Reliability-Based Design Optimization of a Composite Airframe Component

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2009-01-01

A stochastic design optimization methodology (SDO) has been developed to design components of an airframe structure that can be made of metallic and composite materials. The design is obtained as a function of the risk level, or reliability, p. The design method treats uncertainties in load, strength, and material properties as distribution functions, which are defined with mean values and standard deviations. A design constraint or a failure mode is specified as a function of reliability p. Solution to stochastic optimization yields the weight of a structure as a function of reliability p. Optimum weight versus reliability p traced out an inverted-S-shaped graph. The center of the inverted-S graph corresponded to 50 percent (p = 0.5) probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponds to unity for reliability p (or p = 1). Weight can be reduced to a small value for the most failure-prone design with a reliability that approaches zero (p = 0). Reliability can be changed for different components of an airframe structure. For example, the landing gear can be designed for a very high reliability, whereas it can be reduced to a small extent for a raked wingtip. The SDO capability is obtained by combining three codes: (1) The MSC/Nastran code was the deterministic analysis tool, (2) The fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and (3) NASA Glenn Research Center s optimization testbed CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.

Structural design of high-performance capacitive accelerometers using parametric optimization with uncertainties

NASA Astrophysics Data System (ADS)

Teves, André da Costa; Lima, Cícero Ribeiro de; Passaro, Angelo; Silva, Emílio Carlos Nelli

2017-03-01

Electrostatic or capacitive accelerometers are among the highest volume microelectromechanical systems (MEMS) products nowadays. The design of such devices is a complex task, since they depend on many performance requirements, which are often conflicting. Therefore, optimization techniques are often used in the design stage of these MEMS devices. Because of problems with reliability, the technology of MEMS is not yet well established. Thus, in this work, size optimization is combined with the reliability-based design optimization (RBDO) method to improve the performance of accelerometers. To account for uncertainties in the dimensions and material properties of these devices, the first order reliability method is applied to calculate the probabilities involved in the RBDO formulation. Practical examples of bulk-type capacitive accelerometer designs are presented and discussed to evaluate the potential of the implemented RBDO solver.

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

Reliability based design including future tests and multiagent approaches

NASA Astrophysics Data System (ADS)

Villanueva, Diane

The initial stages of reliability-based design optimization involve the formulation of objective functions and constraints, and building a model to estimate the reliability of the design with quantified uncertainties. However, even experienced hands often overlook important objective functions and constraints that affect the design. In addition, uncertainty reduction measures, such as tests and redesign, are often not considered in reliability calculations during the initial stages. This research considers two areas that concern the design of engineering systems: 1) the trade-off of the effect of a test and post-test redesign on reliability and cost and 2) the search for multiple candidate designs as insurance against unforeseen faults in some designs. In this research, a methodology was developed to estimate the effect of a single future test and post-test redesign on reliability and cost. The methodology uses assumed distributions of computational and experimental errors with re-design rules to simulate alternative future test and redesign outcomes to form a probabilistic estimate of the reliability and cost for a given design. Further, it was explored how modeling a future test and redesign provides a company an opportunity to balance development costs versus performance by simultaneously designing the design and the post-test redesign rules during the initial design stage. The second area of this research considers the use of dynamic local surrogates, or surrogate-based agents, to locate multiple candidate designs. Surrogate-based global optimization algorithms often require search in multiple candidate regions of design space, expending most of the computation needed to define multiple alternate designs. Thus, focusing on solely locating the best design may be wasteful. We extended adaptive sampling surrogate techniques to locate multiple optima by building local surrogates in sub-regions of the design space to identify optima. The efficiency of this method was studied, and the method was compared to other surrogate-based optimization methods that aim to locate the global optimum using two two-dimensional test functions, a six-dimensional test function, and a five-dimensional engineering example.

Accounting for Proof Test Data in a Reliability Based Design Optimization Framework

NASA Technical Reports Server (NTRS)

Ventor, Gerharad; Scotti, Stephen J.

2012-01-01

This paper investigates the use of proof (or acceptance) test data during the reliability based design optimization of structural components. It is assumed that every component will be proof tested and that the component will only enter into service if it passes the proof test. The goal is to reduce the component weight, while maintaining high reliability, by exploiting the proof test results during the design process. The proposed procedure results in the simultaneous design of the structural component and the proof test itself and provides the designer with direct control over the probability of failing the proof test. The procedure is illustrated using two analytical example problems and the results indicate that significant weight savings are possible when exploiting the proof test results during the design process.

Reliability prediction of large fuel cell stack based on structure stress analysis

NASA Astrophysics Data System (ADS)

Liu, L. F.; Liu, B.; Wu, C. W.

2017-09-01

The aim of this paper is to improve the reliability of Proton Electrolyte Membrane Fuel Cell (PEMFC) stack by designing the clamping force and the thickness difference between the membrane electrode assembly (MEA) and the gasket. The stack reliability is directly determined by the component reliability, which is affected by the material property and contact stress. The component contact stress is a random variable because it is usually affected by many uncertain factors in the production and clamping process. We have investigated the influences of parameter variation coefficient on the probability distribution of contact stress using the equivalent stiffness model and the first-order second moment method. The optimal contact stress to make the component stay in the highest level reliability is obtained by the stress-strength interference model. To obtain the optimal contact stress between the contact components, the optimal thickness of the component and the stack clamping force are optimally designed. Finally, a detailed description is given how to design the MEA and gasket dimensions to obtain the highest stack reliability. This work can provide a valuable guidance in the design of stack structure for a high reliability of fuel cell stack.

