memory controller with input limitation minimization (HMCIM) for offshore jacket platforms stabilization. The main objective of this study is to reduce the control consumption as well as protect the actuator when satisfying the requirement of the system performance. First, we introduce a dynamic model of offshore platform with low order main modes based on mode reduction method in numerical analysis. Then, based on H∞ control theory and matrix inequality techniques, we develop a novel H∞ memory controller with input limitation. Furthermore, a non-convex optimization model to minimize input energy consumption is proposed. Since it is difficult to solve this non-convex optimization model by optimization algorithm, we use a relaxation method with matrix operations to transform this non-convex optimization model to be a convex optimization model. Thus, it could be solved by a standard convex optimization solver in MATLAB or CPLEX. Finally, several numerical examples are given to validate the proposed models and methods.

Hybrid-optimization strategy for the communication of large-scale Kinetic Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wu, Baodong; Li, Shigang; Zhang, Yunquan; Nie, Ningming

2017-02-01

The parallel Kinetic Monte Carlo (KMC) algorithm based on domain decomposition has been widely used in large-scale physical simulations. However, the communication overhead of the parallel KMC algorithm is critical, and severely degrades the overall performance and scalability. In this paper, we present a hybrid optimization strategy to reduce the communication overhead for the parallel KMC simulations. We first propose a communication aggregation algorithm to reduce the total number of messages and eliminate the communication redundancy. Then, we utilize the shared memory to reduce the memory copy overhead of the intra-node communication. Finally, we optimize the communication scheduling using the neighborhood collective operations. We demonstrate the scalability and high performance of our hybrid optimization strategy by both theoretical and experimental analysis. Results show that the optimized KMC algorithm exhibits better performance and scalability than the well-known open-source library-SPPARKS. On 32-node Xeon E5-2680 cluster (total 640 cores), the optimized algorithm reduces the communication time by 24.8% compared with SPPARKS.

An Optimization Method for Condition Based Maintenance of Aircraft Fleet Considering Prognostics Uncertainty

PubMed Central

Chen, Yiran; Sun, Bo; Li, Songjie

2014-01-01

An optimization method for condition based maintenance (CBM) of aircraft fleet considering prognostics uncertainty is proposed. The CBM and dispatch process of aircraft fleet is analyzed first, and the alternative strategy sets for single aircraft are given. Then, the optimization problem of fleet CBM with lower maintenance cost and dispatch risk is translated to the combinatorial optimization problem of single aircraft strategy. Remain useful life (RUL) distribution of the key line replaceable Module (LRM) has been transformed into the failure probability of the aircraft and the fleet health status matrix is established. And the calculation method of the costs and risks for mission based on health status matrix and maintenance matrix is given. Further, an optimization method for fleet dispatch and CBM under acceptable risk is proposed based on an improved genetic algorithm. Finally, a fleet of 10 aircrafts is studied to verify the proposed method. The results shows that it could realize optimization and control of the aircraft fleet oriented to mission success. PMID:24892046

Cryogenic Tank Structure Sizing With Structural Optimization Method

NASA Technical Reports Server (NTRS)

Wang, J. T.; Johnson, T. F.; Sleight, D. W.; Saether, E.

2001-01-01

Structural optimization methods in MSC /NASTRAN are used to size substructures and to reduce the weight of a composite sandwich cryogenic tank for future launch vehicles. Because the feasible design space of this problem is non-convex, many local minima are found. This non-convex problem is investigated in detail by conducting a series of analyses along a design line connecting two feasible designs. Strain constraint violations occur for some design points along the design line. Since MSC/NASTRAN uses gradient-based optimization procedures. it does not guarantee that the lowest weight design can be found. In this study, a simple procedure is introduced to create a new starting point based on design variable values from previous optimization analyses. Optimization analysis using this new starting point can produce a lower weight design. Detailed inputs for setting up the MSC/NASTRAN optimization analysis and final tank design results are presented in this paper. Approaches for obtaining further weight reductions are also discussed.

Optimization of entanglement witnesses

NASA Astrophysics Data System (ADS)

Lewenstein, M.; Kraus, B.; Cirac, J. I.; Horodecki, P.

2000-11-01

An entanglement witness (EW) is an operator that allows the detection of entangled states. We give necessary and sufficient conditions for such operators to be optimal, i.e., to detect entangled states in an optimal way. We show how to optimize general EW, and then we particularize our results to the nondecomposable ones; the latter are those that can detect positive partial transpose entangled states (PPTES's). We also present a method to systematically construct and optimize this last class of operators based on the existence of ``edge'' PPTES's, i.e., states that violate the range separability criterion [Phys. Lett. A 232, 333 (1997)] in an extreme manner. This method also permits a systematic construction of nondecomposable positive maps (PM's). Our results lead to a sufficient condition for entanglement in terms of nondecomposable EW's and PM's. Finally, we illustrate our results by constructing optimal EW acting on H=C2⊗C4. The corresponding PM's constitute examples of PM's with minimal ``qubit'' domains, or-equivalently-minimal Hermitian conjugate codomains.

A three-term conjugate gradient method under the strong-Wolfe line search

NASA Astrophysics Data System (ADS)

Khadijah, Wan; Rivaie, Mohd; Mamat, Mustafa

2017-08-01

Recently, numerous studies have been concerned in conjugate gradient methods for solving large-scale unconstrained optimization method. In this paper, a three-term conjugate gradient method is proposed for unconstrained optimization which always satisfies sufficient descent direction and namely as Three-Term Rivaie-Mustafa-Ismail-Leong (TTRMIL). Under standard conditions, TTRMIL method is proved to be globally convergent under strong-Wolfe line search. Finally, numerical results are provided for the purpose of comparison.

Approach to optimization of low-power Stirling cryocoolers. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sullivan, D.B.; Radebaugh, R.; Daney, D.E.

1983-01-01

The authors describe a method for optimizing the design (shape of the displacer) of low-power Stirling cryocoolers relative to the power required to operate the systems. A variational calculation which includes static conduction, shuttle, and radiation losses, as well as regenerator inefficiency, has been completed for coolers operating in the 300 K to 10 K range. While the calculations apply to tapered displacer machines, comparison of the results with stepped-displacer cryocoolers indicates reasonable agreement.

Existence and discrete approximation for optimization problems governed by fractional differential equations

NASA Astrophysics Data System (ADS)

Bai, Yunru; Baleanu, Dumitru; Wu, Guo-Cheng

2018-06-01

We investigate a class of generalized differential optimization problems driven by the Caputo derivative. Existence of weak Carathe ´odory solution is proved by using Weierstrass existence theorem, fixed point theorem and Filippov implicit function lemma etc. Then a numerical approximation algorithm is introduced, and a convergence theorem is established. Finally, a nonlinear programming problem constrained by the fractional differential equation is illustrated and the results verify the validity of the algorithm.

Magnetocaloric Materials and the Optimization of Cooling Power Density

NASA Technical Reports Server (NTRS)

Wikus, Patrick; Canavan, Edgar; Heine, Sarah Trowbridge; Matsumoto, Koichi; Numazawa, Takenori

2014-01-01

The magnetocaloric effect is the thermal response of a material to an external magnetic field. This manuscript focuses on the physics and the properties of materials which are commonly used for magnetic refrigeration at cryogenic temperatures. After a brief overview of the magnetocaloric effect and associated thermodynamics, typical requirements on refrigerants are discussed from a standpoint of cooling power density optimization. Finally, a compilation of the most important properties of several common magnetocaloric materials is presented.

Modifications to Improve Data Acquisition and Analysis for Camouflage Design

DTIC Science & Technology

1983-01-01

terrains into facsimiles of the original scenes in 3, 4# or 5 colors in CIELAB notation. Tasks that were addressed included optimization of the...a histogram algorithm (HIST) was used as a first step In the clustering of the CIELAB values of the scene pixels. This algorithm Is highly efficient...however, an optimal process and the CIELAB coordinates of the final color domains can be Influenced by the color coordinate Increments used In the

Taking side effects into account for HIV medication.

PubMed

Costanza, Vicente; Rivadeneira, Pablo S; Biafore, Federico L; D'Attellis, Carlos E

2010-09-01

A control-theoretic approach to the problem of designing "low-side-effects" therapies for HIV patients based on highly active drugs is substantiated here. The evolution of side effects during treatment is modeled by an extra differential equation coupled to the dynamics of virions, healthy T-cells, and infected ones. The new equation reflects the dependence of collateral damages on the amount of each dose administered to the patient and on the evolution of the viral load detected by periodical blood analysis. The cost objective accounts for recommended bounds on healthy cells and virions, and also penalizes the appearance of collateral morbidities caused by the medication. The optimization problem is solved by a hybrid dynamic programming scheme that adhere to discrete-time observation and control actions, but by maintaining the continuous-time setup for predicting states and side effects. The resulting optimal strategies employ less drugs than those prescribed by previous optimization studies, but maintaining high doses at the beginning and the end of each period of six months. If an inverse discount rate is applied to favor early actions, and under a mild penalization of the final viral load, then the optimal doses are found to be high at the beginning and decrease afterward, thus causing an apparent stabilization of the main variables. But in this case, the final viral load turns higher than acceptable.

An n -material thresholding method for improving integerness of solutions in topology optimization

DOE PAGES

Watts, Seth; Tortorelli, Daniel A.

2016-04-10

It is common in solving topology optimization problems to replace an integer-valued characteristic function design field with the material volume fraction field, a real-valued approximation of the design field that permits "fictitious" mixtures of materials during intermediate iterations in the optimization process. This is reasonable so long as one can interpolate properties for such materials and so long as the final design is integer valued. For this purpose, we present a method for smoothly thresholding the volume fractions of an arbitrary number of material phases which specify the design. This method is trivial for two-material design problems, for example, themore » canonical topology design problem of specifying the presence or absence of a single material within a domain, but it becomes more complex when three or more materials are used, as often occurs in material design problems. We take advantage of the similarity in properties between the volume fractions and the barycentric coordinates on a simplex to derive a thresholding, method which is applicable to an arbitrary number of materials. As we show in a sensitivity analysis, this method has smooth derivatives, allowing it to be used in gradient-based optimization algorithms. Finally, we present results, which show synergistic effects when used with Solid Isotropic Material with Penalty and Rational Approximation of Material Properties material interpolation functions, popular methods of ensuring integerness of solutions.« less

Decision Variants for the Automatic Determination of Optimal Feature Subset in RF-RFE.

PubMed

Chen, Qi; Meng, Zhaopeng; Liu, Xinyi; Jin, Qianguo; Su, Ran

2018-06-15

Feature selection, which identifies a set of most informative features from the original feature space, has been widely used to simplify the predictor. Recursive feature elimination (RFE), as one of the most popular feature selection approaches, is effective in data dimension reduction and efficiency increase. A ranking of features, as well as candidate subsets with the corresponding accuracy, is produced through RFE. The subset with highest accuracy (HA) or a preset number of features (PreNum) are often used as the final subset. However, this may lead to a large number of features being selected, or if there is no prior knowledge about this preset number, it is often ambiguous and subjective regarding final subset selection. A proper decision variant is in high demand to automatically determine the optimal subset. In this study, we conduct pioneering work to explore the decision variant after obtaining a list of candidate subsets from RFE. We provide a detailed analysis and comparison of several decision variants to automatically select the optimal feature subset. Random forest (RF)-recursive feature elimination (RF-RFE) algorithm and a voting strategy are introduced. We validated the variants on two totally different molecular biology datasets, one for a toxicogenomic study and the other one for protein sequence analysis. The study provides an automated way to determine the optimal feature subset when using RF-RFE.

A LAGRANGIAN GAUSS-NEWTON-KRYLOV SOLVER FOR MASS- AND INTENSITY-PRESERVING DIFFEOMORPHIC IMAGE REGISTRATION.

PubMed

Mang, Andreas; Ruthotto, Lars

2017-01-01

We present an efficient solver for diffeomorphic image registration problems in the framework of Large Deformations Diffeomorphic Metric Mappings (LDDMM). We use an optimal control formulation, in which the velocity field of a hyperbolic PDE needs to be found such that the distance between the final state of the system (the transformed/transported template image) and the observation (the reference image) is minimized. Our solver supports both stationary and non-stationary (i.e., transient or time-dependent) velocity fields. As transformation models, we consider both the transport equation (assuming intensities are preserved during the deformation) and the continuity equation (assuming mass-preservation). We consider the reduced form of the optimal control problem and solve the resulting unconstrained optimization problem using a discretize-then-optimize approach. A key contribution is the elimination of the PDE constraint using a Lagrangian hyperbolic PDE solver. Lagrangian methods rely on the concept of characteristic curves. We approximate these curves using a fourth-order Runge-Kutta method. We also present an efficient algorithm for computing the derivatives of the final state of the system with respect to the velocity field. This allows us to use fast Gauss-Newton based methods. We present quickly converging iterative linear solvers using spectral preconditioners that render the overall optimization efficient and scalable. Our method is embedded into the image registration framework FAIR and, thus, supports the most commonly used similarity measures and regularization functionals. We demonstrate the potential of our new approach using several synthetic and real world test problems with up to 14.7 million degrees of freedom.

Economic analysis of secondary and enhanced oil recovery techniques in Wyoming

NASA Astrophysics Data System (ADS)

Kara, Erdal

This dissertation primarily aims to theoretically analyze a firm's optimization of enhanced oil recovery (EOR) and carbon dioxide sequestration under different social policies and empirically analyze the firm's optimization of enhanced oil recovery. The final part of the dissertation empirically analyzes how geological factors and water injection management influence oil recovery. The first chapter builds a theoretical model to analyze economic optimization of EOR and geological carbon sequestration under different social policies. Specifically, it analyzes how social policies on sequestration influence the extent of oil operations, optimal oil production and CO2 sequestration. The theoretical results show that the socially optimal policy is a subsidy on the net CO2 sequestration, assuming negative net emissions from EOR. Such a policy is expected to increase a firm's total carbon dioxide sequestration. The second chapter statistically estimates the theoretical oil production model and its different versions. Empirical results are not robust over different estimation techniques and not in line with the theoretical production model. The last part of the second chapter utilizes a simplified version of theoretical model and concludes that EOR via CO2 injection improves oil recovery. The final chapter analyzes how a contemporary oil recovery technology (water flooding of oil reservoirs) and various reservoir-specific geological factors influence oil recovery in Wyoming. The results show that there is a positive concave relationship between cumulative water injection and cumulative oil recovery and also show that certain geological factors affect the oil recovery. Moreover, the curvature of the concave functional relationship between cumulative water injection and oil recovery is reservoir-specific due to heterogeneities among different reservoirs.

Comparison of multiobjective evolutionary algorithms: empirical results.

PubMed

Zitzler, E; Deb, K; Thiele, L

2000-01-01

In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in converging to the Pareto-optimal front (e.g., multimodality and deception). By investigating these different problem features separately, it is possible to predict the kind of problems to which a certain technique is or is not well suited. However, in contrast to what was suspected beforehand, the experimental results indicate a hierarchy of the algorithms under consideration. Furthermore, the emerging effects are evidence that the suggested test functions provide sufficient complexity to compare multiobjective optimizers. Finally, elitism is shown to be an important factor for improving evolutionary multiobjective search.

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

NASA Astrophysics Data System (ADS)

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.

Research on Collection System Optimal Design of Wind Farm with Obstacles

NASA Astrophysics Data System (ADS)

Huang, W.; Yan, B. Y.; Tan, R. S.; Liu, L. F.

2017-05-01

To the collection system optimal design of offshore wind farm, the factors considered are not only the reasonable configuration of the cable and switch, but also the influence of the obstacles on the topology design of the offshore wind farm. This paper presents a concrete topology optimization algorithm with obstacles. The minimal area rectangle encasing box of the obstacle is obtained by using the method of minimal area encasing box. Then the optimization algorithm combining the advantages of Dijkstra algorithm and Prim algorithm is used to gain the scheme of avoidance obstacle path planning. Finally a fuzzy comprehensive evaluation model based on the analytic hierarchy process is constructed to compare the performance of the different topologies. Case studies demonstrate the feasibility of the proposed algorithm and model.

The Study on the Optimization of Container Multimodal Transport Business Process in Shandong

NASA Astrophysics Data System (ADS)

Wang, Fengmei; Gong, Xiaoyi; Ni, Yingying; Zhan, Jun; Che, Huiping

2018-06-01

Shandong is a coastal city with good location advantages. As a hub port for international trade goods and a port of transhipment, shandong's demand for multimodal transport is more urgent. By selecting the suitable non-water port and the multimodal transport carrier to improve the efficiency of multimodal transport, the purpose of saving the time of logistics is achieved, thus reducing the logistics cost.It branch out through Shandongt, and it can reach the central region of China, can reach the Western remote area ,too. This paper puts forward the optimization scheme of the business process of container multimodal transport. The optimization of freight forwarding business process is analyzed. The multimodal transport model in Shandong was designed. Finally, the optimal approach of multimodal transport in Shandong is put forward.

[Optimal solution and analysis of muscular force during standing balance].

PubMed

Wang, Hongrui; Zheng, Hui; Liu, Kun

2015-02-01

The present study was aimed at the optimal solution of the main muscular force distribution in the lower extremity during standing balance of human. The movement musculoskeletal system of lower extremity was simplified to a physical model with 3 joints and 9 muscles. Then on the basis of this model, an optimum mathematical model was built up to solve the problem of redundant muscle forces. Particle swarm optimization (PSO) algorithm is used to calculate the single objective and multi-objective problem respectively. The numerical results indicated that the multi-objective optimization could be more reasonable to obtain the distribution and variation of the 9 muscular forces. Finally, the coordination of each muscle group during maintaining standing balance under the passive movement was qualitatively analyzed using the simulation results obtained.

Bilayer tablets of Paliperidone for Extended release osmotic drug delivery

NASA Astrophysics Data System (ADS)

Chowdary, K. Sunil; Napoleon, A. A.

2017-11-01

The purpose of this study is to develop and optimize the formulation of paliperidone bilayer tablet core and coating which should meet in vitro performance of trilayered Innovator sample Invega. Optimization of core formulations prepared by different ratio of polyox grades and optimization of coating of (i) sub-coating build-up with hydroxy ethyl cellulose (HEC) and (ii).enteric coating build-up with cellulose acetate (CA). Some important influence factors such as different core tablet compositions and different coating solution ingredients involved in the formulation procedure were investigated. The optimization of formulation and process was conducted by comparing different in vitro release behaviours of Paliperidone. In vitro dissolution studies of Innovator sample (Invega) with formulations of different release rate which ever close release pattern during the whole 24 h test is finalized.

An improved hierarchical A * algorithm in the optimization of parking lots

NASA Astrophysics Data System (ADS)

Wang, Yong; Wu, Junjuan; Wang, Ying

2017-08-01

In the parking lot parking path optimization, the traditional evaluation index is the shortest distance as the best index and it does not consider the actual road conditions. Now, the introduction of a more practical evaluation index can not only simplify the hardware design of the boot system but also save the software overhead. Firstly, we establish the parking lot network graph RPCDV mathematical model and all nodes in the network is divided into two layers which were constructed using different evaluation function base on the improved hierarchical A * algorithm which improves the time optimal path search efficiency and search precision of the evaluation index. The final results show that for different sections of the program attribute parameter algorithm always faster the time to find the optimal path.

Optimization of the interplanetary trajectories of spacecraft with a solar electric propulsion power plant of minimal power

NASA Astrophysics Data System (ADS)

Ivanyukhin, A. V.; Petukhov, V. G.