Design for a Crane Metallic Structure Based on Imperialist Competitive Algorithm and Inverse Reliability Strategy

NASA Astrophysics Data System (ADS)

Fan, Xiao-Ning; Zhi, Bo

2017-07-01

Uncertainties in parameters such as materials, loading, and geometry are inevitable in designing metallic structures for cranes. When considering these uncertainty factors, reliability-based design optimization (RBDO) offers a more reasonable design approach. However, existing RBDO methods for crane metallic structures are prone to low convergence speed and high computational cost. A unilevel RBDO method, combining a discrete imperialist competitive algorithm with an inverse reliability strategy based on the performance measure approach, is developed. Application of the imperialist competitive algorithm at the optimization level significantly improves the convergence speed of this RBDO method. At the reliability analysis level, the inverse reliability strategy is used to determine the feasibility of each probabilistic constraint at each design point by calculating its α-percentile performance, thereby avoiding convergence failure, calculation error, and disproportionate computational effort encountered using conventional moment and simulation methods. Application of the RBDO method to an actual crane structure shows that the developed RBDO realizes a design with the best tradeoff between economy and safety together with about one-third of the convergence speed and the computational cost of the existing method. This paper provides a scientific and effective design approach for the design of metallic structures of cranes.

Deterministic and reliability based optimization of integrated thermal protection system composite panel using adaptive sampling techniques

NASA Astrophysics Data System (ADS)

Ravishankar, Bharani

Conventional space vehicles have thermal protection systems (TPS) that provide protection to an underlying structure that carries the flight loads. In an attempt to save weight, there is interest in an integrated TPS (ITPS) that combines the structural function and the TPS function. This has weight saving potential, but complicates the design of the ITPS that now has both thermal and structural failure modes. The main objectives of this dissertation was to optimally design the ITPS subjected to thermal and mechanical loads through deterministic and reliability based optimization. The optimization of the ITPS structure requires computationally expensive finite element analyses of 3D ITPS (solid) model. To reduce the computational expenses involved in the structural analysis, finite element based homogenization method was employed, homogenizing the 3D ITPS model to a 2D orthotropic plate. However it was found that homogenization was applicable only for panels that are much larger than the characteristic dimensions of the repeating unit cell in the ITPS panel. Hence a single unit cell was used for the optimization process to reduce the computational cost. Deterministic and probabilistic optimization of the ITPS panel required evaluation of failure constraints at various design points. This further demands computationally expensive finite element analyses which was replaced by efficient, low fidelity surrogate models. In an optimization process, it is important to represent the constraints accurately to find the optimum design. Instead of building global surrogate models using large number of designs, the computational resources were directed towards target regions near constraint boundaries for accurate representation of constraints using adaptive sampling strategies. Efficient Global Reliability Analyses (EGRA) facilitates sequentially sampling of design points around the region of interest in the design space. EGRA was applied to the response surface construction of the failure constraints in the deterministic and reliability based optimization of the ITPS panel. It was shown that using adaptive sampling, the number of designs required to find the optimum were reduced drastically, while improving the accuracy. System reliability of ITPS was estimated using Monte Carlo Simulation (MCS) based method. Separable Monte Carlo method was employed that allowed separable sampling of the random variables to predict the probability of failure accurately. The reliability analysis considered uncertainties in the geometry, material properties, loading conditions of the panel and error in finite element modeling. These uncertainties further increased the computational cost of MCS techniques which was also reduced by employing surrogate models. In order to estimate the error in the probability of failure estimate, bootstrapping method was applied. This research work thus demonstrates optimization of the ITPS composite panel with multiple failure modes and large number of uncertainties using adaptive sampling techniques.

A reliable algorithm for optimal control synthesis

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1992-01-01

In recent years, powerful design tools for linear time-invariant multivariable control systems have been developed based on direct parameter optimization. In this report, an algorithm for reliable optimal control synthesis using parameter optimization is presented. Specifically, a robust numerical algorithm is developed for the evaluation of the H(sup 2)-like cost functional and its gradients with respect to the controller design parameters. The method is specifically designed to handle defective degenerate systems and is based on the well-known Pade series approximation of the matrix exponential. Numerical test problems in control synthesis for simple mechanical systems and for a flexible structure with densely packed modes illustrate positively the reliability of this method when compared to a method based on diagonalization. Several types of cost functions have been considered: a cost function for robust control consisting of a linear combination of quadratic objectives for deterministic and random disturbances, and one representing an upper bound on the quadratic objective for worst case initial conditions. Finally, a framework for multivariable control synthesis has been developed combining the concept of closed-loop transfer recovery with numerical parameter optimization. The procedure enables designers to synthesize not only observer-based controllers but also controllers of arbitrary order and structure. Numerical design solutions rely heavily on the robust algorithm due to the high order of the synthesis model and the presence of near-overlapping modes. The design approach is successfully applied to the design of a high-bandwidth control system for a rotorcraft.

Multidisciplinary design optimization of vehicle instrument panel based on multi-objective genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Ping; Wu, Guangqiang

2013-03-01

Typical multidisciplinary design optimization(MDO) has gradually been proposed to balance performances of lightweight, noise, vibration and harshness(NVH) and safety for instrument panel(IP) structure in the automotive development. Nevertheless, plastic constitutive relation of Polypropylene(PP) under different strain rates, has not been taken into consideration in current reliability-based and collaborative IP MDO design. In this paper, based on tensile test under different strain rates, the constitutive relation of Polypropylene material is studied. Impact simulation tests for head and knee bolster are carried out to meet the regulation of FMVSS 201 and FMVSS 208, respectively. NVH analysis is performed to obtain mainly the natural frequencies and corresponding mode shapes, while the crashworthiness analysis is employed to examine the crash behavior of IP structure. With the consideration of lightweight, NVH, head and knee bolster impact performance, design of experiment(DOE), response surface model(RSM), and collaborative optimization(CO) are applied to realize the determined and reliability-based optimizations, respectively. Furthermore, based on multi-objective genetic algorithm(MOGA), the optimal Pareto sets are completed to solve the multi-objective optimization(MOO) problem. The proposed research ensures the smoothness of Pareto set, enhances the ability of engineers to make a comprehensive decision about multi-objectives and choose the optimal design, and improves the quality and efficiency of MDO.

Reliable Thermoelectric Module Design under Opposing Requirements from Structural and Thermoelectric Considerations

NASA Astrophysics Data System (ADS)

Karri, Naveen K.; Mo, Changki

2018-06-01

Structural reliability of thermoelectric generation (TEG) systems still remains an issue, especially for applications such as large-scale industrial or automobile exhaust heat recovery, in which TEG systems are subject to dynamic loads and thermal cycling. Traditional thermoelectric (TE) system design and optimization techniques, focused on performance alone, could result in designs that may fail during operation as the geometric requirements for optimal performance (especially the power) are often in conflict with the requirements for mechanical reliability. This study focused on reducing the thermomechanical stresses in a TEG system without compromising the optimized system performance. Finite element simulations were carried out to study the effect of TE element (leg) geometry such as leg length and cross-sectional shape under constrained material volume requirements. Results indicated that the element length has a major influence on the element stresses whereas regular cross-sectional shapes have minor influence. The impact of TE element stresses on the mechanical reliability is evaluated using brittle material failure theory based on Weibull analysis. An alternate couple configuration that relies on the industry practice of redundant element design is investigated. Results showed that the alternate configuration considerably reduced the TE element and metallization stresses, thereby enhancing the structural reliability, with little trade-off in the optimized performance. The proposed alternate configuration could serve as a potential design modification for improving the reliability of systems optimized for thermoelectric performance.

Reliability Sensitivity Analysis and Design Optimization of Composite Structures Based on Response Surface Methodology

NASA Technical Reports Server (NTRS)

Rais-Rohani, Masoud

2003-01-01

This report discusses the development and application of two alternative strategies in the form of global and sequential local response surface (RS) techniques for the solution of reliability-based optimization (RBO) problems. The problem of a thin-walled composite circular cylinder under axial buckling instability is used as a demonstrative example. In this case, the global technique uses a single second-order RS model to estimate the axial buckling load over the entire feasible design space (FDS) whereas the local technique uses multiple first-order RS models with each applied to a small subregion of FDS. Alternative methods for the calculation of unknown coefficients in each RS model are explored prior to the solution of the optimization problem. The example RBO problem is formulated as a function of 23 uncorrelated random variables that include material properties, thickness and orientation angle of each ply, cylinder diameter and length, as well as the applied load. The mean values of the 8 ply thicknesses are treated as independent design variables. While the coefficients of variation of all random variables are held fixed, the standard deviations of ply thicknesses can vary during the optimization process as a result of changes in the design variables. The structural reliability analysis is based on the first-order reliability method with reliability index treated as the design constraint. In addition to the probabilistic sensitivity analysis of reliability index, the results of the RBO problem are presented for different combinations of cylinder length and diameter and laminate ply patterns. The two strategies are found to produce similar results in terms of accuracy with the sequential local RS technique having a considerably better computational efficiency.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Thin-film module circuit design: Practical and reliability aspects

NASA Technical Reports Server (NTRS)

Daiello, R. V.; Twesme, E. N.

1985-01-01

This paper will address several aspects of the design and construction of submodules based on thin film amorphous silicon (a-Si) p i n solar cells. Starting from presently attainable single cell characteristics, and a realistic set of specifications, practical module designs are discussed from the viewpoints of efficient designs, the fabrication requirements, and reliability concerns. The examples center mostly on series interconnected modules of the superstrate type with detailed discussions of each portion of the structure in relation to its influence on module efficiency. Emphasis is placed on engineering topics such as: area coverage, optimal geometries, and cost and reliability. Practical constraints on achieving optimal designs, along with some examples of potential pitfalls in the manufacture and subsequent performance of a-Si modules are discussed.

Reliability-Based Design Optimization of a Composite Airframe Component

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Coroneos, Rula; Patnaik, Surya N.

2011-01-01

A stochastic optimization methodology (SDO) has been developed to design airframe structural components made of metallic and composite materials. The design method accommodates uncertainties in load, strength, and material properties that are defined by distribution functions with mean values and standard deviations. A response parameter, like a failure mode, has become a function of reliability. The primitive variables like thermomechanical loads, material properties, and failure theories, as well as variables like depth of beam or thickness of a membrane, are considered random parameters with specified distribution functions defined by mean values and standard deviations.

Computationally efficient stochastic optimization using multiple realizations

NASA Astrophysics Data System (ADS)

Bayer, P.; Bürger, C. M.; Finkel, M.

2008-02-01

The presented study is concerned with computationally efficient methods for solving stochastic optimization problems involving multiple equally probable realizations of uncertain parameters. A new and straightforward technique is introduced that is based on dynamically ordering the stack of realizations during the search procedure. The rationale is that a small number of critical realizations govern the output of a reliability-based objective function. By utilizing a problem, which is typical to designing a water supply well field, several variants of this "stack ordering" approach are tested. The results are statistically assessed, in terms of optimality and nominal reliability. This study demonstrates that the simple ordering of a given number of 500 realizations while applying an evolutionary search algorithm can save about half of the model runs without compromising the optimization procedure. More advanced variants of stack ordering can, if properly configured, save up to more than 97% of the computational effort that would be required if the entire number of realizations were considered. The findings herein are promising for similar problems of water management and reliability-based design in general, and particularly for non-convex problems that require heuristic search techniques.

Integrated topology for an aircraft electric power distribution system using MATLAB and ILP optimization technique and its implementation

NASA Astrophysics Data System (ADS)

Madhikar, Pratik Ravindra

The most important and crucial design feature while designing an Aircraft Electric Power Distribution System (EPDS) is reliability. In EPDS, the distribution of power is from top level generators to bottom level loads through various sensors, actuators and rectifiers with the help of AC & DC buses and control switches. As the demands of the consumer is never ending and the safety is utmost important, there is an increase in loads and as a result increase in power management. Therefore, the design of an EPDS should be optimized to have maximum efficiency. This thesis discusses an integrated tool that is based on a Need Based Design method and Fault Tree Analysis (FTA) to achieve the optimum design of an EPDS to provide maximum reliability in terms of continuous connectivity, power management and minimum cost. If an EPDS is formulated as an optimization problem then it can be solved with the help of connectivity, cost and power constraints by using a linear solver to get the desired output of maximum reliability at minimum cost. Furthermore, the thesis also discusses the viability and implementation of the resulted topology on typical large aircraft specifications.