2016-12-01

The problem of optimizing the interplanetary trajectories of a spacecraft (SC) with a solar electric propulsion system (SEPS) is examined. The problem of investigating the permissible power minimum of the solar electric propulsion power plant required for a successful flight is studied. Permissible ranges of thrust and exhaust velocity are analyzed for the given range of flight time and final mass of the spacecraft. The optimization is performed according to Portnyagin's maximum principle, and the continuation method is used for reducing the boundary problem of maximal principle to the Cauchy problem and to study the solution/ parameters dependence. Such a combination results in the robust algorithm that reduces the problem of trajectory optimization to the numerical integration of differential equations by the continuation method.

Voronoi Diagram Based Optimization of Dynamic Reactive Power Sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Weihong; Sun, Kai; Qi, Junjian

2015-01-01

Dynamic var sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues or even voltage collapse. This paper proposes a new approach to optimization of the sizes of dynamic var sources at candidate locations by a Voronoi diagram based algorithm. It first disperses sample points of potential solutions in a searching space, evaluates a cost function at each point by barycentric interpolation for the subspaces around the point, and then constructs a Voronoi diagram about cost function values over the entire space. Accordingly, the final optimal solution can be obtained. Case studies on the WSCC 9-bus system and NPCC 140-busmore » system have validated that the new approach can quickly identify the boundary of feasible solutions in searching space and converge to the global optimal solution.« less

Optimal symmetric flight studies

NASA Technical Reports Server (NTRS)

Weston, A. R.; Menon, P. K. A.; Bilimoria, K. D.; Cliff, E. M.; Kelley, H. J.

1985-01-01

Several topics in optimal symmetric flight of airbreathing vehicles are examined. In one study, an approximation scheme designed for onboard real-time energy management of climb-dash is developed and calculations for a high-performance aircraft presented. In another, a vehicle model intermediate in complexity between energy and point-mass models is explored and some quirks in optimal flight characteristics peculiar to the model uncovered. In yet another study, energy-modelling procedures are re-examined with a view to stretching the range of validity of zeroth-order approximation by special choice of state variables. In a final study, time-fuel tradeoffs in cruise-dash are examined for the consequences of nonconvexities appearing in the classical steady cruise-dash model. Two appendices provide retrospective looks at two early publications on energy modelling and related optimal control theory.

Optimal thrust level for orbit insertion

NASA Astrophysics Data System (ADS)

Cerf, Max

2017-07-01

The minimum-fuel orbital transfer is analyzed in the case of a launcher upper stage using a constantly thrusting engine. The thrust level is assumed to be constant and its value is optimized together with the thrust direction. A closed-loop solution for the thrust direction is derived from the extremal analysis for a planar orbital transfer. The optimal control problem reduces to two unknowns, namely the thrust level and the final time. Guessing and propagating the costates is no longer necessary and the optimal trajectory is easily found from a rough initialization. On the other hand the initial costates are assessed analytically from the initial conditions and they can be used as initial guess for transfers at different thrust levels. The method is exemplified on a launcher upper stage targeting a geostationary transfer orbit.

Optimizing the Compressive Strength of Strain-Hardenable Stretch-Formed Microtruss Architectures

NASA Astrophysics Data System (ADS)

Yu, Bosco; Abu Samk, Khaled; Hibbard, Glenn D.

2015-05-01

The mechanical performance of stretch-formed microtrusses is determined by both the internal strut architecture and the accumulated plastic strain during fabrication. The current study addresses the question of optimization, by taking into consideration the interdependency between fabrication path, material properties and architecture. Low carbon steel (AISI1006) and aluminum (AA3003) material systems were investigated experimentally, with good agreement between measured values and the analytical model. The compressive performance of the microtrusses was then optimized on a minimum weight basis under design constraints such as fixed starting sheet thickness and final microtruss height by satisfying the Karush-Kuhn-Tucker condition. The optimization results were summarized as carpet plots in order to meaningfully visualize the interdependency between architecture, microstructural state, and mechanical performance, enabling material and processing path selection.

Optimal design of an electro-hydraulic valve for heavy-duty vehicle clutch actuator with certain constraints

NASA Astrophysics Data System (ADS)

Meng, Fei; Shi, Peng; Karimi, Hamid Reza; Zhang, Hui

2016-02-01

The main objective of this paper is to investigate the sensitivity analysis and optimal design of a proportional solenoid valve (PSV) operated pressure reducing valve (PRV) for heavy-duty automatic transmission clutch actuators. The nonlinear electro-hydraulic valve model is developed based on fluid dynamics. In order to implement the sensitivity analysis and optimization for the PRV, the PSV model is validated by comparing the results with data obtained from a real test-bench. The sensitivity of the PSV pressure response with regard to the structural parameters is investigated by using Sobol's method. Finally, simulations and experimental investigations are performed on the optimized prototype and the results reveal that the dynamical characteristics of the valve have been improved in comparison with the original valve.

Concurrent Monte Carlo transport and fluence optimization with fluence adjusting scalable transport Monte Carlo

PubMed Central

Svatos, M.; Zankowski, C.; Bednarz, B.

2016-01-01

Purpose: The future of radiation therapy will require advanced inverse planning solutions to support single-arc, multiple-arc, and “4π” delivery modes, which present unique challenges in finding an optimal treatment plan over a vast search space, while still preserving dosimetric accuracy. The successful clinical implementation of such methods would benefit from Monte Carlo (MC) based dose calculation methods, which can offer improvements in dosimetric accuracy when compared to deterministic methods. The standard method for MC based treatment planning optimization leverages the accuracy of the MC dose calculation and efficiency of well-developed optimization methods, by precalculating the fluence to dose relationship within a patient with MC methods and subsequently optimizing the fluence weights. However, the sequential nature of this implementation is computationally time consuming and memory intensive. Methods to reduce the overhead of the MC precalculation have been explored in the past, demonstrating promising reductions of computational time overhead, but with limited impact on the memory overhead due to the sequential nature of the dose calculation and fluence optimization. The authors propose an entirely new form of “concurrent” Monte Carlo treat plan optimization: a platform which optimizes the fluence during the dose calculation, reduces wasted computation time being spent on beamlets that weakly contribute to the final dose distribution, and requires only a low memory footprint to function. In this initial investigation, the authors explore the key theoretical and practical considerations of optimizing fluence in such a manner. Methods: The authors present a novel derivation and implementation of a gradient descent algorithm that allows for optimization during MC particle transport, based on highly stochastic information generated through particle transport of very few histories. A gradient rescaling and renormalization algorithm, and the concept of momentum from stochastic gradient descent were used to address obstacles unique to performing gradient descent fluence optimization during MC particle transport. The authors have applied their method to two simple geometrical phantoms, and one clinical patient geometry to examine the capability of this platform to generate conformal plans as well as assess its computational scaling and efficiency, respectively. Results: The authors obtain a reduction of at least 50% in total histories transported in their investigation compared to a theoretical unweighted beamlet calculation and subsequent fluence optimization method, and observe a roughly fixed optimization time overhead consisting of ∼10% of the total computation time in all cases. Finally, the authors demonstrate a negligible increase in memory overhead of ∼7–8 MB to allow for optimization of a clinical patient geometry surrounded by 36 beams using their platform. Conclusions: This study demonstrates a fluence optimization approach, which could significantly improve the development of next generation radiation therapy solutions while incurring minimal additional computational overhead. PMID:27277051

Development of transportation asset management decision support tools : final report.

DOT National Transportation Integrated Search

2017-08-09

This study developed a web-based prototype decision support platform to demonstrate the benefits of transportation asset management in monitoring asset performance, supporting asset funding decisions, planning budget tradeoffs, and optimizing resourc...

Development of Charge Drain Coatings: Final CRADA Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elam, Jeffrey W.

2017-01-17

The primary goal of this CRADA project was to develop and optimize tunable resistive coatings prepared by atomic layer deposition (ALD) for use as charge-drain coatings on the KLA-Tencor digital pattern generators (DPGs).

Optimal ballistically captured Earth-Moon transfers

NASA Astrophysics Data System (ADS)

Ricord Griesemer, Paul; Ocampo, Cesar; Cooley, D. S.

2012-07-01

The optimality of a low-energy Earth-Moon transfer terminating in ballistic capture is examined for the first time using primer vector theory. An optimal control problem is formed with the following free variables: the location, time, and magnitude of the transfer insertion burn, and the transfer time. A constraint is placed on the initial state of the spacecraft to bind it to a given initial orbit around a first body, and on the final state of the spacecraft to limit its Keplerian energy with respect to a second body. Optimal transfers in the system are shown to meet certain conditions placed on the primer vector and its time derivative. A two point boundary value problem containing these necessary conditions is created for use in targeting optimal transfers. The two point boundary value problem is then applied to the ballistic lunar capture problem, and an optimal trajectory is shown. Additionally, the problem is then modified to fix the time of transfer, allowing for optimal multi-impulse transfers. The tradeoff between transfer time and fuel cost is shown for Earth-Moon ballistic lunar capture transfers.

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA Technical Reports Server (NTRS)

Rash, James L.

2010-01-01

NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.

Optimization and scale up of microfluidic nanolipomer production method for preclinical and potential clinical trials.

PubMed

Gdowski, Andrew; Johnson, Kaitlyn; Shah, Sunil; Gryczynski, Ignacy; Vishwanatha, Jamboor; Ranjan, Amalendu

2018-02-12

The process of optimization and fabrication of nanoparticle synthesis for preclinical studies can be challenging and time consuming. Traditional small scale laboratory synthesis techniques suffer from batch to batch variability. Additionally, the parameters used in the original formulation must be re-optimized due to differences in fabrication techniques for clinical production. Several low flow microfluidic synthesis processes have been reported in recent years for developing nanoparticles that are a hybrid between polymeric nanoparticles and liposomes. However, use of high flow microfluidic synthetic techniques has not been described for this type of nanoparticle system, which we will term as nanolipomer. In this manuscript, we describe the successful optimization and functional assessment of nanolipomers fabricated using a microfluidic synthesis method under high flow parameters. The optimal total flow rate for synthesis of these nanolipomers was found to be 12 ml/min and flow rate ratio 1:1 (organic phase: aqueous phase). The PLGA polymer concentration of 10 mg/ml and a DSPE-PEG lipid concentration of 10% w/v provided optimal size, PDI and stability. Drug loading and encapsulation of a representative hydrophobic small molecule drug, curcumin, was optimized and found that high encapsulation efficiency of 58.8% and drug loading of 4.4% was achieved at 7.5% w/w initial concentration of curcumin/PLGA polymer. The final size and polydispersity index of the optimized nanolipomer was 102.11 nm and 0.126, respectively. Functional assessment of uptake of the nanolipomers in C4-2B prostate cancer cells showed uptake at 1 h and increased uptake at 24 h. The nanolipomer was more effective in the cell viability assay compared to free drug. Finally, assessment of in vivo retention in mice of these nanolipomers revealed retention for up to 2 h and were completely cleared at 24 h. In this study, we have demonstrated that a nanolipomer formulation can be successfully synthesized and easily scaled up through a high flow microfluidic system with optimal characteristics. The process of developing nanolipomers using this methodology is significant as the same optimized parameters used for small batches could be translated into manufacturing large scale batches for clinical trials through parallel flow systems.

A consistent methodology for optimal shape design of graphene sheets to maximize their fundamental frequencies considering topological defects

NASA Astrophysics Data System (ADS)

Shi, Jin-Xing; Ohmura, Keiichiro; Shimoda, Masatoshi; Lei, Xiao-Wen

2018-07-01

In recent years, shape design of graphene sheets (GSs) by introducing topological defects for enhancing their mechanical behaviors has attracted the attention of scholars. In the present work, we propose a consistent methodology for optimal shape design of GSs using a combination of the molecular mechanics (MM) method, the non-parametric shape optimization method, the phase field crystal (PFC) method, Voronoi tessellation, and molecular dynamics (MD) simulation to maximize their fundamental frequencies. At first, we model GSs as continuum frame models using a link between the MM method and continuum mechanics. Then, we carry out optimal shape design of GSs in fundamental frequency maximization problem based on a developed shape optimization method for frames. However, the obtained optimal shapes of GSs only consisting of hexagonal carbon rings are unstable that do not satisfy the principle of least action, so we relocate carbon atoms on the optimal shapes by introducing topological defects using the PFC method and Voronoi tessellation. At last, we perform the structural relaxation through MD simulation to determine the final optimal shapes of GSs. We design two examples of GSs and the optimal results show that the fundamental frequencies of GSs can be significantly enhanced according to the optimal shape design methodology.

The Sizing and Optimization Language (SOL): A computer language to improve the user/optimizer interface

NASA Technical Reports Server (NTRS)

Lucas, S. H.; Scotti, S. J.

1989-01-01

The nonlinear mathematical programming method (formal optimization) has had many applications in engineering design. A figure illustrates the use of optimization techniques in the design process. The design process begins with the design problem, such as the classic example of the two-bar truss designed for minimum weight as seen in the leftmost part of the figure. If formal optimization is to be applied, the design problem must be recast in the form of an optimization problem consisting of an objective function, design variables, and constraint function relations. The middle part of the figure shows the two-bar truss design posed as an optimization problem. The total truss weight is the objective function, the tube diameter and truss height are design variables, with stress and Euler buckling considered as constraint function relations. Lastly, the designer develops or obtains analysis software containing a mathematical model of the object being optimized, and then interfaces the analysis routine with existing optimization software such as CONMIN, ADS, or NPSOL. This final state of software development can be both tedious and error-prone. The Sizing and Optimization Language (SOL), a special-purpose computer language whose goal is to make the software implementation phase of optimum design easier and less error-prone, is presented.

Energy-optimal path planning by stochastic dynamically orthogonal level-set optimization

NASA Astrophysics Data System (ADS)

Subramani, Deepak N.; Lermusiaux, Pierre F. J.

2016-04-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. Based on partial differential equations, the methodology rigorously leverages the level-set equation that governs time-optimal reachability fronts for a given relative vehicle-speed function. To set up the energy optimization, the relative vehicle-speed and headings are considered to be stochastic and new stochastic Dynamically Orthogonal (DO) level-set equations are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. Numerical schemes to solve the reduced stochastic DO level-set equations are obtained, and accuracy and efficiency considerations are discussed. These reduced equations are first shown to be efficient at solving the governing stochastic level-sets, in part by comparisons with direct Monte Carlo simulations. To validate the methodology and illustrate its accuracy, comparisons with semi-analytical energy-optimal path solutions are then completed. In particular, we consider the energy-optimal crossing of a canonical steady front and set up its semi-analytical solution using a energy-time nested nonlinear double-optimization scheme. We then showcase the inner workings and nuances of the energy-optimal path planning, considering different mission scenarios. Finally, we study and discuss results of energy-optimal missions in a wind-driven barotropic quasi-geostrophic double-gyre ocean circulation.

Designing a multistage supply chain in cross-stage reverse logistics environments: application of particle swarm optimization algorithms.

PubMed

Chiang, Tzu-An; Che, Z H; Cui, Zhihua

2014-01-01

This study designed a cross-stage reverse logistics course for defective products so that damaged products generated in downstream partners can be directly returned to upstream partners throughout the stages of a supply chain for rework and maintenance. To solve this reverse supply chain design problem, an optimal cross-stage reverse logistics mathematical model was developed. In addition, we developed a genetic algorithm (GA) and three particle swarm optimization (PSO) algorithms: the inertia weight method (PSOA_IWM), V(Max) method (PSOA_VMM), and constriction factor method (PSOA_CFM), which we employed to find solutions to support this mathematical model. Finally, a real case and five simulative cases with different scopes were used to compare the execution times, convergence times, and objective function values of the four algorithms used to validate the model proposed in this study. Regarding system execution time, the GA consumed more time than the other three PSOs did. Regarding objective function value, the GA, PSOA_IWM, and PSOA_CFM could obtain a lower convergence value than PSOA_VMM could. Finally, PSOA_IWM demonstrated a faster convergence speed than PSOA_VMM, PSOA_CFM, and the GA did.

Designing a Multistage Supply Chain in Cross-Stage Reverse Logistics Environments: Application of Particle Swarm Optimization Algorithms

PubMed Central

Chiang, Tzu-An; Che, Z. H.

2014-01-01

This study designed a cross-stage reverse logistics course for defective products so that damaged products generated in downstream partners can be directly returned to upstream partners throughout the stages of a supply chain for rework and maintenance. To solve this reverse supply chain design problem, an optimal cross-stage reverse logistics mathematical model was developed. In addition, we developed a genetic algorithm (GA) and three particle swarm optimization (PSO) algorithms: the inertia weight method (PSOA_IWM), V Max method (PSOA_VMM), and constriction factor method (PSOA_CFM), which we employed to find solutions to support this mathematical model. Finally, a real case and five simulative cases with different scopes were used to compare the execution times, convergence times, and objective function values of the four algorithms used to validate the model proposed in this study. Regarding system execution time, the GA consumed more time than the other three PSOs did. Regarding objective function value, the GA, PSOA_IWM, and PSOA_CFM could obtain a lower convergence value than PSOA_VMM could. Finally, PSOA_IWM demonstrated a faster convergence speed than PSOA_VMM, PSOA_CFM, and the GA did. PMID:24772026

Computation of the target state and feedback controls for time optimal consensus in multi-agent systems

NASA Astrophysics Data System (ADS)

Mulla, Ameer K.; Patil, Deepak U.; Chakraborty, Debraj

2018-02-01

N identical agents with bounded inputs aim to reach a common target state (consensus) in the minimum possible time. Algorithms for computing this time-optimal consensus point, the control law to be used by each agent and the time taken for the consensus to occur, are proposed. Two types of multi-agent systems are considered, namely (1) coupled single-integrator agents on a plane and, (2) double-integrator agents on a line. At the initial time instant, each agent is assumed to have access to the state information of all the other agents. An algorithm, using convexity of attainable sets and Helly's theorem, is proposed, to compute the final consensus target state and the minimum time to achieve this consensus. Further, parts of the computation are parallelised amongst the agents such that each agent has to perform computations of O(N2) run time complexity. Finally, local feedback time-optimal control laws are synthesised to drive each agent to the target point in minimum time. During this part of the operation, the controller for each agent uses measurements of only its own states and does not need to communicate with any neighbouring agents.

Performance assessment and optimization of an irreversible nano-scale Stirling engine cycle operating with Maxwell-Boltzmann gas

NASA Astrophysics Data System (ADS)

Ahmadi, Mohammad H.; Ahmadi, Mohammad-Ali; Pourfayaz, Fathollah

2015-09-01

Developing new technologies like nano-technology improves the performance of the energy industries. Consequently, emerging new groups of thermal cycles in nano-scale can revolutionize the energy systems' future. This paper presents a thermo-dynamical study of a nano-scale irreversible Stirling engine cycle with the aim of optimizing the performance of the Stirling engine cycle. In the Stirling engine cycle the working fluid is an Ideal Maxwell-Boltzmann gas. Moreover, two different strategies are proposed for a multi-objective optimization issue, and the outcomes of each strategy are evaluated separately. The first strategy is proposed to maximize the ecological coefficient of performance (ECOP), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F . Furthermore, the second strategy is suggested to maximize the thermal efficiency ( η), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function ( F). All the strategies in the present work are executed via a multi-objective evolutionary algorithms based on NSGA∥ method. Finally, to achieve the final answer in each strategy, three well-known decision makers are executed. Lastly, deviations of the outcomes gained in each strategy and each decision maker are evaluated separately.

Cure Cycle Optimization of Rapidly Cured Out-Of-Autoclave Composites.