Probabilistic Analysis and Design of a Raked Wing Tip for a Commercial Transport

NASA Technical Reports Server (NTRS)

Mason Brian H.; Chen, Tzi-Kang; Padula, Sharon L.; Ransom, Jonathan B.; Stroud, W. Jefferson

2008-01-01

An approach for conducting reliability-based design and optimization (RBDO) of a Boeing 767 raked wing tip (RWT) is presented. The goal is to evaluate the benefits of RBDO for design of an aircraft substructure. A finite-element (FE) model that includes eight critical static load cases is used to evaluate the response of the wing tip. Thirteen design variables that describe the thickness of the composite skins and stiffeners are selected to minimize the weight of the wing tip. A strain-based margin of safety is used to evaluate the performance of the structure. The randomness in the load scale factor and in the strain limits is considered. Of the 13 variables, the wing-tip design was controlled primarily by the thickness of the thickest plies in the upper skins. The report includes an analysis of the optimization results and recommendations for future reliability-based studies.

Towards Risk Based Design for NASA's Missions

NASA Technical Reports Server (NTRS)

Tumer, Irem Y.; Barrientos, Francesca; Meshkat, Leila

2004-01-01

This paper describes the concept of Risk Based Design in the context of NASA s low volume, high cost missions. The concept of accounting for risk in the design lifecycle has been discussed and proposed under several research topics, including reliability, risk analysis, optimization, uncertainty, decision-based design, and robust design. This work aims to identify and develop methods to enable and automate a means to characterize and optimize risk, and use risk as a tradeable resource to make robust and reliable decisions, in the context of the uncertain and ambiguous stage of early conceptual design. This paper first presents a survey of the related topics explored in the design research community as they relate to risk based design. Then, a summary of the topics from the NASA-led Risk Colloquium is presented, followed by current efforts within NASA to account for risk in early design. Finally, a list of "risk elements", identified for early-phase conceptual design at NASA, is presented. The purpose is to lay the foundation and develop a roadmap for future work and collaborations for research to eliminate and mitigate these risk elements in early phase design.

Optimization Under Uncertainty for Electronics Cooling Design

NASA Astrophysics Data System (ADS)

Bodla, Karthik K.; Murthy, Jayathi Y.; Garimella, Suresh V.

Optimization under uncertainty is a powerful methodology used in design and optimization to produce robust, reliable designs. Such an optimization methodology, employed when the input quantities of interest are uncertain, produces output uncertainties, helping the designer choose input parameters that would result in satisfactory thermal solutions. Apart from providing basic statistical information such as mean and standard deviation in the output quantities, auxiliary data from an uncertainty based optimization, such as local and global sensitivities, help the designer decide the input parameter(s) to which the output quantity of interest is most sensitive. This helps the design of experiments based on the most sensitive input parameter(s). A further crucial output of such a methodology is the solution to the inverse problem - finding the allowable uncertainty range in the input parameter(s), given an acceptable uncertainty range in the output quantity of interest...

Optimization of Systems with Uncertainty: Initial Developments for Performance, Robustness and Reliability Based Designs

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Bushnell, Dennis M. (Technical Monitor)

2002-01-01

This paper presents a study on the optimization of systems with structured uncertainties, whose inputs and outputs can be exhaustively described in the probabilistic sense. By propagating the uncertainty from the input to the output in the space of the probability density functions and the moments, optimization problems that pursue performance, robustness and reliability based designs are studied. Be specifying the desired outputs in terms of desired probability density functions and then in terms of meaningful probabilistic indices, we settle a computationally viable framework for solving practical optimization problems. Applications to static optimization and stability control are used to illustrate the relevance of incorporating uncertainty in the early stages of the design. Several examples that admit a full probabilistic description of the output in terms of the design variables and the uncertain inputs are used to elucidate the main features of the generic problem and its solution. Extensions to problems that do not admit closed form solutions are also evaluated. Concrete evidence of the importance of using a consistent probabilistic formulation of the optimization problem and a meaningful probabilistic description of its solution is provided in the examples. In the stability control problem the analysis shows that standard deterministic approaches lead to designs with high probability of running into instability. The implementation of such designs can indeed have catastrophic consequences.

Optimal clustering of MGs based on droop controller for improving reliability using a hybrid of harmony search and genetic algorithms.

PubMed

Abedini, Mohammad; Moradi, Mohammad H; Hosseinian, S M

2016-03-01

This paper proposes a novel method to address reliability and technical problems of microgrids (MGs) based on designing a number of self-adequate autonomous sub-MGs via adopting MGs clustering thinking. In doing so, a multi-objective optimization problem is developed where power losses reduction, voltage profile improvement and reliability enhancement are considered as the objective functions. To solve the optimization problem a hybrid algorithm, named HS-GA, is provided, based on genetic and harmony search algorithms, and a load flow method is given to model different types of DGs as droop controller. The performance of the proposed method is evaluated in two case studies. The results provide support for the performance of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Analyzing Reliability and Performance Trade-Offs of HLS-Based Designs in SRAM-Based FPGAs Under Soft Errors

NASA Astrophysics Data System (ADS)

Tambara, Lucas Antunes; Tonfat, Jorge; Santos, André; Kastensmidt, Fernanda Lima; Medina, Nilberto H.; Added, Nemitala; Aguiar, Vitor A. P.; Aguirre, Fernando; Silveira, Marcilei A. G.

2017-02-01

The increasing system complexity of FPGA-based hardware designs and shortening of time-to-market have motivated the adoption of new designing methodologies focused on addressing the current need for high-performance circuits. High-Level Synthesis (HLS) tools can generate Register Transfer Level (RTL) designs from high-level software programming languages. These tools have evolved significantly in recent years, providing optimized RTL designs, which can serve the needs of safety-critical applications that require both high performance and high reliability levels. However, a reliability evaluation of HLS-based designs under soft errors has not yet been presented. In this work, the trade-offs of different HLS-based designs in terms of reliability, resource utilization, and performance are investigated by analyzing their behavior under soft errors and comparing them to a standard processor-based implementation in an SRAM-based FPGA. Results obtained from fault injection campaigns and radiation experiments show that it is possible to increase the performance of a processor-based system up to 5,000 times by changing its architecture with a small impact in the cross section (increasing up to 8 times), and still increasing the Mean Workload Between Failures (MWBF) of the system.