PubMed

Dong, Anqi; Zhao, Yan; Zhao, Xinqing; Yu, Qiyong

2018-03-13

Out-of-autoclave prepreg typically needs a long cure cycle to guarantee good properties as the result of low processing pressure applied. It is essential to reduce the manufacturing time, achieve real cost reduction, and take full advantage of out-of-autoclave process. The focus of this paper is to reduce the cure cycle time and production cost while maintaining high laminate quality. A rapidly cured out-of-autoclave resin and relative prepreg were independently developed. To determine a suitable rapid cure procedure for the developed prepreg, the effect of heating rate, initial cure temperature, dwelling time, and post-cure time on the final laminate quality were evaluated and the factors were then optimized. As a result, a rapid cure procedure was determined. The results showed that the resin infiltration could be completed at the end of the initial cure stage and no obvious void could be seen in the laminate at this time. The laminate could achieve good internal quality using the optimized cure procedure. The mechanical test results showed that the laminates had a fiber volume fraction of 59-60% with a final glass transition temperature of 205 °C and excellent mechanical strength especially the flexural properties.

Cure Cycle Optimization of Rapidly Cured Out-Of-Autoclave Composites

PubMed Central

Dong, Anqi; Zhao, Yan; Zhao, Xinqing; Yu, Qiyong

2018-01-01

Out-of-autoclave prepreg typically needs a long cure cycle to guarantee good properties as the result of low processing pressure applied. It is essential to reduce the manufacturing time, achieve real cost reduction, and take full advantage of out-of-autoclave process. The focus of this paper is to reduce the cure cycle time and production cost while maintaining high laminate quality. A rapidly cured out-of-autoclave resin and relative prepreg were independently developed. To determine a suitable rapid cure procedure for the developed prepreg, the effect of heating rate, initial cure temperature, dwelling time, and post-cure time on the final laminate quality were evaluated and the factors were then optimized. As a result, a rapid cure procedure was determined. The results showed that the resin infiltration could be completed at the end of the initial cure stage and no obvious void could be seen in the laminate at this time. The laminate could achieve good internal quality using the optimized cure procedure. The mechanical test results showed that the laminates had a fiber volume fraction of 59–60% with a final glass transition temperature of 205 °C and excellent mechanical strength especially the flexural properties. PMID:29534048

Photo-Electrochemical Treatment of Reactive Dyes in Wastewater and Reuse of the Effluent: Method Optimization

PubMed Central

Sala, Mireia; López-Grimau, Víctor; Gutiérrez-Bouzán, Carmen

2014-01-01

In this work, the efficiency of a photo-electrochemical method to remove color in textile dyeing effluents is discussed. The decolorization of a synthetic effluent containing a bi-functional reactive dye was carried out by applying an electrochemical treatment at different intensities (2 A, 5 A and 10 A), followed by ultraviolet irradiation. The combination of both treatments was optimized. The final percentage of effluent decolorization, the reduction of halogenated organic volatile compound and the total organic carbon removal were the determinant factors in the selection of the best treatment conditions. The optimized method was applied to the treatment of nine simulated dyeing effluents prepared with different reactive dyes in order to compare the behavior of mono, bi, and tri-reactive dyes. Finally, the nine treated effluents were reused in new dyeing processes and the color differences (DECMC (2:1)) with respect to a reference were evaluated. The influence of the effluent organic matter removal on the color differences was also studied. The reuse of the treated effluents provides satisfactory dyeing results, and an important reduction in water consumption and salt discharge is achieved. PMID:28788251

Optimal transfers between libration-point orbits in the elliptic restricted three-body problem

NASA Astrophysics Data System (ADS)

Hiday, Lisa Ann

1992-09-01

A strategy is formulated to design optimal impulsive transfers between three-dimensional libration-point orbits in the vicinity of the interior L(1) libration point of the Sun-Earth/Moon barycenter system. Two methods of constructing nominal transfers, for which the fuel cost is to be minimized, are developed; both inferior and superior transfers between two halo orbits are considered. The necessary conditions for an optimal transfer trajectory are stated in terms of the primer vector. The adjoint equation relating reference and perturbed trajectories in this formulation of the elliptic restricted three-body problem is shown to be distinctly different from that obtained in the analysis of trajectories in the two-body problem. Criteria are established whereby the cost on a nominal transfer can be improved by the addition of an interior impulse or by the implementation of coastal arcs in the initial and final orbits. The necessary conditions for the local optimality of a time-fixed transfer trajectory possessing additional impulses are satisfied by requiring continuity of the Hamiltonian and the derivative of the primer vector at all interior impulses. The optimality of a time-free transfer containing coastal arcs is surmised by examination of the slopes at the endpoints of a plot of the magnitude of the primer vector over the duration of the transfer path. If the initial and final slopes of the primer magnitude are zero, the transfer trajectory is optimal; otherwise, the execution of coasts is warranted. The position and timing of each interior impulse applied to a time-fixed transfer as well as the direction and length of coastal periods implemented on a time-free transfer are specified by the unconstrained minimization of the appropriate variation in cost utilizing a multivariable search technique. Although optimal solutions in some instances are elusive, the time-fixed and time-free optimization algorithms prove to be very successful in diminishing costs on nominal transfer trajectories. The inclusion of coastal arcs on time-free superior and inferior transfers results in significant modification of the transfer time of flight caused by shifts in departure and arrival locations on the halo orbits.

Four-state virtual research peer exchange 2015 : final report.

DOT National Transportation Integrated Search

2016-01-01

The transportation research programs in Idaho, Nevada, South Dakota, and Wyoming each hosted a multi-state : online webinar-based peer exchange consisting of a series of four webinars addressing four topics: : - Research Quality: optimizing the value...

Implementation of transportation asset management in Grandview, Missouri : final report.

DOT National Transportation Integrated Search

2017-02-01

The successful implementation of transportation asset management (TAM) by local governments facilitates the optimization of limited resources. The use of a data-driven TAM program helps to identify and prioritize needs, identify and dedicate resource...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Y. M., E-mail: ymingy@gmail.com; Bednarz, B.; Svatos, M.

Purpose: The future of radiation therapy will require advanced inverse planning solutions to support single-arc, multiple-arc, and “4π” delivery modes, which present unique challenges in finding an optimal treatment plan over a vast search space, while still preserving dosimetric accuracy. The successful clinical implementation of such methods would benefit from Monte Carlo (MC) based dose calculation methods, which can offer improvements in dosimetric accuracy when compared to deterministic methods. The standard method for MC based treatment planning optimization leverages the accuracy of the MC dose calculation and efficiency of well-developed optimization methods, by precalculating the fluence to dose relationship withinmore » a patient with MC methods and subsequently optimizing the fluence weights. However, the sequential nature of this implementation is computationally time consuming and memory intensive. Methods to reduce the overhead of the MC precalculation have been explored in the past, demonstrating promising reductions of computational time overhead, but with limited impact on the memory overhead due to the sequential nature of the dose calculation and fluence optimization. The authors propose an entirely new form of “concurrent” Monte Carlo treat plan optimization: a platform which optimizes the fluence during the dose calculation, reduces wasted computation time being spent on beamlets that weakly contribute to the final dose distribution, and requires only a low memory footprint to function. In this initial investigation, the authors explore the key theoretical and practical considerations of optimizing fluence in such a manner. Methods: The authors present a novel derivation and implementation of a gradient descent algorithm that allows for optimization during MC particle transport, based on highly stochastic information generated through particle transport of very few histories. A gradient rescaling and renormalization algorithm, and the concept of momentum from stochastic gradient descent were used to address obstacles unique to performing gradient descent fluence optimization during MC particle transport. The authors have applied their method to two simple geometrical phantoms, and one clinical patient geometry to examine the capability of this platform to generate conformal plans as well as assess its computational scaling and efficiency, respectively. Results: The authors obtain a reduction of at least 50% in total histories transported in their investigation compared to a theoretical unweighted beamlet calculation and subsequent fluence optimization method, and observe a roughly fixed optimization time overhead consisting of ∼10% of the total computation time in all cases. Finally, the authors demonstrate a negligible increase in memory overhead of ∼7–8 MB to allow for optimization of a clinical patient geometry surrounded by 36 beams using their platform. Conclusions: This study demonstrates a fluence optimization approach, which could significantly improve the development of next generation radiation therapy solutions while incurring minimal additional computational overhead.« less

An Optimal Order Nonnested Mixed Multigrid Method for Generalized Stokes Problems

NASA Technical Reports Server (NTRS)

Deng, Qingping

1996-01-01

A multigrid algorithm is developed and analyzed for generalized Stokes problems discretized by various nonnested mixed finite elements within a unified framework. It is abstractly proved by an element-independent analysis that the multigrid algorithm converges with an optimal order if there exists a 'good' prolongation operator. A technique to construct a 'good' prolongation operator for nonnested multilevel finite element spaces is proposed. Its basic idea is to introduce a sequence of auxiliary nested multilevel finite element spaces and define a prolongation operator as a composite operator of two single grid level operators. This makes not only the construction of a prolongation operator much easier (the final explicit forms of such prolongation operators are fairly simple), but the verification of the approximate properties for prolongation operators is also simplified. Finally, as an application, the framework and technique is applied to seven typical nonnested mixed finite elements.

Incorporating Linear Synchronous Transit Interpolation into the Growing String Method: Algorithm and Applications.

PubMed

Behn, Andrew; Zimmerman, Paul M; Bell, Alexis T; Head-Gordon, Martin

2011-12-13

The growing string method is a powerful tool in the systematic study of chemical reactions with theoretical methods which allows for the rapid identification of transition states connecting known reactant and product structures. However, the efficiency of this method is heavily influenced by the choice of interpolation scheme when adding new nodes to the string during optimization. In particular, the use of Cartesian coordinates with cubic spline interpolation often produces guess structures which are far from the final reaction path and require many optimization steps (and thus many energy and gradient calculations) to yield a reasonable final structure. In this paper, we present a new method for interpolating and reparameterizing nodes within the growing string method using the linear synchronous transit method of Halgren and Lipscomb. When applied to the alanine dipeptide rearrangement and a simplified cationic alkyl ring condensation reaction, a significant speedup in terms of computational cost is achieved (30-50%).

Accuracy of heart rate variability estimation by photoplethysmography using an smartphone: Processing optimization and fiducial point selection.

PubMed

Ferrer-Mileo, V; Guede-Fernandez, F; Fernandez-Chimeno, M; Ramos-Castro, J; Garcia-Gonzalez, M A

2015-08-01

This work compares several fiducial points to detect the arrival of a new pulse in a photoplethysmographic signal using the built-in camera of smartphones or a photoplethysmograph. Also, an optimization process for the signal preprocessing stage has been done. Finally we characterize the error produced when we use the best cutoff frequencies and fiducial point for smartphones and photopletysmograph and compare if the error of smartphones can be reasonably be explained by variations in pulse transit time. The results have revealed that the peak of the first derivative and the minimum of the second derivative of the pulse wave have the lowest error. Moreover, for these points, high pass filtering the signal between 0.1 to 0.8 Hz and low pass around 2.7 Hz or 3.5 Hz are the best cutoff frequencies. Finally, the error in smartphones is slightly higher than in a photoplethysmograph.

FPFH-based graph matching for 3D point cloud registration

NASA Astrophysics Data System (ADS)

Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua

2018-04-01

Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.

Optimal high- and low-thrust geocentric transfer

NASA Technical Reports Server (NTRS)

Sackett, L. L.; Edelbaum, T. N.

1974-01-01

A computer code which rapidly calculates time optimal combined high- and low-thrust transfers between two geocentric orbits in the presence of a strong gravitational field has been developed as a mission analysis tool. The low-thrust portion of the transfer can be between any two arbitrary ellipses. There is an option for including the effect of two initial high-thrust impulses which would raise the spacecraft from a low, initially circular orbit to the initial orbit for the low-thrust portion of the transfer. In addition, the effect of a single final impulse after the low-thrust portion of the transfer may be included. The total Delta V for the initial two impulses must be specified as well as the Delta V for the final impulse. Either solar electric or nuclear electric propulsion can be assumed for the low-thrust phase of the transfer.

Cost Effective Bioethanol via Acid Pretreatment of Corn Stover, Saccharification, and Conversion via a Novel Fermentation Organism: Cooperative Research and Development Final Report, CRADA Number: CRD-12-485

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dowe, N.

2014-05-01

This research program will convert acid pretreated corn stover to sugars at the National Renewable Energy Laboratory (NREL) and then transfer these sugars to Honda R&D and its partner the Green Earth Institute (GEI) for conversion to ethanol via a novel fermentation organism. In phase one, NREL will adapt its pretreatment and saccharification process to the unique attributes of this organism, and Honda R&D/GEI will increase the sugar conversion rate as well as the yield and titer of the resulting ethanol. In later phases, NREL, Honda R&D, and GEI will work together at NREL to optimize and scale-up to pilot-scalemore » the Honda R&D/GEI bioethanol production process. The final stage will be to undertake a pilot-scale test at NREL of the optimized bioethanol conversion process.« less

Space Shuttle 2 advanced space transportation system, volume 2

NASA Technical Reports Server (NTRS)

Adinaro, James N.; Benefield, Philip A.; Johnson, Shelby D.; Knight, Lisa K.

1989-01-01

To determine the best configuration from all candidate configurations, it was necessary first to calculate minimum system weights and performance. To optimize the design, it is necessary to vary configuration-specific variables such as total system weight, thrust-to-weight ratios, burn durations, total thrust available, and mass fraction for the system. Optimizing each of these variables at the same time is technically unfeasible and not necessarily mathematically possible. However, discrete sets of data can be generated which will eliminate many candidate configurations. From the most promising remaining designs, a final configuration can be selected. Included are the three most important designs considered: one which closely approximates the design criteria set forth in a Marshall Space Flight Center study of the Shuttle 2; the configuration used in the initial proposal; and the final configuration. A listing by cell of the formulas used to generate the aforementioned data is included for reference.

Optimization of Maillard Reaction between Glucosamine and Other Precursors by Measuring Browning with a Spectrophotometer.

PubMed

Ogutu, Benrick; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Hong, Dong-Lee; Lee, Yang-Bong

2017-09-01

The individual Maillard reactions of glucose, glucosamine, cyclohexylamine, and benzylamine were studied at a fixed temperature of 120°C under different durations by monitoring the absorbance of the final products at 425 nm. Glucosamine was the most individually reactive compound, whereas the reactions of glucose, cyclohexylamine, and benzylamine were not significantly different from each other. Maillard reactions of reaction mixtures consisting of glucosamine-cyclohexylamine, glucosamine-benzylamine, glucose-cyclohexylamine, and glucose-benzylamine were also studied using different concentration ratios under different durations at a fixed temperature of 120°C and pH 9. Maillard reactions in the pairs involving glucosamine were observed to be more intense than those of the pairs involving glucose. Finally, with respect to the concentration ratios, it was observed that in most instances, optimal activity was realized, when the reaction mixtures were in the ratio of 1:1.

Optimization of Maillard Reaction between Glucosamine and Other Precursors by Measuring Browning with a Spectrophotometer

PubMed Central

Ogutu, Benrick; Kim, Ye-Joo; Kim, Dae-Wook; Oh, Sang-Chul; Hong, Dong-Lee; Lee, Yang-Bong

2017-01-01

The individual Maillard reactions of glucose, glucosamine, cyclohexylamine, and benzylamine were studied at a fixed temperature of 120°C under different durations by monitoring the absorbance of the final products at 425 nm. Glucosamine was the most individually reactive compound, whereas the reactions of glucose, cyclohexylamine, and benzylamine were not significantly different from each other. Maillard reactions of reaction mixtures consisting of glucosamine-cyclohexylamine, glucosamine-benzylamine, glucose-cyclohexylamine, and glucose-benzylamine were also studied using different concentration ratios under different durations at a fixed temperature of 120°C and pH 9. Maillard reactions in the pairs involving glucosamine were observed to be more intense than those of the pairs involving glucose. Finally, with respect to the concentration ratios, it was observed that in most instances, optimal activity was realized, when the reaction mixtures were in the ratio of 1:1. PMID:29043219

Optimizing noise control strategy in a forging workshop.

PubMed

Razavi, Hamideh; Ramazanifar, Ehsan; Bagherzadeh, Jalal

2014-01-01

In this paper, a computer program based on a genetic algorithm is developed to find an economic solution for noise control in a forging workshop. Initially, input data, including characteristics of sound sources, human exposure, abatement techniques, and production plans are inserted into the model. Using sound pressure levels at working locations, the operators who are at higher risk are identified and picked out for the next step. The program is devised in MATLAB such that the parameters can be easily defined and changed for comparison. The final results are structured into 4 sections that specify an appropriate abatement method for each operator and machine, minimum allowance time for high-risk operators, required damping material for enclosures, and minimum total cost of these treatments. The validity of input data in addition to proper settings in the optimization model ensures the final solution is practical and economically reasonable.

A free gingival impression for achieving optimal interdental papilla height: a case report.

PubMed

Nozawa, Takeshi; Kitami, Norikazu; Tsurumaki, Shunzo; Enomoto, Hiroaki; Ito, Koichi

2011-02-01

Failure to tend to inadequate crown contours in the crown trial can cause long-term disharmony of the free gingival form. This case report describes a novel technique for free gingival impression from a final provisional restoration to a zirconia crown. Two die casts were manufactured from a silicone impression. The first die cast was for the zirconia crown; the second die cast was for the final provisional restoration and the provisionalized transfer coping. A free gingival impression was taken using a provisionalized transfer coping, and a soft gingival model was manufactured. The proximal contact position was managed using the predicted convex curve of the interdental papillae. One year after zirconia crown placement, no inflammation was observed around the pyramidal interdental papillae, and symmetric interdental papilla heights were evident. A free gingival impression using a two die-cast technique appears to be useful for achieving optimal interdental papilla height.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Anode optimization for miniature electronic brachytherapy X-ray sources using Monte Carlo and computational fluid dynamic codes

PubMed Central

Khajeh, Masoud; Safigholi, Habib

2015-01-01

A miniature X-ray source has been optimized for electronic brachytherapy. The cooling fluid for this device is water. Unlike the radionuclide brachytherapy sources, this source is able to operate at variable voltages and currents to match the dose with the tumor depth. First, Monte Carlo (MC) optimization was performed on the tungsten target-buffer thickness layers versus energy such that the minimum X-ray attenuation occurred. Second optimization was done on the selection of the anode shape based on the Monte Carlo in water TG-43U1 anisotropy function. This optimization was carried out to get the dose anisotropy functions closer to unity at any angle from 0° to 170°. Three anode shapes including cylindrical, spherical, and conical were considered. Moreover, by Computational Fluid Dynamic (CFD) code the optimal target-buffer shape and different nozzle shapes for electronic brachytherapy were evaluated. The characterization criteria of the CFD were the minimum temperature on the anode shape, cooling water, and pressure loss from inlet to outlet. The optimal anode was conical in shape with a conical nozzle. Finally, the TG-43U1 parameters of the optimal source were compared with the literature. PMID:26966563

Ultraviolet (UV)-Curable Coatings for Department of Defense (DoD) Applications

DTIC Science & Technology

2009-09-01

complete) Task II – Demonstration/Validation • Make final selection of coatings for dem/val (in-progress) • Conduct lab testing and optimization (in...away; target rating of 4B or 5B Strippability Chemical Strippers Removal of the coating to the substrate Dry Media (blasting) Removal of the coating...stakeholders and ESTCP • Selected vendors to conduct final reformulation and submit for testing to JTP at the CTIO • Purchase portable lamp system

Orbital and angular motion construction for low thrust interplanetary flight

NASA Astrophysics Data System (ADS)

Yelnikov, R. V.; Mashtakov, Y. V.; Ovchinnikov, M. Yu.; Tkachev, S. S.