Data Sufficiency Assessment and Pumping Test Design for Groundwater Prediction Using Decision Theory and Genetic Algorithms

NASA Astrophysics Data System (ADS)

McPhee, J.; William, Y. W.

2005-12-01

This work presents a methodology for pumping test design based on the reliability requirements of a groundwater model. Reliability requirements take into consideration the application of the model results in groundwater management, expressed in this case as a multiobjective management model. The pumping test design is formulated as a mixed-integer nonlinear programming (MINLP) problem and solved using a combination of genetic algorithm (GA) and gradient-based optimization. Bayesian decision theory provides a formal framework for assessing the influence of parameter uncertainty over the reliability of the proposed pumping test. The proposed methodology is useful for selecting a robust design that will outperform all other candidate designs under most potential 'true' states of the system

Aircraft Engine Thrust Estimator Design Based on GSA-LSSVM

NASA Astrophysics Data System (ADS)

Sheng, Hanlin; Zhang, Tianhong

2017-08-01

In view of the necessity of highly precise and reliable thrust estimator to achieve direct thrust control of aircraft engine, based on support vector regression (SVR), as well as least square support vector machine (LSSVM) and a new optimization algorithm - gravitational search algorithm (GSA), by performing integrated modelling and parameter optimization, a GSA-LSSVM-based thrust estimator design solution is proposed. The results show that compared to particle swarm optimization (PSO) algorithm, GSA can find unknown optimization parameter better and enables the model developed with better prediction and generalization ability. The model can better predict aircraft engine thrust and thus fulfills the need of direct thrust control of aircraft engine.

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.

Aerothermodynamic shape optimization of hypersonic blunt bodies

NASA Astrophysics Data System (ADS)

Eyi, Sinan; Yumuşak, Mine

2015-07-01

The aim of this study is to develop a reliable and efficient design tool that can be used in hypersonic flows. The flow analysis is based on the axisymmetric Euler/Navier-Stokes and finite-rate chemical reaction equations. The equations are coupled simultaneously and solved implicitly using Newton's method. The Jacobian matrix is evaluated analytically. A gradient-based numerical optimization is used. The adjoint method is utilized for sensitivity calculations. The objective of the design is to generate a hypersonic blunt geometry that produces the minimum drag with low aerodynamic heating. Bezier curves are used for geometry parameterization. The performances of the design optimization method are demonstrated for different hypersonic flow conditions.

Optimization Testbed Cometboards Extended into Stochastic Domain

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.; Patnaik, Surya N.

2010-01-01

COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.

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.

Robust Control Design for Systems With Probabilistic Uncertainty

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.

2005-01-01

This paper presents a reliability- and robustness-based formulation for robust control synthesis for systems with probabilistic uncertainty. In a reliability-based formulation, the probability of violating design requirements prescribed by inequality constraints is minimized. In a robustness-based formulation, a metric which measures the tendency of a random variable/process to cluster close to a target scalar/function is minimized. A multi-objective optimization procedure, which combines stability and performance requirements in time and frequency domains, is used to search for robustly optimal compensators. Some of the fundamental differences between the proposed strategy and conventional robust control methods are: (i) unnecessary conservatism is eliminated since there is not need for convex supports, (ii) the most likely plants are favored during synthesis allowing for probabilistic robust optimality, (iii) the tradeoff between robust stability and robust performance can be explored numerically, (iv) the uncertainty set is closely related to parameters with clear physical meaning, and (v) compensators with improved robust characteristics for a given control structure can be synthesized.

FY04 Advanced Life Support Architecture and Technology Studies: Mid-Year Presentation

NASA Technical Reports Server (NTRS)

Lange, Kevin; Anderson, Molly; Duffield, Bruce; Hanford, Tony; Jeng, Frank

2004-01-01

Long-Term Objective: Identify optimal advanced life support system designs that meet existing and projected requirements for future human spaceflight missions. a) Include failure-tolerance, reliability, and safe-haven requirements. b) Compare designs based on multiple criteria including equivalent system mass (ESM), technology readiness level (TRL), simplicity, commonality, etc. c) Develop and evaluate new, more optimal, architecture concepts and technology applications.

Control optimization, stabilization and computer algorithms for aircraft applications

NASA Technical Reports Server (NTRS)

1975-01-01

Research related to reliable aircraft design is summarized. Topics discussed include systems reliability optimization, failure detection algorithms, analysis of nonlinear filters, design of compensators incorporating time delays, digital compensator design, estimation for systems with echoes, low-order compensator design, descent-phase controller for 4-D navigation, infinite dimensional mathematical programming problems and optimal control problems with constraints, robust compensator design, numerical methods for the Lyapunov equations, and perturbation methods in linear filtering and control.

A system methodology for optimization design of the structural crashworthiness of a vehicle subjected to a high-speed frontal crash

NASA Astrophysics Data System (ADS)

Xia, Liang; Liu, Weiguo; Lv, Xiaojiang; Gu, Xianguang

2018-04-01

The structural crashworthiness design of vehicles has become an important research direction to ensure the safety of the occupants. To effectively improve the structural safety of a vehicle in a frontal crash, a system methodology is presented in this study. The surrogate model of Online support vector regression (Online-SVR) is adopted to approximate crashworthiness criteria and different kernel functions are selected to enhance the accuracy of the model. The Online-SVR model is demonstrated to have the advantages of solving highly nonlinear problems and saving training costs, and can effectively be applied for vehicle structural crashworthiness design. By combining the non-dominated sorting genetic algorithm II and Monte Carlo simulation, both deterministic optimization and reliability-based design optimization (RBDO) are conducted. The optimization solutions are further validated by finite element analysis, which shows the effectiveness of the RBDO solution in the structural crashworthiness design process. The results demonstrate the advantages of using RBDO, resulting in not only increased energy absorption and decreased structural weight from a baseline design, but also a significant improvement in the reliability of the design.