2016-11-01

Low thrust interplanetary flight is considered. Firstly, the fuel-optimal control is found. Then the angular motion is synthesized. This motion provides the thruster tracking of the required by optimal control direction. And, finally, reaction wheel control law for tracking this angular motion is proposed and implemented. The numerical example is given and total operation time for thrusters is found. Disturbances from solar pressure, thrust eccentricity, inaccuracy of reaction wheels installation and errors of inertia tensor are taken into account.

Variational Transition State Theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Truhlar, Donald G.

2016-09-29

This is the final report on a project involving the development and applications of variational transition state theory. This project involved the development of variational transition state theory for gas-phase reactions, including optimized multidimensional tunneling contributions and the application of this theory to gas-phase reactions with a special emphasis on developing reaction rate theory in directions that are important for applications to combustion. The development of variational transition state theory with optimized multidimensional tunneling as a useful computational tool for combustion kinetics involved eight objectives.

Genetic algorithm dynamics on a rugged landscape

NASA Astrophysics Data System (ADS)

Bornholdt, Stefan

1998-04-01

The genetic algorithm is an optimization procedure motivated by biological evolution and is successfully applied to optimization problems in different areas. A statistical mechanics model for its dynamics is proposed based on the parent-child fitness correlation of the genetic operators, making it applicable to general fitness landscapes. It is compared to a recent model based on a maximum entropy ansatz. Finally it is applied to modeling the dynamics of a genetic algorithm on the rugged fitness landscape of the NK model.

Limited Qualities Evaluation of Longitudinal Flight Control Systems Designed Using Multiobjective Control Design Techniques (HAVE INFINITY II)

DTIC Science & Technology

1998-06-01

analytical phase of this research. Finally, the mixed H2/H-Infinity method optimally tradeoff the different benefits offered by the separate H2 and H...potential benefits of the multiobjective design techniques used. Due to the HAVE INFINITY I test results, AFIT made the decision to continue the...sensitivity and complimentary sensitivity weighting, and a mixed H2/H-Infinity design that compromised the benefits of both design techniques optimally. The

The admissible portfolio selection problem with transaction costs and an improved PSO algorithm

NASA Astrophysics Data System (ADS)

Chen, Wei; Zhang, Wei-Guo

2010-05-01

In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets. We propose a new admissible efficient portfolio selection model and design an improved particle swarm optimization (PSO) algorithm because traditional optimization algorithms fail to work efficiently for our proposed problem. Finally, we offer a numerical example to illustrate the proposed effective approaches and compare the admissible portfolio efficient frontiers under different constraints.

Approximating the Basset force by optimizing the method of van Hinsberg et al.

NASA Astrophysics Data System (ADS)

Casas, G.; Ferrer, A.; Oñate, E.

2018-01-01

In this work we put the method proposed by van Hinsberg et al. [29] to the test, highlighting its accuracy and efficiency in a sequence of benchmarks of increasing complexity. Furthermore, we explore the possibility of systematizing the way in which the method's free parameters are determined by generalizing the optimization problem that was considered originally. Finally, we provide a list of worked-out values, ready for implementation in large-scale particle-laden flow simulations.

KdV-like equations for fluid dynamics

NASA Astrophysics Data System (ADS)

Ruggieri, M.; Speciale, M. P.

2014-12-01

Main goal of the authors is to consider the generalized system of KdV equations ut+uxxx+2uux+2e1vvx+e2(uxv+uvx)+e3vxxx = 0 c1vt+vxxx+2vvx+c2vx+c3(e1(uxv+uvx)+2e2uux+e3uxxx) = 0 (1), and to construct the optimal system of one dimensional subalgebras. The reduction of the above system to ODEs through the optimal systems is performed and finally an application is shown.

NMR reaction monitoring in flow synthesis

PubMed Central

Gomez, M Victoria

2017-01-01

Recent advances in the use of flow chemistry with in-line and on-line analysis by NMR are presented. The use of macro- and microreactors, coupled with standard and custom made NMR probes involving microcoils, incorporated into high resolution and benchtop NMR instruments is reviewed. Some recent selected applications have been collected, including synthetic applications, the determination of the kinetic and thermodynamic parameters and reaction optimization, even in single experiments and on the μL scale. Finally, software that allows automatic reaction monitoring and optimization is discussed. PMID:28326137

A ranking algorithm for spacelab crew and experiment scheduling

NASA Technical Reports Server (NTRS)

Grone, R. D.; Mathis, F. H.

1980-01-01

The problem of obtaining an optimal or near optimal schedule for scientific experiments to be performed on Spacelab missions is addressed. The current capabilities in this regard are examined and a method of ranking experiments in order of difficulty is developed to support the existing software. Experimental data is obtained from applying this method to the sets of experiments corresponding to Spacelab mission 1, 2, and 3. Finally, suggestions are made concerning desirable modifications and features of second generation software being developed for this problem.

NMR reaction monitoring in flow synthesis.

PubMed

Gomez, M Victoria; de la Hoz, Antonio

2017-01-01

Recent advances in the use of flow chemistry with in-line and on-line analysis by NMR are presented. The use of macro- and microreactors, coupled with standard and custom made NMR probes involving microcoils, incorporated into high resolution and benchtop NMR instruments is reviewed. Some recent selected applications have been collected, including synthetic applications, the determination of the kinetic and thermodynamic parameters and reaction optimization, even in single experiments and on the μL scale. Finally, software that allows automatic reaction monitoring and optimization is discussed.

Adsorption of charged albumin subdomains on a graphite surface.

PubMed

Raffaini, Giuseppina; Ganazzoli, Fabio

2006-03-01

We report some new molecular dynamics simulation results about the adsorption on a hydrophobic graphite surface of two albumin subdomains, each formed by three different alpha-helices, considering the correctly charged side groups at pH = 7 instead of the neutral ones as done in our previous exploratory paper (Raffaini and Ganazzoli, Langmuir 2003;19:3403-3412). We find that the presence of charges affects somewhat the initial adsorption stage on the electrostatically neutral surface, but not the final one. Thus, we recover the result that a monolayer of aminoacids is eventually formed, with a rough parallelism of distant strands to optimize both the intramolecular and the surface interactions. This feature is consistent with the adsorption on the hydrophobic surface being driven by dispersion forces only, and with the "soft" nature of albumin. Additional optimizations of the final monolayer carried out at pH = 3 and 11 do not modify appreciably this picture, suggesting that adsorption on graphite is basically independent of pH. The enhanced hydration of the final adsorption state due to the (delocalized) charges of the side groups is also discussed in comparison with similar results of the neutralized subdomains. (c) 2005 Wiley Periodicals, Inc.

Binary-Phase Fourier Gratings for Nonuniform Array Generation

NASA Technical Reports Server (NTRS)

Keys, Andrew S.; Crow, Robert W.; Ashley, Paul R.

2003-01-01

We describe a design method for a binary-phase Fourier grating that generates an array of spots with nonuniform, user-defined intensities symmetric about the zeroth order. Like the Dammann fanout grating approach, the binary-phase Fourier grating uses only two phase levels in its grating surface profile to generate the final spot array. Unlike the Dammann fanout grating approach, this method allows for the generation of nonuniform, user-defined intensities within the final fanout pattern. Restrictions governing the specification and realization of the array's individual spot intensities are discussed. Design methods used to realize the grating employ both simulated annealing and nonlinear optimization approaches to locate optimal solutions to the grating design problem. The end-use application driving this development operates in the near- to mid-infrared spectrum - allowing for higher resolution in grating specification and fabrication with respect to wavelength than may be available in visible spectrum applications. Fabrication of a grating generating a user-defined nine spot pattern is accomplished in GaAs for the near-infrared. Characterization of the grating is provided through the measurement of individual spot intensities, array uniformity, and overall efficiency. Final measurements are compared to calculated values with a discussion of the results.

Optimal control of LQG problem with an explicit trade-off between mean and variance

NASA Astrophysics Data System (ADS)

Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

2011-12-01

For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.

Phase noise optimization in temporal phase-shifting digital holography with partial coherence light sources and its application in quantitative cell imaging.

PubMed

Remmersmann, Christian; Stürwald, Stephan; Kemper, Björn; Langehanenberg, Patrik; von Bally, Gert

2009-03-10

In temporal phase-shifting-based digital holographic microscopy, high-resolution phase contrast imaging requires optimized conditions for hologram recording and phase retrieval. To optimize the phase resolution, for the example of a variable three-step algorithm, a theoretical analysis on statistical errors, digitalization errors, uncorrelated errors, and errors due to a misaligned temporal phase shift is carried out. In a second step the theoretically predicted results are compared to the measured phase noise obtained from comparative experimental investigations with several coherent and partially coherent light sources. Finally, the applicability for noise reduction is demonstrated by quantitative phase contrast imaging of pancreas tumor cells.

Optimization experiments with a double Gauss lens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brixner, B.; Klein, M.M.

1988-05-01

This paper describes how a lens can be generated by starting from plane surfaces. Three different experiments, using the Los Alamos National Laboratory optimization procedure, all converged on the same stable prescriptions in the optimum minimum region. The starts were made first from an already optimized lens appearing in the literature, then from a powerless plane-surfaces configuration, and finally from a crude Super Angulon configuration. In each case the result was a double Gauss lens, which suggests that this type of lens may be the best compact six-glass solution for one imaging problem: an f/2 aperture and a moderate fieldmore » of view. The procedures and results are discussed in detail.« less

Optimization Experiments With A Double Gauss Lens

NASA Astrophysics Data System (ADS)

Brixner, Berlyn; Klein, Morris M.

1988-05-01

This paper describes how a lens can be generated by starting from plane surfaces. Three different experiments, using the Los Alamos National Laboratory optimization procedure, all converged on the same stable prescriptions in the optimum minimum region. The starts were made first from an already optimized lens appearing in the literature, then from a powerless plane-surfaces configuration, and finally from a crude Super Angulon configuration. In each case the result was a double Gauss lens, which suggests that this type of lens may be the best compact six-glass solution for one imaging problem: an f/2 aperture and a moderate field of view. The procedures and results are discussed in detail.

Optimization research of railway passenger transfer scheme based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Ni, Xiang

2018-05-01

The optimization research of railway passenger transfer scheme can provide strong support for railway passenger transport system, and its essence is path search. This paper realized the calculation of passenger transfer scheme for high speed railway when giving the time and stations of departure and arrival. The specific method that used were generating a passenger transfer service network of high-speed railway, establishing optimization model and searching by Ant Colony Algorithm. Finally, making analysis on the scheme from LanZhouxi to BeiJingXi which were based on high-speed railway network of China in 2017. The results showed that the transfer network and model had relatively high practical value and operation efficiency.

Design and optimization of a high-efficiency array generator in the mid-IR with binary subwavelength grooves.

PubMed

Bloom, Guillaume; Larat, Christian; Lallier, Eric; Lee-Bouhours, Mane-Si Laure; Loiseaux, Brigitte; Huignard, Jean-Pierre

2011-02-10

We have designed a high-efficiency array generator composed of subwavelength grooves etched in a GaAs substrate for operation at 4.5 μm. The method used combines rigorous coupled wave analysis with an optimization algorithm. The optimized beam splitter has both a high efficiency (∼96%) and a good intensity uniformity (∼0.2%). The fabrication error tolerances are numerically calculated, and it is shown that this subwavelength array generator could be fabricated with current electron beam writers and inductively coupled plasma etching. Finally, we studied the effect of a simple and realistic antireflection coating on the performance of the beam splitter.

Optimization design of turbo-expander gas bearing for a 500W helium refrigerator

NASA Astrophysics Data System (ADS)

Li, S. S.; Fu, B.; Y Zhang, Q.

2017-12-01

Turbo-expander is the core machinery of the helium refrigerator. Bearing as the supporting element is the core technology to impact the design of turbo-expander. The perfect design and performance study for the gas bearing are essential to ensure the stability of turbo-expander. In this paper, numerical simulation is used to analyze the performance of gas bearing for a 500W helium refrigerator turbine, and the optimization design of the gas bearing has been completed. And the results of the gas bearing optimization have a guiding role in the processing technology. Finally, the turbine experiments verify that the gas bearing has good performance, and ensure the stable operation of the turbine.

Optimal Pitch Thrust-Vector Angle and Benefits for all Flight Regimes

NASA Technical Reports Server (NTRS)

Gilyard, Glenn B.; Bolonkin, Alexander

2000-01-01

The NASA Dryden Flight Research Center is exploring the optimum thrust-vector angle on aircraft. Simple aerodynamic performance models for various phases of aircraft flight are developed and optimization equations and algorithms are presented in this report. Results of optimal angles of thrust vectors and associated benefits for various flight regimes of aircraft (takeoff, climb, cruise, descent, final approach, and landing) are given. Results for a typical wide-body transport aircraft are also given. The benefits accruable for this class of aircraft are small, but the technique can be applied to other conventionally configured aircraft. The lower L/D aerodynamic characteristics of fighters generally would produce larger benefits than those produced for transport aircraft.

Analytic model for ultrasound energy receivers and their optimal electric loads II: Experimental validation

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-10-01

In this paper, we verify the two optimal electric load concepts based on the zero reflection condition and on the power maximization approach for ultrasound energy receivers. We test a high loss 1-3 composite transducer, and find that the measurements agree very well with the predictions of the analytic model for plate transducers that we have developed previously. Additionally, we also confirm that the power maximization and zero reflection loads are very different when the losses in the receiver are high. Finally, we compare the optimal load predictions by the KLM and the analytic models with frequency dependent attenuation to evaluate the influence of the viscosity.

Analytic model for ultrasound energy receivers and their optimal electric loads

NASA Astrophysics Data System (ADS)

Gorostiaga, M.; Wapler, M. C.; Wallrabe, U.

2017-08-01

In this paper, we present an analytic model for thickness resonating plate ultrasound energy receivers, which we have derived from the piezoelectric and the wave equations and, in which we have included dielectric, viscosity and acoustic attenuation losses. Afterwards, we explore the optimal electric load predictions by the zero reflection and power maximization approaches present in the literature with different acoustic boundary conditions, and discuss their limitations. To validate our model, we compared our expressions with the KLM model solved numerically with very good agreement. Finally, we discuss the differences between the zero reflection and power maximization optimal electric loads, which start to differ as losses in the receiver increase.

Outsourcing lead optimization: the eye of the storm.

PubMed

Clark, David E

2011-02-01

This article is the third in a series examining the evolution of the market for outsourced lead optimization services and covers developments from late 2006 to the present. Following an analysis of the significant events that have impacted the marketplace in recent years, a brief survey of the growing number of companies offering lead optimization services is presented. Subsequently, three notable trends that can be perceived in this highly dynamic field are discussed: the continuing rise of outsourcing companies in Asia and Eastern Europe, the increase in deals with not-for-profit organizations and, finally, the emergence of a variety of business models under which outsourced work is conducted. Copyright © 2010 Elsevier Ltd. All rights reserved.

Optimal symmetric flight with an intermediate vehicle model

NASA Technical Reports Server (NTRS)

Menon, P. K. A.; Kelley, H. J.; Cliff, E. M.

1983-01-01

Optimal flight in the vertical plane with a vehicle model intermediate in complexity between the point-mass and energy models is studied. Flight-path angle takes on the role of a control variable. Range-open problems feature subarcs of vertical flight and singular subarcs. The class of altitude-speed-range-time optimization problems with fuel expenditure unspecified is investigated and some interesting phenomena uncovered. The maximum-lift-to-drag glide appears as part of the family, final-time-open, with appropriate initial and terminal transient exceeding level-flight drag, some members exhibiting oscillations. Oscillatory paths generally fail the Jacobi test for durations exceeding a period and furnish a minimum only for short-duration problems.

Generalized Differential Calculus and Applications to Optimization

NASA Astrophysics Data System (ADS)

Rector, Robert Blake Hayden

This thesis contains contributions in three areas: the theory of generalized calculus, numerical algorithms for operations research, and applications of optimization to problems in modern electric power systems. A geometric approach is used to advance the theory and tools used for studying generalized notions of derivatives for nonsmooth functions. These advances specifically pertain to methods for calculating subdifferentials and to expanding our understanding of a certain notion of derivative of set-valued maps, called the coderivative, in infinite dimensions. A strong understanding of the subdifferential is essential for numerical optimization algorithms, which are developed and applied to nonsmooth problems in operations research, including non-convex problems. Finally, an optimization framework is applied to solve a problem in electric power systems involving a smart solar inverter and battery storage system providing energy and ancillary services to the grid.

Building of Reusable Reverse Logistics Model and its Optimization Considering the Decision of Backorder or Next Arrival of Goods

NASA Astrophysics Data System (ADS)

Lee, Jeong-Eun; Gen, Mitsuo; Rhee, Kyong-Gu; Lee, Hee-Hyol

This paper deals with the building of the reusable reverse logistics model considering the decision of the backorder or the next arrival of goods. The optimization method to minimize the transportation cost and to minimize the volume of the backorder or the next arrival of goods occurred by the Just in Time delivery of the final delivery stage between the manufacturer and the processing center is proposed. Through the optimization algorithms using the priority-based genetic algorithm and the hybrid genetic algorithm, the sub-optimal delivery routes are determined. Based on the case study of a distilling and sale company in Busan in Korea, the new model of the reusable reverse logistics of empty bottles is built and the effectiveness of the proposed method is verified.

A Numerical-Analytical Approach Based on Canonical Transformations for Computing Optimal Low-Thrust Transfers

NASA Astrophysics Data System (ADS)

da Silva Fernandes, S.; das Chagas Carvalho, F.; Bateli Romão, J. V.

2018-04-01

A numerical-analytical procedure based on infinitesimal canonical transformations is developed for computing optimal time-fixed low-thrust limited power transfers (no rendezvous) between coplanar orbits with small eccentricities in an inverse-square force field. The optimization problem is formulated as a Mayer problem with a set of non-singular orbital elements as state variables. Second order terms in eccentricity are considered in the development of the maximum Hamiltonian describing the optimal trajectories. The two-point boundary value problem of going from an initial orbit to a final orbit is solved by means of a two-stage Newton-Raphson algorithm which uses an infinitesimal canonical transformation. Numerical results are presented for some transfers between circular orbits with moderate radius ratio, including a preliminary analysis of Earth-Mars and Earth-Venus missions.

Multi-objective optimal design of sandwich panels using a genetic algorithm

NASA Astrophysics Data System (ADS)

Xu, Xiaomei; Jiang, Yiping; Pueh Lee, Heow

2017-10-01

In this study, an optimization problem concerning sandwich panels is investigated by simultaneously considering the two objectives of minimizing the panel mass and maximizing the sound insulation performance. First of all, the acoustic model of sandwich panels is discussed, which provides a foundation to model the acoustic objective function. Then the optimization problem is formulated as a bi-objective programming model, and a solution algorithm based on the non-dominated sorting genetic algorithm II (NSGA-II) is provided to solve the proposed model. Finally, taking an example of a sandwich panel that is expected to be used as an automotive roof panel, numerical experiments are carried out to verify the effectiveness of the proposed model and solution algorithm. Numerical results demonstrate in detail how the core material, geometric constraints and mechanical constraints impact the optimal designs of sandwich panels.

A niching genetic algorithm applied to optimize a SiC-bulk crystal growth system

NASA Astrophysics Data System (ADS)

Su, Juan; Chen, Xuejiang; Li, Yuan; Pons, Michel; Blanquet, Elisabeth

2017-06-01

A niching genetic algorithm (NGA) was presented to optimize a SiC-bulk crystal growth system by PVT. The NGA based on clearing mechanism and its combination method with heat transfer model for SiC crystal growth were described in details. Then three inverse problems for optimization of growth system were carried out by NGA. Firstly, the radius of blind hole was optimized to decrease the radial temperature gradient along the substrate while the center temperature on the surface of substrate is fixed at 2500 K. Secondly, insulation materials with anisotropic thermal conductivities were selected to obtain much higher growth rate as 600, 800 and 1000 μm/h. Finally, the density of coils was also rearranged to minimize the temperature variation in the SiC powder. All the results were analyzed and discussed.