Parts and Components Reliability Assessment: A Cost Effective Approach

NASA Technical Reports Server (NTRS)

Lee, Lydia

2009-01-01

System reliability assessment is a methodology which incorporates reliability analyses performed at parts and components level such as Reliability Prediction, Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA) to assess risks, perform design tradeoffs, and therefore, to ensure effective productivity and/or mission success. The system reliability is used to optimize the product design to accommodate today?s mandated budget, manpower, and schedule constraints. Stand ard based reliability assessment is an effective approach consisting of reliability predictions together with other reliability analyses for electronic, electrical, and electro-mechanical (EEE) complex parts and components of large systems based on failure rate estimates published by the United States (U.S.) military or commercial standards and handbooks. Many of these standards are globally accepted and recognized. The reliability assessment is especially useful during the initial stages when the system design is still in the development and hard failure data is not yet available or manufacturers are not contractually obliged by their customers to publish the reliability estimates/predictions for their parts and components. This paper presents a methodology to assess system reliability using parts and components reliability estimates to ensure effective productivity and/or mission success in an efficient manner, low cost, and tight schedule.

A diameter-sensitive flow entropy method for reliability consideration in water distribution system design

NASA Astrophysics Data System (ADS)

Liu, Haixing; Savić, Dragan; Kapelan, Zoran; Zhao, Ming; Yuan, Yixing; Zhao, Hongbin

2014-07-01

Flow entropy is a measure of uniformity of pipe flows in water distribution systems. By maximizing flow entropy one can identify reliable layouts or connectivity in networks. In order to overcome the disadvantage of the common definition of flow entropy that does not consider the impact of pipe diameter on reliability, an extended definition of flow entropy, termed as diameter-sensitive flow entropy, is proposed. This new methodology is then assessed by using other reliability methods, including Monte Carlo Simulation, a pipe failure probability model, and a surrogate measure (resilience index) integrated with water demand and pipe failure uncertainty. The reliability assessment is based on a sample of WDS designs derived from an optimization process for each of the two benchmark networks. Correlation analysis is used to evaluate quantitatively the relationship between entropy and reliability. To ensure reliability, a comparative analysis between the flow entropy and the new method is conducted. The results demonstrate that the diameter-sensitive flow entropy shows consistently much stronger correlation with the three reliability measures than simple flow entropy. Therefore, the new flow entropy method can be taken as a better surrogate measure for reliability and could be potentially integrated into the optimal design problem of WDSs. Sensitivity analysis results show that the velocity parameters used in the new flow entropy has no significant impact on the relationship between diameter-sensitive flow entropy and reliability.

Reliability-based optimization of an active vibration controller using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Saraygord Afshari, Sajad; Pourtakdoust, Seid H.

2017-04-01

Many modern industrialized systems such as aircrafts, rotating turbines, satellite booms, etc. cannot perform their desired tasks accurately if their uninhibited structural vibrations are not controlled properly. Structural health monitoring and online reliability calculations are emerging new means to handle system imposed uncertainties. As stochastic forcing are unavoidable, in most engineering systems, it is often needed to take them into the account for the control design process. In this research, smart material technology is utilized for structural health monitoring and control in order to keep the system in a reliable performance range. In this regard, a reliability-based cost function is assigned for both controller gain optimization as well as sensor placement. The proposed scheme is implemented and verified for a wing section. Comparison of results for the frequency responses is considered to show potential applicability of the presented technique.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease

NASA Astrophysics Data System (ADS)

Gorzelic, P.; Schiff, S. J.; Sinha, A.

2013-04-01

Objective. To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). Approach. A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. Main Results. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Significance. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

Model-based rational feedback controller design for closed-loop deep brain stimulation of Parkinson's disease.

PubMed

Gorzelic, P; Schiff, S J; Sinha, A

2013-04-01

To explore the use of classical feedback control methods to achieve an improved deep brain stimulation (DBS) algorithm for application to Parkinson's disease (PD). A computational model of PD dynamics was employed to develop model-based rational feedback controller design. The restoration of thalamocortical relay capabilities to patients suffering from PD is formulated as a feedback control problem with the DBS waveform serving as the control input. Two high-level control strategies are tested: one that is driven by an online estimate of thalamic reliability, and another that acts to eliminate substantial decreases in the inhibition from the globus pallidus interna (GPi) to the thalamus. Control laws inspired by traditional proportional-integral-derivative (PID) methodology are prescribed for each strategy and simulated on this computational model of the basal ganglia network. For control based upon thalamic reliability, a strategy of frequency proportional control with proportional bias delivered the optimal control achieved for a given energy expenditure. In comparison, control based upon synaptic inhibitory output from the GPi performed very well in comparison with those of reliability-based control, with considerable further reduction in energy expenditure relative to that of open-loop DBS. The best controller performance was amplitude proportional with derivative control and integral bias, which is full PID control. We demonstrated how optimizing the three components of PID control is feasible in this setting, although the complexity of these optimization functions argues for adaptive methods in implementation. Our findings point to the potential value of model-based rational design of feedback controllers for Parkinson's disease.

The Role of Probabilistic Design Analysis Methods in Safety and Affordability

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.

2016-01-01

For the last several years, NASA and its contractors have been working together to build space launch systems to commercialize space. Developing commercial affordable and safe launch systems becomes very important and requires a paradigm shift. This paradigm shift enforces the need for an integrated systems engineering environment where cost, safety, reliability, and performance need to be considered to optimize the launch system design. In such an environment, rule based and deterministic engineering design practices alone may not be sufficient to optimize margins and fault tolerance to reduce cost. As a result, introduction of Probabilistic Design Analysis (PDA) methods to support the current deterministic engineering design practices becomes a necessity to reduce cost without compromising reliability and safety. This paper discusses the importance of PDA methods in NASA's new commercial environment, their applications, and the key role they can play in designing reliable, safe, and affordable launch systems. More specifically, this paper discusses: 1) The involvement of NASA in PDA 2) Why PDA is needed 3) A PDA model structure 4) A PDA example application 5) PDA link to safety and affordability.