[The application of operating room quality backward system in instrument place management].

PubMed

Du, Hui; He, Anjie; Zeng, Leilei

2010-09-01

Improvement of the surgery instrument's clean quality, the optimized preparation way, reasonable arrangement in groups, raising the working efficiency. We use the quality backward system into the instrument clean, the pack and the preparation way's question, carry on the analysis and the optimization, and appraise the effect after trying out 6 months. After finally the way optimized, instrument clean quality distinct enhancement; The flaws in the instrument clean, the pack way and the total operating time reduce; the contradictory between nurses and the cleans arising from the unclear connection reduces, the satisfaction degree of nurse and doctor to the instrument enhances. Using of operating room quality backward system in the management of the instrument clean, the pack and the preparation way optimized, may reduce flaws in the work and the waste of human resources, raise the working efficiency.

Guidance control of small UAV with energy and maneuverability limitations for a search and coverage mission

NASA Astrophysics Data System (ADS)

Gramajo, German G.

This thesis presents an algorithm for a search and coverage mission that has increased autonomy in generating an ideal trajectory while explicitly considering the available energy in the optimization. Further, current algorithms used to generate trajectories depend on the operator providing a discrete set of turning rate requirements to obtain an optimal solution. This work proposes an additional modification to the algorithm so that it optimizes the trajectory for a range of turning rates instead of a discrete set of turning rates. This thesis conducts an evaluation of the algorithm with variation in turn duration, entry-heading angle, and entry point. Comparative studies of the algorithm with existing method indicates improved autonomy in choosing the optimization parameters while producing trajectories with better coverage area and closer final distance to the desired terminal point.

Optimal Periodic Cooperative Spectrum Sensing Based on Weight Fusion in Cognitive Radio Networks

PubMed Central

Liu, Xin; Jia, Min; Gu, Xuemai; Tan, Xuezhi

2013-01-01

The performance of cooperative spectrum sensing in cognitive radio (CR) networks depends on the sensing mode, the sensing time and the number of cooperative users. In order to improve the sensing performance and reduce the interference to the primary user (PU), a periodic cooperative spectrum sensing model based on weight fusion is proposed in this paper. Moreover, the sensing period, the sensing time and the searching time are optimized, respectively. Firstly the sensing period is optimized to improve the spectrum utilization and reduce the interference, then the joint optimization algorithm of the local sensing time and the number of cooperative users, is proposed to obtain the optimal sensing time for improving the throughput of the cognitive radio user (CRU) during each period, and finally the water-filling principle is applied to optimize the searching time in order to make the CRU find an idle channel within the shortest time. The simulation results show that compared with the previous algorithms, the optimal sensing period can improve the spectrum utilization of the CRU and decrease the interference to the PU significantly, the optimal sensing time can make the CRU achieve the largest throughput, and the optimal searching time can make the CRU find an idle channel with the least time. PMID:23604027

Guidance and Control strategies for aerospace vehicles

NASA Technical Reports Server (NTRS)

Hibey, J. L.; Naidu, D. S.; Charalambous, C. D.

1989-01-01

A neighboring optimal guidance scheme was devised for a nonlinear dynamic system with stochastic inputs and perfect measurements as applicable to fuel optimal control of an aeroassisted orbital transfer vehicle. For the deterministic nonlinear dynamic system describing the atmospheric maneuver, a nominal trajectory was determined. Then, a neighboring, optimal guidance scheme was obtained for open loop and closed loop control configurations. Taking modelling uncertainties into account, a linear, stochastic, neighboring optimal guidance scheme was devised. Finally, the optimal trajectory was approximated as the sum of the deterministic nominal trajectory and the stochastic neighboring optimal solution. Numerical results are presented for a typical vehicle. A fuel-optimal control problem in aeroassisted noncoplanar orbital transfer is also addressed. The equations of motion for the atmospheric maneuver are nonlinear and the optimal (nominal) trajectory and control are obtained. In order to follow the nominal trajectory under actual conditions, a neighboring optimum guidance scheme is designed using linear quadratic regulator theory for onboard real-time implementation. One of the state variables is used as the independent variable in reference to the time. The weighting matrices in the performance index are chosen by a combination of a heuristic method and an optimal modal approach. The necessary feedback control law is obtained in order to minimize the deviations from the nominal conditions.

Identifying best practices for snowplow route optimization : final report.

DOT National Transportation Integrated Search

2016-12-01

Well-designed winter maintenance routes result in snow and ice control service that is both more effective, because roads are cleared more rapidly, and more cost-efficient, because deadheading, route overlap and other inefficiencies are reduced or el...

OPTIMAL DESIGN FOR MULTINOMIAL CHOICE EXPERIMENTS. (R827987)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Ring rolling process simulation for geometry optimization

NASA Astrophysics Data System (ADS)

Franchi, Rodolfo; Del Prete, Antonio; Donatiello, Iolanda; Calabrese, Maurizio

2017-10-01

Ring Rolling is a complex hot forming process where different rolls are involved in the production of seamless rings. Since each roll must be independently controlled, different speed laws must be set; usually, in the industrial environment, a milling curve is introduced to monitor the shape of the workpiece during the deformation in order to ensure the correct ring production. In the present paper a ring rolling process has been studied and optimized in order to obtain anular components to be used in aerospace applications. In particular, the influence of process input parameters (feed rate of the mandrel and angular speed of main roll) on geometrical features of the final ring has been evaluated. For this purpose, a three-dimensional finite element model for HRR (Hot Ring Rolling) has been implemented in SFTC DEFORM V11. The FEM model has been used to formulate a proper optimization problem. The optimization procedure has been implemented in the commercial software DS ISight in order to find the combination of process parameters which allows to minimize the percentage error of each obtained dimension with respect to its nominal value. The software allows to find the relationship between input and output parameters applying Response Surface Methodology (RSM), by using the exact values of output parameters in the control points of the design space explored through FEM simulation. Once this relationship is known, the values of the output parameters can be calculated for each combination of the input parameters. After the calculation of the response surfaces for the selected output parameters, an optimization procedure based on Genetic Algorithms has been applied. At the end, the error between each obtained dimension and its nominal value has been minimized. The constraints imposed were the maximum values of standard deviations of the dimensions obtained for the final ring.

Desirability-based methods of multiobjective optimization and ranking for global QSAR studies. Filtering safe and potent drug candidates from combinatorial libraries.

PubMed

Cruz-Monteagudo, Maykel; Borges, Fernanda; Cordeiro, M Natália D S; Cagide Fajin, J Luis; Morell, Carlos; Ruiz, Reinaldo Molina; Cañizares-Carmenate, Yudith; Dominguez, Elena Rosa

2008-01-01

Up to now, very few applications of multiobjective optimization (MOOP) techniques to quantitative structure-activity relationship (QSAR) studies have been reported in the literature. However, none of them report the optimization of objectives related directly to the final pharmaceutical profile of a drug. In this paper, a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies, simultaneously considering the potency, bioavailability, and safety of a set of drug candidates, is introduced. The results of the desirability-based MOOP (the levels of the predictor variables concurrently producing the best possible compromise between the properties determining an optimal drug candidate) are used for the implementation of a ranking method that is also based on the application of desirability functions. This method allows ranking drug candidates with unknown pharmaceutical properties from combinatorial libraries according to the degree of similarity with the previously determined optimal candidate. Application of this method will make it possible to filter the most promising drug candidates of a library (the best-ranked candidates), which should have the best pharmaceutical profile (the best compromise between potency, safety and bioavailability). In addition, a validation method of the ranking process, as well as a quantitative measure of the quality of a ranking, the ranking quality index (Psi), is proposed. The usefulness of the desirability-based methods of MOOP and ranking is demonstrated by its application to a library of 95 fluoroquinolones, reporting their gram-negative antibacterial activity and mammalian cell cytotoxicity. Finally, the combined use of the desirability-based methods of MOOP and ranking proposed here seems to be a valuable tool for rational drug discovery and development.

Improved protein kinase C affinity through final step diversification of a simplified salicylate-derived bryostatin analog scaffold.

PubMed

Wender, Paul A; Staveness, Daryl

2014-10-03

Bryostatin 1, in clinical trials or preclinical development for cancer, Alzheimer's disease, and a first-of-its-kind strategy for HIV/AIDS eradication, is neither readily available nor optimally suited for clinical use. In preceding work, we disclosed a new class of simplified bryostatin analogs designed for ease of access and tunable activity. Here we describe a final step diversification strategy that provides, in only 25 synthetic steps, simplified and tunable analogs with bryostatin-like PKC modulatory activities.

Collection of X-ray diffraction data from macromolecular crystals

PubMed Central

Dauter, Zbigniew

2017-01-01

Diffraction data acquisition is the final experimental stage of the crystal structure analysis. All subsequent steps involve mainly computer calculations. Optimally measured and accurate data make the structure solution and refinement easier and lead to more faithful interpretation of the final models. Here, the important factors in data collection from macromolecular crystals are discussed and strategies appropriate for various applications, such as molecular replacement, anomalous phasing, atomic-resolution refinement etc., are presented. Criteria useful for judging the diffraction data quality are also discussed. PMID:28573573

Grey fuzzy optimization model for water quality management of a river system

NASA Astrophysics Data System (ADS)

Karmakar, Subhankar; Mujumdar, P. P.

2006-07-01

A grey fuzzy optimization model is developed for water quality management of river system to address uncertainty involved in fixing the membership functions for different goals of Pollution Control Agency (PCA) and dischargers. The present model, Grey Fuzzy Waste Load Allocation Model (GFWLAM), has the capability to incorporate the conflicting goals of PCA and dischargers in a deterministic framework. The imprecision associated with specifying the water quality criteria and fractional removal levels are modeled in a fuzzy mathematical framework. To address the imprecision in fixing the lower and upper bounds of membership functions, the membership functions themselves are treated as fuzzy in the model and the membership parameters are expressed as interval grey numbers, a closed and bounded interval with known lower and upper bounds but unknown distribution information. The model provides flexibility for PCA and dischargers to specify their aspirations independently, as the membership parameters for different membership functions, specified for different imprecise goals are interval grey numbers in place of a deterministic real number. In the final solution optimal fractional removal levels of the pollutants are obtained in the form of interval grey numbers. This enhances the flexibility and applicability in decision-making, as the decision-maker gets a range of optimal solutions for fixing the final decision scheme considering technical and economic feasibility of the pollutant treatment levels. Application of the GFWLAM is illustrated with case study of the Tunga-Bhadra river system in India.

Optimization of individualized graft composition: CD3/CD19 depletion combined with CD34 selection for haploidentical transplantation.

PubMed

Huenecke, Sabine; Bremm, Melanie; Cappel, Claudia; Esser, Ruth; Quaiser, Andrea; Bonig, Halvard; Jarisch, Andrea; Soerensen, Jan; Klingebiel, Thomas; Bader, Peter; Koehl, Ulrike

2016-09-01

Excessive T-cell depletion (TCD) is a prerequisite for graft manufacturing in haploidentical stem cell (SC) transplantation by using either CD34 selection or direct TCD such as CD3/CD19 depletion. To optimize graft composition we compared 1) direct or indirect TCD only, 2) a combination of CD3/CD19-depleted with CD34-selected grafts, or 3) TCD twice for depletion improvement based on our 10-year experience with 320 separations in graft manufacturing and quality control. SC recovery was significantly higher (85%, n = 187 vs. 73%, n = 115; p < 0.0001), but TCD was inferior (median log depletion, -3.6 vs. -5.2) for CD3/CD19 depletion compared to CD34 selection, respectively. For end products with less than -2.5 log TCD, a second depletion step led to a successful improvement in TCD. Thawing of grafts showed a high viability and recovery of SCs, but low NK-cell yield. To optimize individualized graft engineering, a calculator was developed to estimate the results of the final graft based on the content of CD34+ and CD3+ cells in the leukapheresis product. Finally, calculated splitting of the starting product followed by CD3/19 depletion together with CD34+ graft manipulation may enable the composition of optimized grafts with high CD34+-cell and minimal T-cell content. © 2016 AABB.

Essential strategies to optimize asymmetric PCR conditions as a reliable method to generate large amount of ssDNA aptamers.

PubMed

Heiat, Mohammad; Ranjbar, Reza; Latifi, Ali Mohammad; Rasaee, Mohammad Javad; Farnoosh, Gholamreza

2017-07-01

Asymmetric PCR, a simple method to generate single-stranded DNA (ssDNA) aptamers in systematic evaluation of ligand by exponential enrichments rounds, is coupled with limitations. We investigated the essential strategies for optimization of conditions to perform a high-quality asymmetric PCR. Final concentrations of primers and template, the number of PCR cycles, and annealing temperature were selected as optimizing variables. The qualities of visualized PCR products were analyzed by ImageJ software. The highest proportion of interested DNA than unwanted products was considered as optimum conditions. Results revealed that the best values for primers ratio, final template concentration, annealing temperature, and PCR cycles were, respectively, 30:1, 1 ng/μL, 55 °C, and 20 cycles for the first and 50:1, 2 ng/μL, 59 °C, and 20 cycles for other rounds. No significant difference was found between optimized asymmetric PCR results in the rounds of two to eight (P > 0.05). The ssDNA quality in round 10 was significantly better than other rounds (P < 0.05). Generally, the ssDNA product with less dimers, double-stranded DNA (dsDNA), and smear are preferable. The dsDNA contamination is the worst, because it can act as antidote and inhibits aptameric performance. Therefore, to choose the best conditions, the lower amount of dsDNA is more important than other unwanted products. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

A triaxial accelerometer monkey algorithm for optimal sensor placement in structural health monitoring

NASA Astrophysics Data System (ADS)

Jia, Jingqing; Feng, Shuo; Liu, Wei

2015-06-01

Optimal sensor placement (OSP) technique is a vital part of the field of structural health monitoring (SHM). Triaxial accelerometers have been widely used in the SHM of large-scale structures in recent years. Triaxial accelerometers must be placed in such a way that all of the important dynamic information is obtained. At the same time, the sensor configuration must be optimal, so that the test resources are conserved. The recommended practice is to select proper degrees of freedom (DOF) based upon several criteria and the triaxial accelerometers are placed at the nodes corresponding to these DOFs. This results in non-optimal placement of many accelerometers. A ‘triaxial accelerometer monkey algorithm’ (TAMA) is presented in this paper to solve OSP problems of triaxial accelerometers. The EFI3 measurement theory is modified and involved in the objective function to make it more adaptable in the OSP technique of triaxial accelerometers. A method of calculating the threshold value based on probability theory is proposed to improve the healthy rate of monkeys in a troop generation process. Meanwhile, the processes of harmony ladder climb and scanning watch jump are proposed and given in detail. Finally, Xinghai NO.1 Bridge in Dalian is implemented to demonstrate the effectiveness of TAMA. The final results obtained by TAMA are compared with those of the original monkey algorithm and EFI3 measurement, which show that TAMA can improve computational efficiency and get a better sensor configuration.

Training-based descreening.

PubMed

Siddiqui, Hasib; Bouman, Charles A

2007-03-01

Conventional halftoning methods employed in electrophotographic printers tend to produce Moiré artifacts when used for printing images scanned from printed material, such as books and magazines. We present a novel approach for descreening color scanned documents aimed at providing an efficient solution to the Moiré problem in practical imaging devices, including copiers and multifunction printers. The algorithm works by combining two nonlinear image-processing techniques, resolution synthesis-based denoising (RSD), and modified smallest univalue segment assimilating nucleus (SUSAN) filtering. The RSD predictor is based on a stochastic image model whose parameters are optimized beforehand in a separate training procedure. Using the optimized parameters, RSD classifies the local window around the current pixel in the scanned image and applies filters optimized for the selected classes. The output of the RSD predictor is treated as a first-order estimate to the descreened image. The modified SUSAN filter uses the output of RSD for performing an edge-preserving smoothing on the raw scanned data and produces the final output of the descreening algorithm. Our method does not require any knowledge of the screening method, such as the screen frequency or dither matrix coefficients, that produced the printed original. The proposed scheme not only suppresses the Moiré artifacts, but, in addition, can be trained with intrinsic sharpening for deblurring scanned documents. Finally, once optimized for a periodic clustered-dot halftoning method, the same algorithm can be used to inverse halftone scanned images containing stochastic error diffusion halftone noise.

Optimal layout design of obstacles for panic evacuation using differential evolution

NASA Astrophysics Data System (ADS)

Zhao, Yongxiang; Li, Meifang; Lu, Xin; Tian, Lijun; Yu, Zhiyong; Huang, Kai; Wang, Yana; Li, Ting

2017-01-01

To improve the pedestrian outflow in panic situations by suitably placing an obstacle in front of the exit, it is vital to understand the physical mechanism behind the evacuation efficiency enhancement. In this paper, a robust differential evolution is firstly employed to optimize the geometrical parameters of different shaped obstacles in order to achieve an optimal evacuation efficiency. Moreover, it is found that all the geometrical parameters of obstacles could markedly influence the evacuation efficiency of pedestrians, and the best way for achieving an optimal pedestrian outflow is to slightly shift the obstacle from the center of the exit which is consistent with findings of extant literature. Most importantly, by analyzing the profiles of density, velocity and specific flow, as well as the spatial distribution of crowd pressure, we have proven that placing an obstacle in panic situations does not reduce or absorb the pressure in the region of exit, on the contrary, promotes the pressure to a much higher level, hence the physical mechanism behind the evacuation efficiency enhancement is not a pressure decrease in the region of exit, but a significant reduction of high density region by effective separation in space which finally causes the increasing of escape speed and evacuation outflow. Finally, it is clearly demonstrated that the panel-like obstacle is considerably more robust and stable than the pillar-like obstacle to guarantee the enhancement of evacuation efficiency under different initial pedestrian distributions, different initial crowd densities as well as different desired velocities.

Acoustic design of boundary segments in aircraft fuselages using topology optimization and a specialized acoustic pressure function

NASA Astrophysics Data System (ADS)

Radestock, Martin; Rose, Michael; Monner, Hans Peter

2017-04-01

In most aviation applications, a major cost benefit can be achieved by a reduction of the system weight. Often the acoustic properties of the fuselage structure are not in the focus of the primary design process, too. A final correction of poor acoustic properties is usually done using insulation mats in the chamber between the primary and secondary shell. It is plausible that a more sophisticated material distribution in that area can result in a substantially reduced weight. Topology optimization is a well-known approach to reduce material of compliant structures. In this paper an adaption of this method to acoustic problems is investigated. The gap full of insulation mats is suitably parameterized to achieve different material distributions. To find advantageous configurations, the objective in the underlying topology optimization is chosen to obtain good acoustic pressure patterns in the aircraft cabin. An important task in the optimization is an adequate Finite Element model of the system. This can usually not be obtained from commercially available programs due to the lack of special sensitivity data with respect to the design parameters. Therefore an appropriate implementation of the algorithm has been done, exploiting the vector and matrix capabilities in the MATLABQ environment. Finally some new aspects of the Finite Element implementation will also be presented, since they are interesting on its own and can be generalized to efficiently solve other partial differential equations as well.

Genetic programming assisted stochastic optimization strategies for optimization of glucose to gluconic acid fermentation.