Design optimization of a fuzzy distributed generation (DG) system with multiple renewable energy sources

NASA Astrophysics Data System (ADS)

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.

2012-09-01

The global rise in energy demands brings major obstacles to many energy organizations in providing adequate energy supply. Hence, many techniques to generate cost effective, reliable and environmentally friendly alternative energy source are being explored. One such method is the integration of photovoltaic cells, wind turbine generators and fuel-based generators, included with storage batteries. This sort of power systems are known as distributed generation (DG) power system. However, the application of DG power systems raise certain issues such as cost effectiveness, environmental impact and reliability. The modelling as well as the optimization of this DG power system was successfully performed in the previous work using Particle Swarm Optimization (PSO). The central idea of that work was to minimize cost, minimize emissions and maximize reliability (multi-objective (MO) setting) with respect to the power balance and design requirements. In this work, we introduce a fuzzy model that takes into account the uncertain nature of certain variables in the DG system which are dependent on the weather conditions (such as; the insolation and wind speed profiles). The MO optimization in a fuzzy environment was performed by applying the Hopfield Recurrent Neural Network (HNN). Analysis on the optimized results was then carried out.

A Bayesian-Based EDA Tool for Nano-circuits Reliability Calculations

NASA Astrophysics Data System (ADS)

Ibrahim, Walid; Beiu, Valeriu

As the sizes of (nano-)devices are aggressively scaled deep into the nanometer range, the design and manufacturing of future (nano-)circuits will become extremely complex and inevitably will introduce more defects while their functioning will be adversely affected by transient faults. Therefore, accurately calculating the reliability of future designs will become a very important aspect for (nano-)circuit designers as they investigate several design alternatives to optimize the trade-offs between the conflicting metrics of area-power-energy-delay versus reliability. This paper introduces a novel generic technique for the accurate calculation of the reliability of future nano-circuits. Our aim is to provide both educational and research institutions (as well as the semiconductor industry at a later stage) with an accurate and easy to use tool for closely comparing the reliability of different design alternatives, and for being able to easily select the design that best fits a set of given (design) constraints. Moreover, the reliability model generated by the tool should empower designers with the unique opportunity of understanding the influence individual gates play on the design’s overall reliability, and identifying those (few) gates which impact the design’s reliability most significantly.

Mathematical programming models for the economic design and assessment of wind energy conversion systems

NASA Astrophysics Data System (ADS)

Reinert, K. A.

The use of linear decision rules (LDR) and chance constrained programming (CCP) to optimize the performance of wind energy conversion clusters coupled to storage systems is described. Storage is modelled by LDR and output by CCP. The linear allocation rule and linear release rule prescribe the size and optimize a storage facility with a bypass. Chance constraints are introduced to explicitly treat reliability in terms of an appropriate value from an inverse cumulative distribution function. Details of deterministic programming structure and a sample problem involving a 500 kW and a 1.5 MW WECS are provided, considering an installed cost of $1/kW. Four demand patterns and three levels of reliability are analyzed for optimizing the generator choice and the storage configuration for base load and peak operating conditions. Deficiencies in ability to predict reliability and to account for serial correlations are noted in the model, which is concluded useful for narrowing WECS design options.

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

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

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S.

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.« less

Reliability based design of the primary structure of oil tankers

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

Casella, G.; Dogliani, M.; Guedes Soares, C.

1996-12-31

The present paper describes the reliability analysis carried out for two oil tanker-ships having comparable dimensions but different design. The scope of the analysis was to derive indications on the value of the reliability index obtained for existing, typical and well designed oil tankers, as well as to apply the tentative rule checking formulation developed within the CEC-funded SHIPREL Project. The checking formula was adopted to redesign the midships section of one of the considered ships, upgrading her in order to meet the target failure probability considered in the rule development process. The resulting structure, in view of an upgradingmore » of the steel grade in the central part of the deck, lead to a convenient reliability level. The results of the analysis clearly showed that a large scatter exists presently in the design safety levels of ships, even when the Classification Societies` unified requirements are satisfied. A reliability based approach for the calibration of the rules for the global strength of ships is therefore proposed, in order to assist designers and Classification Societies in the process of producing ships which are more optimized, with respect to ensured safety levels. Based on the work reported in the paper, the feasibility and usefulness of a reliability based approach in the development of ship longitudinal strength requirements has been demonstrated.« less

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.

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.

Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1994-01-01

The reliability with bounded distribution parameters (mean, standard deviation) was maximized and the reliability-based cost was minimized for adaptive intra-ply hybrid fiber composites by using a probabilistic method. The probabilistic method accounts for all naturally occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry, and control-related parameters. Probabilistic sensitivity factors were computed and used in the optimization procedures. For actuated change in the angle of attack of an airfoil-like composite shell structure with an adaptive torque plate, the reliability was maximized to 0.9999 probability, with constraints on the mean and standard deviation of the actuation material volume ratio (percentage of actuation composite material in a ply) and the actuation strain coefficient. The reliability-based cost was minimized for an airfoil-like composite shell structure with an adaptive skin and a mean actuation material volume ratio as the design parameter. At a O.9-mean actuation material volume ratio, the minimum cost was obtained.

Design and Optimization Method of a Two-Disk Rotor System

NASA Astrophysics Data System (ADS)

Huang, Jingjing; Zheng, Longxi; Mei, Qing

2016-04-01

An integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.