PubMed

Cheema, Jitender Jit Singh; Sankpal, Narendra V; Tambe, Sanjeev S; Kulkarni, Bhaskar D

2002-01-01

This article presents two hybrid strategies for the modeling and optimization of the glucose to gluconic acid batch bioprocess. In the hybrid approaches, first a novel artificial intelligence formalism, namely, genetic programming (GP), is used to develop a process model solely from the historic process input-output data. In the next step, the input space of the GP-based model, representing process operating conditions, is optimized using two stochastic optimization (SO) formalisms, viz., genetic algorithms (GAs) and simultaneous perturbation stochastic approximation (SPSA). These SO formalisms possess certain unique advantages over the commonly used gradient-based optimization techniques. The principal advantage of the GP-GA and GP-SPSA hybrid techniques is that process modeling and optimization can be performed exclusively from the process input-output data without invoking the detailed knowledge of the process phenomenology. The GP-GA and GP-SPSA techniques have been employed for modeling and optimization of the glucose to gluconic acid bioprocess, and the optimized process operating conditions obtained thereby have been compared with those obtained using two other hybrid modeling-optimization paradigms integrating artificial neural networks (ANNs) and GA/SPSA formalisms. Finally, the overall optimized operating conditions given by the GP-GA method, when verified experimentally resulted in a significant improvement in the gluconic acid yield. The hybrid strategies presented here are generic in nature and can be employed for modeling and optimization of a wide variety of batch and continuous bioprocesses.

Optimal colour quality of LED clusters based on memory colours.

PubMed

Smet, Kevin; Ryckaert, Wouter R; Pointer, Michael R; Deconinck, Geert; Hanselaer, Peter

2011-03-28

The spectral power distributions of tri- and tetrachromatic clusters of Light-Emitting-Diodes, composed of simulated and commercially available LEDs, were optimized with a genetic algorithm to maximize the luminous efficacy of radiation and the colour quality as assessed by the memory colour quality metric developed by the authors. The trade-off of the colour quality as assessed by the memory colour metric and the luminous efficacy of radiation was investigated by calculating the Pareto optimal front using the NSGA-II genetic algorithm. Optimal peak wavelengths and spectral widths of the LEDs were derived, and over half of them were found to be close to Thornton's prime colours. The Pareto optimal fronts of real LED clusters were always found to be smaller than those of the simulated clusters. The effect of binning on designing a real LED cluster was investigated and was found to be quite large. Finally, a real LED cluster of commercially available AlGaInP, InGaN and phosphor white LEDs was optimized to obtain a higher score on memory colour quality scale than its corresponding CIE reference illuminant.

Recent advances in integrated multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Walsh, Joanne L.; Pritchard, Jocelyn I.

1992-01-01

A joint activity involving NASA and Army researchers at NASA LaRC to develop optimization procedures to improve the rotor blade design process by integrating appropriate disciplines and accounting for all of the important interactions among the disciplines is described. The disciplines involved include rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. The work is focused on combining these five key disciplines in an optimization procedure capable of designing a rotor system to satisfy multidisciplinary design requirements. Fundamental to the plan is a three-phased approach. In phase 1, the disciplines of blade dynamics, blade aerodynamics, and blade structure are closely coupled while acoustics and airframe dynamics are decoupled and are accounted for as effective constraints on the design for the first three disciplines. In phase 2, acoustics is integrated with the first three disciplines. Finally, in phase 3, airframe dynamics is integrated with the other four disciplines. Representative results from work performed to date are described. These include optimal placement of tuning masses for reduction of blade vibratory shear forces, integrated aerodynamic/dynamic optimization, and integrated aerodynamic/dynamic/structural optimization. Examples of validating procedures are described.

Modelling and multi objective optimization of WEDM of commercially Monel super alloy using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Varun, Sajja; Reddy, Kalakada Bhargav Bal; Vardhan Reddy, R. R. Vishnu

2016-09-01

In this research work, development of a multi response optimization technique has been undertaken, using traditional desirability analysis and non-traditional particle swarm optimization techniques (for different customer's priorities) in wire electrical discharge machining (WEDM). Monel 400 has been selected as work material for experimentation. The effect of key process parameters such as pulse on time (TON), pulse off time (TOFF), peak current (IP), wire feed (WF) were on material removal rate (MRR) and surface roughness(SR) in WEDM operation were investigated. Further, the responses such as MRR and SR were modelled empirically through regression analysis. The developed models can be used by the machinists to predict the MRR and SR over a wide range of input parameters. The optimization of multiple responses has been done for satisfying the priorities of multiple users by using Taguchi-desirability function method and particle swarm optimization technique. The analysis of variance (ANOVA) is also applied to investigate the effect of influential parameters. Finally, the confirmation experiments were conducted for the optimal set of machining parameters, and the betterment has been proved.

Recent advances in multidisciplinary optimization of rotorcraft

NASA Technical Reports Server (NTRS)

Adelman, Howard M.; Walsh, Joanne L.; Pritchard, Jocelyn I.

1992-01-01

A joint activity involving NASA and Army researchers at NASA LaRC to develop optimization procedures to improve the rotor blade design process by integrating appropriate disciplines and accounting for all of the important interactions among the disciplines is described. The disciplines involved include rotor aerodynamics, rotor dynamics, rotor structures, airframe dynamics, and acoustics. The work is focused on combining these five key disciplines in an optimization procedure capable of designing a rotor system to satisfy multidisciplinary design requirements. Fundamental to the plan is a three-phased approach. In phase 1, the disciplines of blade dynamics, blade aerodynamics, and blade structure are closely coupled while acoustics and airframe dynamics are decoupled and are accounted for as effective constraints on the design for the first three disciplines. In phase 2, acoustics is integrated with the first three disciplines. Finally, in phase 3, airframe dynamics is integrated with the other four disciplines. Representative results from work performed to date are described. These include optimal placement of tuning masses for reduction of blade vibratory shear forces, integrated aerodynamic/dynamic optimization, and integrated aerodynamic/dynamic/structural optimization. Examples of validating procedures are described.

Optimization of freeform surfaces using intelligent deformation techniques for LED applications

NASA Astrophysics Data System (ADS)

Isaac, Annie Shalom; Neumann, Cornelius

2018-04-01

For many years, optical designers have great interests in designing efficient optimization algorithms to bring significant improvement to their initial design. However, the optimization is limited due to a large number of parameters present in the Non-uniform Rationaly b-Spline Surfaces. This limitation was overcome by an indirect technique known as optimization using freeform deformation (FFD). In this approach, the optical surface is placed inside a cubical grid. The vertices of this grid are modified, which deforms the underlying optical surface during the optimization. One of the challenges in this technique is the selection of appropriate vertices of the cubical grid. This is because these vertices share no relationship with the optical performance. When irrelevant vertices are selected, the computational complexity increases. Moreover, the surfaces created by them are not always feasible to manufacture, which is the same problem faced in any optimization technique while creating freeform surfaces. Therefore, this research addresses these two important issues and provides feasible design techniques to solve them. Finally, the proposed techniques are validated using two different illumination examples: street lighting lens and stop lamp for automobiles.

Optimal design of a magnetorheological damper used in smart prosthetic knees

NASA Astrophysics Data System (ADS)

Gao, Fei; Liu, Yan-Nan; Liao, Wei-Hsin

2017-03-01

In this paper, a magnetorheological (MR) damper is optimally designed for use in smart prosthetic knees. The objective of optimization is to minimize the total energy consumption during one gait cycle and weight of the MR damper. Firstly, a smart prosthetic knee employing a DC motor, MR damper and springs is developed based on the kinetics characteristics of human knee during walking. Then the function of the MR damper is analyzed. In the initial stance phase and swing phase, the MR damper is powered off (off-state). While during the late stance phase, the MR damper is powered on to work as a clutch (on-state). Based on the MR damper model as well as the prosthetic knee model, the instantaneous energy consumption of the MR damper is derived in the two working states. Then by integrating in one gait cycle, the total energy consumption is obtained. Particle swarm optimization algorithm is used to optimize the geometric dimensions of MR damper. Finally, a prototype of the optimized MR damper is fabricated and tested with comparison to simulation.

Distribution path robust optimization of electric vehicle with multiple distribution centers

PubMed Central

Hao, Wei; He, Ruichun; Jia, Xiaoyan; Pan, Fuquan; Fan, Jing; Xiong, Ruiqi

2018-01-01

To identify electrical vehicle (EV) distribution paths with high robustness, insensitivity to uncertainty factors, and detailed road-by-road schemes, optimization of the distribution path problem of EV with multiple distribution centers and considering the charging facilities is necessary. With the minimum transport time as the goal, a robust optimization model of EV distribution path with adjustable robustness is established based on Bertsimas’ theory of robust discrete optimization. An enhanced three-segment genetic algorithm is also developed to solve the model, such that the optimal distribution scheme initially contains all road-by-road path data using the three-segment mixed coding and decoding method. During genetic manipulation, different interlacing and mutation operations are carried out on different chromosomes, while, during population evolution, the infeasible solution is naturally avoided. A part of the road network of Xifeng District in Qingyang City is taken as an example to test the model and the algorithm in this study, and the concrete transportation paths are utilized in the final distribution scheme. Therefore, more robust EV distribution paths with multiple distribution centers can be obtained using the robust optimization model. PMID:29518169

Data-Driven Zero-Sum Neuro-Optimal Control for a Class of Continuous-Time Unknown Nonlinear Systems With Disturbance Using ADP.

PubMed

Wei, Qinglai; Song, Ruizhuo; Yan, Pengfei

2016-02-01

This paper is concerned with a new data-driven zero-sum neuro-optimal control problem for continuous-time unknown nonlinear systems with disturbance. According to the input-output data of the nonlinear system, an effective recurrent neural network is introduced to reconstruct the dynamics of the nonlinear system. Considering the system disturbance as a control input, a two-player zero-sum optimal control problem is established. Adaptive dynamic programming (ADP) is developed to obtain the optimal control under the worst case of the disturbance. Three single-layer neural networks, including one critic and two action networks, are employed to approximate the performance index function, the optimal control law, and the disturbance, respectively, for facilitating the implementation of the ADP method. Convergence properties of the ADP method are developed to show that the system state will converge to a finite neighborhood of the equilibrium. The weight matrices of the critic and the two action networks are also convergent to finite neighborhoods of their optimal ones. Finally, the simulation results will show the effectiveness of the developed data-driven ADP methods.

An optimized treatment for algorithmic differentiation of an important glaciological fixed-point problem

DOE PAGES

Goldberg, Daniel N.; Narayanan, Sri Hari Krishna; Hascoet, Laurent; ...

2016-05-20

We apply an optimized method to the adjoint generation of a time-evolving land ice model through algorithmic differentiation (AD). The optimization involves a special treatment of the fixed-point iteration required to solve the nonlinear stress balance, which differs from a straightforward application of AD software, and leads to smaller memory requirements and in some cases shorter computation times of the adjoint. The optimization is done via implementation of the algorithm of Christianson (1994) for reverse accumulation of fixed-point problems, with the AD tool OpenAD. For test problems, the optimized adjoint is shown to have far lower memory requirements, potentially enablingmore » larger problem sizes on memory-limited machines. In the case of the land ice model, implementation of the algorithm allows further optimization by having the adjoint model solve a sequence of linear systems with identical (as opposed to varying) matrices, greatly improving performance. Finally, the methods introduced here will be of value to other efforts applying AD tools to ice models, particularly ones which solve a hybrid shallow ice/shallow shelf approximation to the Stokes equations.« less

Optimal Reference Strain Structure for Studying Dynamic Responses of Flexible Rockets

NASA Technical Reports Server (NTRS)

Tsushima, Natsuki; Su, Weihua; Wolf, Michael G.; Griffin, Edwin D.; Dumoulin, Marie P.

2017-01-01

In the proposed paper, the optimal design of reference strain structures (RSS) will be performed targeting for the accurate observation of the dynamic bending and torsion deformation of a flexible rocket. It will provide the detailed description of the finite-element (FE) model of a notional flexible rocket created in MSC.Patran. The RSS will be attached longitudinally along the side of the rocket and to track the deformation of the thin-walled structure under external loads. An integrated surrogate-based multi-objective optimization approach will be developed to find the optimal design of the RSS using the FE model. The Kriging method will be used to construct the surrogate model. For the data sampling and the performance evaluation, static/transient analyses will be performed with MSC.Natran/Patran. The multi-objective optimization will be solved with NSGA-II to minimize the difference between the strains of the launch vehicle and RSS. Finally, the performance of the optimal RSS will be evaluated by checking its strain-tracking capability in different numerical simulations of the flexible rocket.

Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

PubMed

Levesque, Ives R; Sled, John G; Pike, G Bruce

2011-09-01

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

NASA Astrophysics Data System (ADS)

Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

2017-10-01

Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

Impacts of Stress, Self-Efficacy, and Optimism on Suicide Ideation among Rehabilitation Patients with Acute Pesticide Poisoning

PubMed Central

Feng, Jun; Li, Shusheng; Chen, Huawen

2015-01-01

Background The high incidence of pesticide ingestion as a means to commit suicide is a critical public health problem. An important predictor of suicidal behavior is suicide ideation, which is related to stress. However, studies on how to defend against stress-induced suicidal thoughts are limited. Objective This study explores the impact of stress on suicidal ideation by investigating the mediating effect of self-efficacy and dispositional optimism. Methods Direct and indirect (via self-efficacy and dispositional optimism) effects of stress on suicidal ideation were investigated among 296 patients with acute pesticide poisoning from four general hospitals. For this purpose, structural equation modeling (SEM) and bootstrap method were used. Results Results obtained using SEM and bootstrap method show that stress has a direct effect on suicide ideation. Furthermore, self-efficacy and dispositional optimism partially weakened the relationship between stress and suicidal ideation. Conclusion The final model shows a significant relationship between stress and suicidal ideation through self-efficacy or dispositional optimism. The findings extended prior studies and provide enlightenment on how self-efficacy and optimism prevents stress-induced suicidal thoughts. PMID:25679994

Impacts of stress, self-efficacy, and optimism on suicide ideation among rehabilitation patients with acute pesticide poisoning.

PubMed

Feng, Jun; Li, Shusheng; Chen, Huawen

2015-01-01

The high incidence of pesticide ingestion as a means to commit suicide is a critical public health problem. An important predictor of suicidal behavior is suicide ideation, which is related to stress. However, studies on how to defend against stress-induced suicidal thoughts are limited. This study explores the impact of stress on suicidal ideation by investigating the mediating effect of self-efficacy and dispositional optimism. Direct and indirect (via self-efficacy and dispositional optimism) effects of stress on suicidal ideation were investigated among 296 patients with acute pesticide poisoning from four general hospitals. For this purpose, structural equation modeling (SEM) and bootstrap method were used. Results obtained using SEM and bootstrap method show that stress has a direct effect on suicide ideation. Furthermore, self-efficacy and dispositional optimism partially weakened the relationship between stress and suicidal ideation. The final model shows a significant relationship between stress and suicidal ideation through self-efficacy or dispositional optimism. The findings extended prior studies and provide enlightenment on how self-efficacy and optimism prevents stress-induced suicidal thoughts.

Ortho Image and DTM Generation with Intelligent Methods

NASA Astrophysics Data System (ADS)

Bagheri, H.; Sadeghian, S.

2013-10-01

Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

NASA Astrophysics Data System (ADS)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon

NASA Astrophysics Data System (ADS)

Wu, Jiang; Liao, Fucheng; Tomizuka, Masayoshi

2017-01-01

This paper discusses the design of the optimal preview controller for a linear continuous-time stochastic control system in finite-time horizon, using the method of augmented error system. First, an assistant system is introduced for state shifting. Then, in order to overcome the difficulty of the state equation of the stochastic control system being unable to be differentiated because of Brownian motion, the integrator is introduced. Thus, the augmented error system which contains the integrator vector, control input, reference signal, error vector and state of the system is reconstructed. This leads to the tracking problem of the optimal preview control of the linear stochastic control system being transformed into the optimal output tracking problem of the augmented error system. With the method of dynamic programming in the theory of stochastic control, the optimal controller with previewable signals of the augmented error system being equal to the controller of the original system is obtained. Finally, numerical simulations show the effectiveness of the controller.

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Understanding and mimicking the dual optimality of the fly ear

NASA Astrophysics Data System (ADS)

Liu, Haijun; Currano, Luke; Gee, Danny; Helms, Tristan; Yu, Miao

2013-08-01

The fly Ormia ochracea has the remarkable ability, given an eardrum separation of only 520 μm, to pinpoint the 5 kHz chirp of its cricket host. Previous research showed that the two eardrums are mechanically coupled, which amplifies the directional cues. We have now performed a mechanics and optimization analysis which reveals that the right coupling strength is key: it results in simultaneously optimized directional sensitivity and directional cue linearity at 5 kHz. We next demonstrated that this dual optimality is replicable in a synthetic device and can be tailored for a desired frequency. Finally, we demonstrated a miniature sensor endowed with this dual-optimality at 8 kHz with unparalleled sound localization. This work provides a quantitative and mechanistic explanation for the fly's sound-localization ability from a new perspective, and it provides a framework for the development of fly-ear inspired sensors to overcoming a previously-insurmountable size constraint in engineered sound-localization systems.

Power Grid Construction Project Portfolio Optimization Based on Bi-level programming model

NASA Astrophysics Data System (ADS)

Zhao, Erdong; Li, Shangqi

2017-08-01

As the main body of power grid operation, county-level power supply enterprises undertake an important emission to guarantee the security of power grid operation and safeguard social power using order. The optimization of grid construction projects has been a key issue of power supply capacity and service level of grid enterprises. According to the actual situation of power grid construction project optimization of county-level power enterprises, on the basis of qualitative analysis of the projects, this paper builds a Bi-level programming model based on quantitative analysis. The upper layer of the model is the target restriction of the optimal portfolio; the lower layer of the model is enterprises’ financial restrictions on the size of the enterprise project portfolio. Finally, using a real example to illustrate operation proceeding and the optimization result of the model. Through qualitative analysis and quantitative analysis, the bi-level programming model improves the accuracy and normative standardization of power grid enterprises projects.

A self optimizing synthetic organic reactor system using real-time in-line NMR spectroscopy† †Electronic supplementary information (ESI) available: Details about the methodology, LabView scripts, experimental set-ups, additional spectra and self-optimization can be found in the SI. See DOI: 10.1039/c4sc03075c Click here for additional data file.

PubMed Central

Sans, Victor; Porwol, Luzian; Dragone, Vincenza

2015-01-01

A configurable platform for synthetic chemistry incorporating an in-line benchtop NMR that is capable of monitoring and controlling organic reactions in real-time is presented. The platform is controlled via a modular LabView software control system for the hardware, NMR, data analysis and feedback optimization. Using this platform we report the real-time advanced structural characterization of reaction mixtures, including 19F, 13C, DEPT, 2D NMR spectroscopy (COSY, HSQC and 19F-COSY) for the first time. Finally, the potential of this technique is demonstrated through the optimization of a catalytic organic reaction in real-time, showing its applicability to self-optimizing systems using criteria such as stereoselectivity, multi-nuclear measurements or 2D correlations. PMID:29560211

Interior and exterior ballistics coupled optimization with constraints of attitude control and mechanical-thermal conditions

NASA Astrophysics Data System (ADS)

Liang, Xin-xin; Zhang, Nai-min; Zhang, Yan

2016-07-01

For solid launch vehicle performance promotion, a modeling method of interior and exterior ballistics associated optimization with constraints of attitude control and mechanical-thermal condition is proposed. Firstly, the interior and external ballistic models of the solid launch vehicle are established, and the attitude control model of the high wind area and the stage of the separation is presented, and the load calculation model of the drag reduction device is presented, and thermal condition calculation model of flight is presented. Secondly, the optimization model is established to optimize the range, which has internal and external ballistic design parameters as variables selected by sensitivity analysis, and has attitude control and mechanical-thermal conditions as constraints. Finally, the method is applied to the optimal design of a three stage solid launch vehicle simulation with differential evolution algorithm. Simulation results are shown that range capability is improved by 10.8%, and both attitude control and mechanical-thermal conditions are satisfied.

Practical automated glass selection and the design of apochromats with large field of view.

PubMed

Siew, Ronian

2016-11-10

This paper presents an automated approach to the selection of optical glasses for the design of an apochromatic lens with large field of view, based on a design originally provided by Yang et al. [Appl. Opt.55, 5977 (2016)APOPAI0003-693510.1364/AO.55.005977]. Following from this reference's preliminary optimized structure, it is shown that the effort of glass selection is significantly reduced by using the global optimization feature in the Zemax optical design program. The glass selection process is very fast, complete within minutes, and the key lies in automating the substitution of glasses found from the global search without the need to simultaneously optimize any other lens parameter during the glass search. The result is an alternate optimized version of the lens from the above reference possessing zero axial secondary color within the visible spectrum and a large field of view. Supplementary material is provided in the form of Zemax and text files, before and after final optimization.

Optimal estimation of recurrence structures from time series

NASA Astrophysics Data System (ADS)

beim Graben, Peter; Sellers, Kristin K.; Fröhlich, Flavio; Hutt, Axel

2016-05-01

Recurrent temporal dynamics is a phenomenon observed frequently in high-dimensional complex systems and its detection is a challenging task. Recurrence quantification analysis utilizing recurrence plots may extract such dynamics, however it still encounters an unsolved pertinent problem: the optimal selection of distance thresholds for estimating the recurrence structure of dynamical systems. The present work proposes a stochastic Markov model for the recurrent dynamics that allows for the analytical derivation of a criterion for the optimal distance threshold. The goodness of fit is assessed by a utility function which assumes a local maximum for that threshold reflecting the optimal estimate of the system's recurrence structure. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. The final application to neurophysiological time series obtained from anesthetized animals illustrates the method and reveals novel dynamic features of the underlying system. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.

Multimode resource-constrained multiple project scheduling problem under fuzzy random environment and its application to a large scale hydropower construction project.

PubMed

Xu, Jiuping; Feng, Cuiying

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method.

Optimization of transfer trajectories to the Apophis asteroid for spacecraft with high and low thrust

NASA Astrophysics Data System (ADS)

Ivashkin, V. V.; Krylov, I. V.

2014-03-01

The problem of optimization of a spacecraft transfer to the Apophis asteroid is investigated. The scheme of transfer under analysis includes a geocentric stage of boosting the spacecraft with high thrust, a heliocentric stage of control by a low thrust engine, and a stage of deceleration with injection to an orbit of the asteroid's satellite. In doing this, the problem of optimal control is solved for cases of ideal and piecewise-constant low thrust, and the optimal magnitude and direction of spacecraft's hyperbolic velocity "at infinity" during departure from the Earth are determined. The spacecraft trajectories are found based on a specially developed comprehensive method of optimization. This method combines the method of dynamic programming at the first stage of analysis and the Pontryagin maximum principle at the concluding stage, together with the parameter continuation method. The estimates are obtained for the spacecraft's final mass and for the payload mass that can be delivered to the asteroid using the Soyuz-Fregat carrier launcher.

Hierarchical Winner-Take-All Particle Swarm Optimization Social Network for Neural Model Fitting

PubMed Central

Coventry, Brandon S.; Parthasarathy, Aravindakshan; Sommer, Alexandra L.; Bartlett, Edward L.

2016-01-01

Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models. PMID:27726048

Optimal replenishment and credit policy in supply chain inventory model under two levels of trade credit with time- and credit-sensitive demand involving default risk

NASA Astrophysics Data System (ADS)

Mahata, Puspita; Mahata, Gour Chandra; Kumar De, Sujit

2018-03-01

Traditional supply chain inventory modes with trade credit usually only assumed that the up-stream suppliers offered the down-stream retailers a fixed credit period. However, in practice the retailers will also provide a credit period to customers to promote the market competition. In this paper, we formulate an optimal supply chain inventory model under two levels of trade credit policy with default risk consideration. Here, the demand is assumed to be credit-sensitive and increasing function of time. The major objective is to determine the retailer's optimal credit period and cycle time such that the total profit per unit time is maximized. The existence and uniqueness of the optimal solution to the presented model are examined, and an easy method is also shown to find the optimal inventory policies of the considered problem. Finally, numerical examples and sensitive analysis are presented to illustrate the developed model and to provide some managerial insights.

Decentralized stabilization for a class of continuous-time nonlinear interconnected systems using online learning optimal control approach.

PubMed

Liu, Derong; Wang, Ding; Li, Hongliang

2014-02-01

In this paper, using a neural-network-based online learning optimal control approach, a novel decentralized control strategy is developed to stabilize a class of continuous-time nonlinear interconnected large-scale systems. First, optimal controllers of the isolated subsystems are designed with cost functions reflecting the bounds of interconnections. Then, it is proven that the decentralized control strategy of the overall system can be established by adding appropriate feedback gains to the optimal control policies of the isolated subsystems. Next, an online policy iteration algorithm is presented to solve the Hamilton-Jacobi-Bellman equations related to the optimal control problem. Through constructing a set of critic neural networks, the cost functions can be obtained approximately, followed by the control policies. Furthermore, the dynamics of the estimation errors of the critic networks are verified to be uniformly and ultimately bounded. Finally, a simulation example is provided to illustrate the effectiveness of the present decentralized control scheme.

Adaptive critic designs for optimal control of uncertain nonlinear systems with unmatched interconnections.

PubMed

Yang, Xiong; He, Haibo

2018-05-26

In this paper, we develop a novel optimal control strategy for a class of uncertain nonlinear systems with unmatched interconnections. To begin with, we present a stabilizing feedback controller for the interconnected nonlinear systems by modifying an array of optimal control laws of auxiliary subsystems. We also prove that this feedback controller ensures a specified cost function to achieve optimality. Then, under the framework of adaptive critic designs, we use critic networks to solve the Hamilton-Jacobi-Bellman equations associated with auxiliary subsystem optimal control laws. The critic network weights are tuned through the gradient descent method combined with an additional stabilizing term. By using the newly established weight tuning rules, we no longer need the initial admissible control condition. In addition, we demonstrate that all signals in the closed-loop auxiliary subsystems are stable in the sense of uniform ultimate boundedness by using classic Lyapunov techniques. Finally, we provide an interconnected nonlinear plant to validate the present control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Use and optimization of a dual-flowrate loading strategy to maximize throughput in protein-a affinity chromatography.

PubMed

Ghose, Sanchayita; Nagrath, Deepak; Hubbard, Brian; Brooks, Clayton; Cramer, Steven M

2004-01-01

The effect of an alternate strategy employing two different flowrates during loading was explored as a means of increasing system productivity in Protein-A chromatography. The effect of such a loading strategy was evaluated using a chromatographic model that was able to accurately predict experimental breakthrough curves for this Protein-A system. A gradient-based optimization routine is carried out to establish the optimal loading conditions (initial and final flowrates and switching time). The two-step loading strategy (using a higher flowrate during the initial stages followed by a lower flowrate) was evaluated for an Fc-fusion protein and was found to result in significant improvements in process throughput. In an extension of this optimization routine, dynamic loading capacity and productivity were simultaneously optimized using a weighted objective function, and this result was compared to that obtained with the single flowrate. Again, the dual-flowrate strategy was found to be superior.

Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

NASA Technical Reports Server (NTRS)

Cheung, Kar-Ming; Lee, Charles H.

2012-01-01

We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

Multimode Resource-Constrained Multiple Project Scheduling Problem under Fuzzy Random Environment and Its Application to a Large Scale Hydropower Construction Project

PubMed Central

Xu, Jiuping

2014-01-01

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform the fuzzy random parameters into fuzzy variables that are subsequently defuzzified using an expected value operator with an optimistic-pessimistic index. Then a combinatorial-priority-based hybrid particle swarm optimization algorithm is developed to solve the proposed model, where the combinatorial particle swarm optimization and priority-based particle swarm optimization are designed to assign modes to activities and to schedule activities, respectively. Finally, the results and analysis of a practical example at a large scale hydropower construction project are presented to demonstrate the practicality and efficiency of the proposed model and optimization method. PMID:24550708

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

An Optimization Framework for Driver Feedback Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Malikopoulos, Andreas; Aguilar, Juan P.

2013-01-01

Modern vehicles have sophisticated electronic control units that can control engine operation with discretion to balance fuel economy, emissions, and power. These control units are designed for specific driving conditions (e.g., different speed profiles for highway and city driving). However, individual driving styles are different and rarely match the specific driving conditions for which the units were designed. In the research reported here, we investigate driving-style factors that have a major impact on fuel economy and construct an optimization framework to optimize individual driving styles with respect to these driving factors. In this context, we construct a set of polynomialmore » metamodels to reflect the responses produced in fuel economy by changing the driving factors. Then, we compare the optimized driving styles to the original driving styles and evaluate the effectiveness of the optimization framework. Finally, we use this proposed framework to develop a real-time feedback system, including visual instructions, to enable drivers to alter their driving styles in response to actual driving conditions to improve fuel efficiency.« less

U35: Legacy Engine Final Report

DOT National Transportation Integrated Search

2012-07-01

The Legacy engine is a new core technology that can be used with existing infrastructure providing for near term benefits while minimizing costs. Also, as a new technology, it will be optimized for many years to come providing the opportunity for con...

Optimal charging scheduler for electric vehicles on the Florida turnpike : final research project report.

DOT National Transportation Integrated Search

2017-06-01

This project developed a methodology to simulate and analyze roadway traffic patterns : and expected penetration and timing of electric vehicles (EVs) with application directed : toward the requirements for electric vehicle supply equipment (EVSE) si...

Surveying Florida MPO readiness to incorporate innovative technologies into long range transportation plans : draft final report.

DOT National Transportation Integrated Search

2016-08-01

There is optimism that Automated Vehicles (AVs) can improve the safety of the transportation system, : reduce congestion, increase reliability, offer improved mobility solutions to all segments of the population : including the transportation-disadva...

Adaptive Environment for Supercompiling with Optimized Parallelism (AESOP)

DTIC Science & Technology

2011-09-01

DATES COVERED (From - To) September 2011 Final 09 March 2009 – 31 July 2011 4 . TITLE AND SUBTITLE ADAPTIVE ENVIRONMENT FOR SUPERCOMPILING WITH... 4 2.1 System characterization loop...Integration Points for AESOP .......................................................................................10 4 . LLVM and the AESOP Compiler

Improving striping operations through system optimization - phase 2 : final report.

DOT National Transportation Integrated Search

2016-07-01

Striping operations generate a significant workload for MoDOT maintenance operations. The requirement for each striping crew : to replenish its stock of paint and other consumable items from a bulk storage facility, along with the necessity to make s...

Addendum to final report, Optimizing traffic counting procedures.

DOT National Transportation Integrated Search

1987-01-01

The methodology described in entry 55-14 was used with 1980 data for 16 continuous count stations to determine periods that were stable throughout the year for different short counts. It was found that stable periods for short counts occurred mainly ...

Formation of optimal construction fleet composition

NASA Astrophysics Data System (ADS)

Tuskaeva, Zalina

2017-10-01

Machinery supply and its rational use in construction processes considerably determine the final product of construction organizations. Therefore, the problem of defining the type size composition of the construction fleet as one of the lowest material-intensive productions, is of a particular importance.

Optimization of salt fog conditions for organic zinc paints : final report.

DOT National Transportation Integrated Search

1981-10-01

Although Louisiana has been testing and using organic zinc coatings since 1963, premature failures have occurred on bridges within the state recently. These failures were not predicted by accelerated testing which included salt fog exposure. the resu...

ECONOMIC-ENGINEERING OPTIMIZATION FOR CALIFORNIA WATER MANAGEMENT. (R825285)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563

Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.

Parametric modeling and stagger angle optimization of an axial flow fan

NASA Astrophysics Data System (ADS)

Li, M. X.; Zhang, C. H.; Liu, Y.; Y Zheng, S.

2013-12-01

Axial flow fans are widely used in every field of social production. Improving their efficiency is a sustained and urgent demand of domestic industry. The optimization of stagger angle is an important method to improve fan performance. Parametric modeling and calculation process automation are realized in this paper to improve optimization efficiency. Geometric modeling and mesh division are parameterized based on GAMBIT. Parameter setting and flow field calculation are completed in the batch mode of FLUENT. A control program is developed in Visual C++ to dominate the data exchange of mentioned software. It also extracts calculation results for optimization algorithm module (provided by Matlab) to generate directive optimization control parameters, which as feedback are transferred upwards to modeling module. The center line of the blade airfoil, based on CLARK y profile, is constructed by non-constant circulation and triangle discharge method. Stagger angles of six airfoil sections are optimized, to reduce the influence of inlet shock loss as well as gas leak in blade tip clearance and hub resistance at blade root. Finally an optimal solution is obtained, which meets the total pressure requirement under given conditions and improves total pressure efficiency by about 6%.

Research on Optimal Observation Scale for Damaged Buildings after Earthquake Based on Optimal Feature Space

NASA Astrophysics Data System (ADS)

Chen, J.; Chen, W.; Dou, A.; Li, W.; Sun, Y.

2018-04-01

A new information extraction method of damaged buildings rooted in optimal feature space is put forward on the basis of the traditional object-oriented method. In this new method, ESP (estimate of scale parameter) tool is used to optimize the segmentation of image. Then the distance matrix and minimum separation distance of all kinds of surface features are calculated through sample selection to find the optimal feature space, which is finally applied to extract the image of damaged buildings after earthquake. The overall extraction accuracy reaches 83.1 %, the kappa coefficient 0.813. The new information extraction method greatly improves the extraction accuracy and efficiency, compared with the traditional object-oriented method, and owns a good promotional value in the information extraction of damaged buildings. In addition, the new method can be used for the information extraction of different-resolution images of damaged buildings after earthquake, then to seek the optimal observation scale of damaged buildings through accuracy evaluation. It is supposed that the optimal observation scale of damaged buildings is between 1 m and 1.2 m, which provides a reference for future information extraction of damaged buildings.

The effect of spectral filters on visual search in stroke patients.

PubMed

Beasley, Ian G; Davies, Leon N

2013-01-01

Visual search impairment can occur following stroke. The utility of optimal spectral filters on visual search in stroke patients has not been considered to date. The present study measured the effect of optimal spectral filters on visual search response time and accuracy, using a task requiring serial processing. A stroke and control cohort undertook the task three times: (i) using an optimally selected spectral filter; (ii) the subjects were randomly assigned to two groups with group 1 using an optimal filter for two weeks, whereas group 2 used a grey filter for two weeks; (iii) the groups were crossed over with group 1 using a grey filter for a further two weeks and group 2 given an optimal filter, before undertaking the task for the final time. Initial use of an optimal spectral filter improved visual search response time but not error scores in the stroke cohort. Prolonged use of neither an optimal nor a grey filter improved response time or reduced error scores. In fact, response times increased with the filter, regardless of its type, for stroke and control subjects; this outcome may be due to contrast reduction or a reflection of task design, given that significant practice effects were noted.

Proper Orthogonal Decomposition in Optimal Control of Fluids

NASA Technical Reports Server (NTRS)

Ravindran, S. S.

1999-01-01

In this article, we present a reduced order modeling approach suitable for active control of fluid dynamical systems based on proper orthogonal decomposition (POD). The rationale behind the reduced order modeling is that numerical simulation of Navier-Stokes equations is still too costly for the purpose of optimization and control of unsteady flows. We examine the possibility of obtaining reduced order models that reduce computational complexity associated with the Navier-Stokes equations while capturing the essential dynamics by using the POD. The POD allows extraction of certain optimal set of basis functions, perhaps few, from a computational or experimental data-base through an eigenvalue analysis. The solution is then obtained as a linear combination of these optimal set of basis functions by means of Galerkin projection. This makes it attractive for optimal control and estimation of systems governed by partial differential equations. We here use it in active control of fluid flows governed by the Navier-Stokes equations. We show that the resulting reduced order model can be very efficient for the computations of optimization and control problems in unsteady flows. Finally, implementational issues and numerical experiments are presented for simulations and optimal control of fluid flow through channels.

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT

PubMed Central

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment. PMID:29181020

Optimal lattice-structured materials

DOE PAGES

Messner, Mark C.

2016-07-09

This paper describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describingmore » the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.« less

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

PubMed

Nie, Xiaohua; Wang, Wei; Nie, Haoyao

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

A System-Oriented Approach for the Optimal Control of Process Chains under Stochastic Influences

NASA Astrophysics Data System (ADS)

Senn, Melanie; Schäfer, Julian; Pollak, Jürgen; Link, Norbert

2011-09-01

Process chains in manufacturing consist of multiple connected processes in terms of dynamic systems. The properties of a product passing through such a process chain are influenced by the transformation of each single process. There exist various methods for the control of individual processes, such as classical state controllers from cybernetics or function mapping approaches realized by statistical learning. These controllers ensure that a desired state is obtained at process end despite of variations in the input and disturbances. The interactions between the single processes are thereby neglected, but play an important role in the optimization of the entire process chain. We divide the overall optimization into two phases: (1) the solution of the optimization problem by Dynamic Programming to find the optimal control variable values for each process for any encountered end state of its predecessor and (2) the application of the optimal control variables at runtime for the detected initial process state. The optimization problem is solved by selecting adequate control variables for each process in the chain backwards based on predefined quality requirements for the final product. For the demonstration of the proposed concept, we have chosen a process chain from sheet metal manufacturing with simplified transformation functions.

Aerodynamic design optimization using sensitivity analysis and computational fluid dynamics

NASA Technical Reports Server (NTRS)

Baysal, Oktay; Eleshaky, Mohamed E.

1991-01-01

A new and efficient method is presented for aerodynamic design optimization, which is based on a computational fluid dynamics (CFD)-sensitivity analysis algorithm. The method is applied to design a scramjet-afterbody configuration for an optimized axial thrust. The Euler equations are solved for the inviscid analysis of the flow, which in turn provides the objective function and the constraints. The CFD analysis is then coupled with the optimization procedure that uses a constrained minimization method. The sensitivity coefficients, i.e. gradients of the objective function and the constraints, needed for the optimization are obtained using a quasi-analytical method rather than the traditional brute force method of finite difference approximations. During the one-dimensional search of the optimization procedure, an approximate flow analysis (predicted flow) based on a first-order Taylor series expansion is used to reduce the computational cost. Finally, the sensitivity of the optimum objective function to various design parameters, which are kept constant during the optimization, is computed to predict new optimum solutions. The flow analysis of the demonstrative example are compared with the experimental data. It is shown that the method is more efficient than the traditional methods.

The optimal design of stepped wedge trials with equal allocation to sequences and a comparison to other trial designs.

PubMed

Thompson, Jennifer A; Fielding, Katherine; Hargreaves, James; Copas, Andrew

2017-12-01

Background/Aims We sought to optimise the design of stepped wedge trials with an equal allocation of clusters to sequences and explored sample size comparisons with alternative trial designs. Methods We developed a new expression for the design effect for a stepped wedge trial, assuming that observations are equally correlated within clusters and an equal number of observations in each period between sequences switching to the intervention. We minimised the design effect with respect to (1) the fraction of observations before the first and after the final sequence switches (the periods with all clusters in the control or intervention condition, respectively) and (2) the number of sequences. We compared the design effect of this optimised stepped wedge trial to the design effects of a parallel cluster-randomised trial, a cluster-randomised trial with baseline observations, and a hybrid trial design (a mixture of cluster-randomised trial and stepped wedge trial) with the same total cluster size for all designs. Results We found that a stepped wedge trial with an equal allocation to sequences is optimised by obtaining all observations after the first sequence switches and before the final sequence switches to the intervention; this means that the first sequence remains in the control condition and the last sequence remains in the intervention condition for the duration of the trial. With this design, the optimal number of sequences is [Formula: see text], where [Formula: see text] is the cluster-mean correlation, [Formula: see text] is the intracluster correlation coefficient, and m is the total cluster size. The optimal number of sequences is small when the intracluster correlation coefficient and cluster size are small and large when the intracluster correlation coefficient or cluster size is large. A cluster-randomised trial remains more efficient than the optimised stepped wedge trial when the intracluster correlation coefficient or cluster size is small. A cluster-randomised trial with baseline observations always requires a larger sample size than the optimised stepped wedge trial. The hybrid design can always give an equally or more efficient design, but will be at most 5% more efficient. We provide a strategy for selecting a design if the optimal number of sequences is unfeasible. For a non-optimal number of sequences, the sample size may be reduced by allowing a proportion of observations before the first or after the final sequence has switched. Conclusion The standard stepped wedge trial is inefficient. To reduce sample sizes when a hybrid design is unfeasible, stepped wedge trial designs should have no observations before the first sequence switches or after the final sequence switches.

Optimization and experimental validation of a thermal cycle that maximizes entropy coefficient fisher identifiability for lithium iron phosphate cells

NASA Astrophysics Data System (ADS)

Mendoza, Sergio; Rothenberger, Michael; Hake, Alison; Fathy, Hosam

2016-03-01

This article presents a framework for optimizing the thermal cycle to estimate a battery cell's entropy coefficient at 20% state of charge (SOC). Our goal is to maximize Fisher identifiability: a measure of the accuracy with which a parameter can be estimated. Existing protocols in the literature for estimating entropy coefficients demand excessive laboratory time. Identifiability optimization makes it possible to achieve comparable accuracy levels in a fraction of the time. This article demonstrates this result for a set of lithium iron phosphate (LFP) cells. We conduct a 24-h experiment to obtain benchmark measurements of their entropy coefficients. We optimize a thermal cycle to maximize parameter identifiability for these cells. This optimization proceeds with respect to the coefficients of a Fourier discretization of this thermal cycle. Finally, we compare the estimated parameters using (i) the benchmark test, (ii) the optimized protocol, and (iii) a 15-h test from the literature (by Forgez et al.). The results are encouraging for two reasons. First, they confirm the simulation-based prediction that the optimized experiment can produce accurate parameter estimates in 2 h, compared to 15-24. Second, the optimized experiment also estimates a thermal time constant representing the effects of thermal capacitance and convection heat transfer.

Optimization of lightweight structure and supporting bipod flexure for a space mirror.

PubMed

Chen, Yi-Cheng; Huang, Bo-Kai; You, Zhen-Ting; Chan, Chia-Yen; Huang, Ting-Ming

2016-12-20

This article presents an optimization process for integrated optomechanical design. The proposed optimization process for integrated optomechanical design comprises computer-aided drafting, finite element analysis (FEA), optomechanical transfer codes, and an optimization solver. The FEA was conducted to determine mirror surface deformation; then, deformed surface nodal data were transferred into Zernike polynomials through MATLAB optomechanical transfer codes to calculate the resulting optical path difference (OPD) and optical aberrations. To achieve an optimum design, the optimization iterations of the FEA, optomechanical transfer codes, and optimization solver were automatically connected through a self-developed Tcl script. Two examples of optimization design were illustrated in this research, namely, an optimum lightweight design of a Zerodur primary mirror with an outer diameter of 566 mm that is used in a spaceborne telescope and an optimum bipod flexure design that supports the optimum lightweight primary mirror. Finally, optimum designs were successfully accomplished in both examples, achieving a minimum peak-to-valley (PV) value for the OPD of the deformed optical surface. The simulated optimization results showed that (1) the lightweight ratio of the primary mirror increased from 56% to 66%; and (2) the PV value of the mirror supported by optimum bipod flexures in the horizontal position effectively decreased from 228 to 61 nm.

Application of the advanced engineering environment for optimization energy consumption in designed vehicles

NASA Astrophysics Data System (ADS)

Monica, Z.; Sękala, A.; Gwiazda, A.; Banaś, W.

2016-08-01

Nowadays a key issue is to reduce the energy consumption of road vehicles. In particular solution one could find different strategies of energy optimization. The most popular but not sophisticated is so called eco-driving. In this strategy emphasized is particular behavior of drivers. In more sophisticated solution behavior of drivers is supported by control system measuring driving parameters and suggesting proper operation of the driver. The other strategy is concerned with application of different engineering solutions that aid optimization the process of energy consumption. Such systems take into consideration different parameters measured in real time and next take proper action according to procedures loaded to the control computer of a vehicle. The third strategy bases on optimization of the designed vehicle taking into account especially main sub-systems of a technical mean. In this approach the optimal level of energy consumption by a vehicle is obtained by synergetic results of individual optimization of particular constructional sub-systems of a vehicle. It is possible to distinguish three main sub-systems: the structural one the drive one and the control one. In the case of the structural sub-system optimization of the energy consumption level is related with the optimization or the weight parameter and optimization the aerodynamic parameter. The result is optimized body of a vehicle. Regarding the drive sub-system the optimization of the energy consumption level is related with the fuel or power consumption using the previously elaborated physical models. Finally the optimization of the control sub-system consists in determining optimal control parameters.

CSOLNP: Numerical Optimization Engine for Solving Non-linearly Constrained Problems.

PubMed

Zahery, Mahsa; Maes, Hermine H; Neale, Michael C

2017-08-01

We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.

Optimizing model: insemination, replacement, seasonal production, and cash flow.

PubMed

DeLorenzo, M A; Spreen, T H; Bryan, G R; Beede, D K; Van Arendonk, J A

1992-03-01

Dynamic programming to solve the Markov decision process problem of optimal insemination and replacement decisions was adapted to address large dairy herd management decision problems in the US. Expected net present values of cow states (151,200) were used to determine the optimal policy. States were specified by class of parity (n = 12), production level (n = 15), month of calving (n = 12), month of lactation (n = 16), and days open (n = 7). Methodology optimized decisions based on net present value of an individual cow and all replacements over a 20-yr decision horizon. Length of decision horizon was chosen to ensure that optimal policies were determined for an infinite planning horizon. Optimization took 286 s of central processing unit time. The final probability transition matrix was determined, in part, by the optimal policy. It was estimated iteratively to determine post-optimization steady state herd structure, milk production, replacement, feed inputs and costs, and resulting cash flow on a calendar month and annual basis if optimal policies were implemented. Implementation of the model included seasonal effects on lactation curve shapes, estrus detection rates, pregnancy rates, milk prices, replacement costs, cull prices, and genetic progress. Other inputs included calf values, values of dietary TDN and CP per kilogram, and discount rate. Stochastic elements included conception (and, thus, subsequent freshening), cow milk production level within herd, and survival. Validation of optimized solutions was by separate simulation model, which implemented policies on a simulated herd and also described herd dynamics during transition to optimized structure.

Exact and Optimal Quantum Mechanics/Molecular Mechanics Boundaries.

PubMed

Sun, Qiming; Chan, Garnet Kin-Lic

2014-09-09

Motivated by recent work in density matrix embedding theory, we define exact link orbitals that capture all quantum mechanical (QM) effects across arbitrary quantum mechanics/molecular mechanics (QM/MM) boundaries. Exact link orbitals are rigorously defined from the full QM solution, and their number is equal to the number of orbitals in the primary QM region. Truncating the exact set yields a smaller set of link orbitals optimal with respect to reproducing the primary region density matrix. We use the optimal link orbitals to obtain insight into the limits of QM/MM boundary treatments. We further analyze the popular general hybrid orbital (GHO) QM/MM boundary across a test suite of molecules. We find that GHOs are often good proxies for the most important optimal link orbital, although there is little detailed correlation between the detailed GHO composition and optimal link orbital valence weights. The optimal theory shows that anions and cations cannot be described by a single link orbital. However, expanding to include the second most important optimal link orbital in the boundary recovers an accurate description. The second optimal link orbital takes the chemically intuitive form of a donor or acceptor orbital for charge redistribution, suggesting that optimal link orbitals can be used as interpretative tools for electron transfer. We further find that two optimal link orbitals are also sufficient for boundaries that cut across double bonds. Finally, we suggest how to construct "approximately" optimal link orbitals for practical QM/MM calculations.

$L^1$ penalization of volumetric dose objectives in optimal control of PDEs

DOE PAGES

Barnard, Richard C.; Clason, Christian

2017-02-11

This work is concerned with a class of PDE-constrained optimization problems that are motivated by an application in radiotherapy treatment planning. Here the primary design objective is to minimize the volume where a functional of the state violates a prescribed level, but prescribing these levels in the form of pointwise state constraints leads to infeasible problems. We therefore propose an alternative approach based on L 1 penalization of the violation that is also applicable when state constraints are infeasible. We establish well-posedness of the corresponding optimal control problem, derive first-order optimality conditions, discuss convergence of minimizers as the penalty parametermore » tends to infinity, and present a semismooth Newton method for their efficient numerical solution. Finally, the performance of this method for a model problem is illustrated and contrasted with an alternative approach based on (regularized) state constraints.« less

Coordination of a supply chain with consumer return under vendor-managed consignment inventory and stochastic demand

NASA Astrophysics Data System (ADS)

Wu, Zhihui; Chen, Dongyan; Yu, Hui

2016-07-01

In this paper, the problem of the coordination policy is investigated for vendor-managed consignment inventory supply chain subject to consumer return. Here, the market demand is assumed to be affected by promotional effort and consumer return policy. The optimal consignment inventory and the optimal promotional effort level are proposed under the decentralized and centralized decisions. Based on the optimal decision conditions, the markdown allowance-promotional cost-sharing contract is investigated to coordinate the supply chain. Subsequently, the comparison between the two extreme policies shows that full-refund policy dominates the no-return policy when the returning cost and the positive effect of return policy are satisfied certain conditions. Finally, a numerical example is provided to illustrate the impacts of consumer return policy on the coordination contract and optimal profit as well as the effectiveness of the proposed supply chain decision.

Investigating the optimal passive and active vibration controls of adjacent buildings based on performance indices using genetic algorithms

NASA Astrophysics Data System (ADS)

Hadi, Muhammad N. S.; Uz, Mehmet E.

2015-02-01

This study proposes the optimal passive and active damper parameters for achieving the best results in seismic response mitigation of coupled buildings connected to each other by dampers. The optimization to minimize the H2 and H∞ norms in the performance indices is carried out by genetic algorithms (GAs). The final passive and active damper parameters are checked for adjacent buildings connected to each other under El Centro NS 1940 and Kobe NS 1995 excitations. Using real coded GA in H∞ norm, the optimal controller gain is obtained by different combinations of the measurement as the feedback for designing the control force between the buildings. The proposed method is more effective than other metaheuristic methods and more feasible, although the control force increased. The results in the active control system show that the response of adjacent buildings is reduced in an efficient manner.

Optimization of deflection of a big NEO through impact with a small one.

PubMed

Zhu, Kaijian; Huang, Weiping; Wang, Yuncai; Niu, Wei; Wu, Gongyou

2014-01-01

Using a small near-Earth object (NEO) to impact a larger and potentially threatening NEO has been suggested as an effective method to avert a collision with Earth. This paper develops a procedure for analysis of the technique for specific NEOs. First, an optimization method is used to select a proper small body from the database. Some principles of optimality are achieved with the optimization process. Then, the orbit of the small body is changed to guarantee that it flies toward and impacts the big threatening NEO. Kinetic impact by a spacecraft is chosen as the strategy of deflecting the small body. The efficiency of this method is compared with that of a direct kinetic impact to the big NEO by a spacecraft. Finally, a case study is performed for the deflection of the Apophis NEO, and the efficiency of the method is assessed.

Optimization of Deflection of a Big NEO through Impact with a Small One

PubMed Central

Zhu, Kaijian; Huang, Weiping; Wang, Yuncai; Niu, Wei; Wu, Gongyou

2014-01-01

Using a small near-Earth object (NEO) to impact a larger and potentially threatening NEO has been suggested as an effective method to avert a collision with Earth. This paper develops a procedure for analysis of the technique for specific NEOs. First, an optimization method is used to select a proper small body from the database. Some principles of optimality are achieved with the optimization process. Then, the orbit of the small body is changed to guarantee that it flies toward and impacts the big threatening NEO. Kinetic impact by a spacecraft is chosen as the strategy of deflecting the small body. The efficiency of this method is compared with that of a direct kinetic impact to the big NEO by a spacecraft. Finally, a case study is performed for the deflection of the Apophis NEO, and the efficiency of the method is assessed. PMID:25525627

SOM neural network fault diagnosis method of polymerization kettle equipment optimized by improved PSO algorithm.

PubMed

Wang, Jie-sheng; Li, Shu-xia; Gao, Jie

2014-01-01

For meeting the real-time fault diagnosis and the optimization monitoring requirements of the polymerization kettle in the polyvinyl chloride resin (PVC) production process, a fault diagnosis strategy based on the self-organizing map (SOM) neural network is proposed. Firstly, a mapping between the polymerization process data and the fault pattern is established by analyzing the production technology of polymerization kettle equipment. The particle swarm optimization (PSO) algorithm with a new dynamical adjustment method of inertial weights is adopted to optimize the structural parameters of SOM neural network. The fault pattern classification of the polymerization kettle equipment is to realize the nonlinear mapping from symptom set to fault set according to the given symptom set. Finally, the simulation experiments of fault diagnosis are conducted by combining with the industrial on-site historical data of the polymerization kettle and the simulation results show that the proposed PSO-SOM fault diagnosis strategy is effective.

The Study of Intelligent Vehicle Navigation Path Based on Behavior Coordination of Particle Swarm.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen

2016-01-01

In the behavior dynamics model, behavior competition leads to the shock problem of the intelligent vehicle navigation path, because of the simultaneous occurrence of the time-variant target behavior and obstacle avoidance behavior. Considering the safety and real-time of intelligent vehicle, the particle swarm optimization (PSO) algorithm is proposed to solve these problems for the optimization of weight coefficients of the heading angle and the path velocity. Firstly, according to the behavior dynamics model, the fitness function is defined concerning the intelligent vehicle driving characteristics, the distance between intelligent vehicle and obstacle, and distance of intelligent vehicle and target. Secondly, behavior coordination parameters that minimize the fitness function are obtained by particle swarm optimization algorithms. Finally, the simulation results show that the optimization method and its fitness function can improve the perturbations of the vehicle planning path and real-time and reliability.

Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations

NASA Technical Reports Server (NTRS)

Newman, Perry A.; Newman, James C., III; Barnwell, Richard W.; Taylor, Arthur C., III; Hou, Gene J.-W.

1998-01-01

This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.

Neural network-based optimal adaptive output feedback control of a helicopter UAV.

PubMed

Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

2013-07-01

Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

Technology forecasting for space communication. Task one report: Cost and weight tradeoff studies for EOS and TDRS

NASA Technical Reports Server (NTRS)

1974-01-01

Weight and cost optimized EOS communication links are determined for 2.25, 7.25, 14.5, 21, and 60 GHz systems and for a 10.6 micron homodyne detection laser system. EOS to ground links are examined for 556, 834, and 1112 km EOS orbits, with ground terminals at the Network Test and Tracking Facility and at Goldstone. Optimized 21 GHz and 10.6 micron links are also examined. For the EOS to Tracking and Data Relay Satellite to ground link, signal-to-noise ratios of the uplink and downlink are also optimized for minimum overall cost or spaceborne weight. Finally, the optimized 21 GHz EOS to ground link is determined for various precipitation rates. All system performance parameters and mission dependent constraints are presented, as are the system cost and weight functional dependencies. The features and capabilities of the computer program to perform the foregoing analyses are described.

Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

Image denoising in mixed Poisson-Gaussian noise.

PubMed

Luisier, Florian; Blu, Thierry; Unser, Michael

2011-03-01

We propose a general methodology (PURE-LET) to design and optimize a wide class of transform-domain thresholding algorithms for denoising images corrupted by mixed Poisson-Gaussian noise. We express the denoising process as a linear expansion of thresholds (LET) that we optimize by relying on a purely data-adaptive unbiased estimate of the mean-squared error (MSE), derived in a non-Bayesian framework (PURE: Poisson-Gaussian unbiased risk estimate). We provide a practical approximation of this theoretical MSE estimate for the tractable optimization of arbitrary transform-domain thresholding. We then propose a pointwise estimator for undecimated filterbank transforms, which consists of subband-adaptive thresholding functions with signal-dependent thresholds that are globally optimized in the image domain. We finally demonstrate the potential of the proposed approach through extensive comparisons with state-of-the-art techniques that are specifically tailored to the estimation of Poisson intensities. We also present denoising results obtained on real images of low-count fluorescence microscopy.

Replica analysis for the duality of the portfolio optimization problem

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2016-11-01

In the present paper, the primal-dual problem consisting of the investment risk minimization problem and the expected return maximization problem in the mean-variance model is discussed using replica analysis. As a natural extension of the investment risk minimization problem under only a budget constraint that we analyzed in a previous study, we herein consider a primal-dual problem in which the investment risk minimization problem with budget and expected return constraints is regarded as the primal problem, and the expected return maximization problem with budget and investment risk constraints is regarded as the dual problem. With respect to these optimal problems, we analyze a quenched disordered system involving both of these optimization problems using the approach developed in statistical mechanical informatics and confirm that both optimal portfolios can possess the primal-dual structure. Finally, the results of numerical simulations are shown to validate the effectiveness of the proposed method.

Transformational leadership in the local police in Spain: a leader-follower distance approach.

PubMed

Álvarez, Octavio; Lila, Marisol; Tomás, Inés; Castillo, Isabel

2014-01-01

Based on the transformational leadership theory (Bass, 1985), the aim of the present study was to analyze the differences in leadership styles according to the various leading ranks and the organizational follower-leader distance reported by a representative sample of 975 local police members (828 male and 147 female) from Valencian Community (Spain). Results showed differences by rank (p < .01), and by rank distance (p < .05). The general intendents showed the most optimal profile of leadership in all the variables examined (transformational-leadership behaviors, transactional-leadership behaviors, laissez-faire behaviors, satisfaction with the leader, extra effort by follower, and perceived leadership effectiveness). By contrast, the least optimal profiles were presented by intendents. Finally, the maximum distance (five ranks) generally yielded the most optimal profiles, whereas the 3-rank distance generally produced the least optimal profiles for all variables examined. Outcomes and practical implications for the workforce dimensioning are also discussed.

Imaging Tasks Scheduling for High-Altitude Airship in Emergency Condition Based on Energy-Aware Strategy

PubMed Central

Zhimeng, Li; Chuan, He; Dishan, Qiu; Jin, Liu; Manhao, Ma

2013-01-01

Aiming to the imaging tasks scheduling problem on high-altitude airship in emergency condition, the programming models are constructed by analyzing the main constraints, which take the maximum task benefit and the minimum energy consumption as two optimization objectives. Firstly, the hierarchy architecture is adopted to convert this scheduling problem into three subproblems, that is, the task ranking, value task detecting, and energy conservation optimization. Then, the algorithms are designed for the sub-problems, and the solving results are corresponding to feasible solution, efficient solution, and optimization solution of original problem, respectively. This paper makes detailed introduction to the energy-aware optimization strategy, which can rationally adjust airship's cruising speed based on the distribution of task's deadline, so as to decrease the total energy consumption caused by cruising activities. Finally, the application results and comparison analysis show that the proposed strategy and algorithm are effective and feasible. PMID:23864822