Reliability evaluation of high-performance, low-power FinFET standard cells based on mixed RBB/FBB technique

NASA Astrophysics Data System (ADS)

Wang, Tian; Cui, Xiaoxin; Ni, Yewen; Liao, Kai; Liao, Nan; Yu, Dunshan; Cui, Xiaole

2017-04-01

With shrinking transistor feature size, the fin-type field-effect transistor (FinFET) has become the most promising option in low-power circuit design due to its superior capability to suppress leakage. To support the VLSI digital system flow based on logic synthesis, we have designed an optimized high-performance low-power FinFET standard cell library based on employing the mixed FBB/RBB technique in the existing stacked structure of each cell. This paper presents the reliability evaluation of the optimized cells under process and operating environment variations based on Monte Carlo analysis. The variations are modelled with Gaussian distribution of the device parameters and 10000 sweeps are conducted in the simulation to obtain the statistical properties of the worst-case delay and input-dependent leakage for each cell. For comparison, a set of non-optimal cells that adopt the same topology without employing the mixed biasing technique is also generated. Experimental results show that the optimized cells achieve standard deviation reduction of 39.1% and 30.7% at most in worst-case delay and input-dependent leakage respectively while the normalized deviation shrinking in worst-case delay and input-dependent leakage can be up to 98.37% and 24.13%, respectively, which demonstrates that our optimized cells are less sensitive to variability and exhibit more reliability. Project supported by the National Natural Science Foundation of China (No. 61306040), the State Key Development Program for Basic Research of China (No. 2015CB057201), the Beijing Natural Science Foundation (No. 4152020), and Natural Science Foundation of Guangdong Province, China (No. 2015A030313147).

Reliability Methods for Shield Design Process

NASA Technical Reports Server (NTRS)

Tripathi, R. K.; Wilson, J. W.

2002-01-01

Providing protection against the hazards of space radiation is a major challenge to the exploration and development of space. The great cost of added radiation shielding is a potential limiting factor in deep space operations. In this enabling technology, we have developed methods for optimized shield design over multi-segmented missions involving multiple work and living areas in the transport and duty phase of space missions. The total shield mass over all pieces of equipment and habitats is optimized subject to career dose and dose rate constraints. An important component of this technology is the estimation of two most commonly identified uncertainties in radiation shield design, the shielding properties of materials used and the understanding of the biological response of the astronaut to the radiation leaking through the materials into the living space. The largest uncertainty, of course, is in the biological response to especially high charge and energy (HZE) ions of the galactic cosmic rays. These uncertainties are blended with the optimization design procedure to formulate reliability-based methods for shield design processes. The details of the methods will be discussed.

Optimization of an electromagnetic linear actuator using a network and a finite element model

NASA Astrophysics Data System (ADS)

Neubert, Holger; Kamusella, Alfred; Lienig, Jens

2011-03-01

Model based design optimization leads to robust solutions only if the statistical deviations of design, load and ambient parameters from nominal values are considered. We describe an optimization methodology that involves these deviations as stochastic variables for an exemplary electromagnetic actuator used to drive a Braille printer. A combined model simulates the dynamic behavior of the actuator and its non-linear load. It consists of a dynamic network model and a stationary magnetic finite element (FE) model. The network model utilizes lookup tables of the magnetic force and the flux linkage computed by the FE model. After a sensitivity analysis using design of experiment (DoE) methods and a nominal optimization based on gradient methods, a robust design optimization is performed. Selected design variables are involved in form of their density functions. In order to reduce the computational effort we use response surfaces instead of the combined system model obtained in all stochastic analysis steps. Thus, Monte-Carlo simulations can be applied. As a result we found an optimum system design meeting our requirements with regard to function and reliability.

A Simple and Reliable Method of Design for Standalone Photovoltaic Systems

NASA Astrophysics Data System (ADS)

Srinivasarao, Mantri; Sudha, K. Rama; Bhanu, C. V. K.

2017-06-01

Standalone photovoltaic (SAPV) systems are seen as a promoting method of electrifying areas of developing world that lack power grid infrastructure. Proliferations of these systems require a design procedure that is simple, reliable and exhibit good performance over its life time. The proposed methodology uses simple empirical formulae and easily available parameters to design SAPV systems, that is, array size with energy storage. After arriving at the different array size (area), performance curves are obtained for optimal design of SAPV system with high amount of reliability in terms of autonomy at a specified value of loss of load probability (LOLP). Based on the array to load ratio (ALR) and levelized energy cost (LEC) through life cycle cost (LCC) analysis, it is shown that the proposed methodology gives better performance, requires simple data and is more reliable when compared with conventional design using monthly average daily load and insolation.

A Gradient-Based Multistart Algorithm for Multimodal Aerodynamic Shape Optimization Problems Based on Free-Form Deformation

NASA Astrophysics Data System (ADS)

Streuber, Gregg Mitchell

Environmental and economic factors motivate the pursuit of more fuel-efficient aircraft designs. Aerodynamic shape optimization is a powerful tool in this effort, but is hampered by the presence of multimodality in many design spaces. Gradient-based multistart optimization uses a sampling algorithm and multiple parallel optimizations to reliably apply fast gradient-based optimization to moderately multimodal problems. Ensuring that the sampled geometries remain physically realizable requires manually developing specialized linear constraints for each class of problem. Utilizing free-form deformation geometry control allows these linear constraints to be written in a geometry-independent fashion, greatly easing the process of applying the algorithm to new problems. This algorithm was used to assess the presence of multimodality when optimizing a wing in subsonic and transonic flows, under inviscid and viscous conditions, and a blended wing-body under transonic, viscous conditions. Multimodality was present in every wing case, while the blended wing-body was found to be generally unimodal.

System principles, mathematical models and methods to ensure high reliability of safety systems

NASA Astrophysics Data System (ADS)

Zaslavskyi, V.

2017-04-01

Modern safety and security systems are composed of a large number of various components designed for detection, localization, tracking, collecting, and processing of information from the systems of monitoring, telemetry, control, etc. They are required to be highly reliable in a view to correctly perform data aggregation, processing and analysis for subsequent decision making support. On design and construction phases of the manufacturing of such systems a various types of components (elements, devices, and subsystems) are considered and used to ensure high reliability of signals detection, noise isolation, and erroneous commands reduction. When generating design solutions for highly reliable systems a number of restrictions and conditions such as types of components and various constrains on resources should be considered. Various types of components perform identical functions; however, they are implemented using diverse principles, approaches and have distinct technical and economic indicators such as cost or power consumption. The systematic use of different component types increases the probability of tasks performing and eliminates the common cause failure. We consider type-variety principle as an engineering principle of system analysis, mathematical models based on this principle, and algorithms for solving optimization problems of highly reliable safety and security systems design. Mathematical models are formalized in a class of two-level discrete optimization problems of large dimension. The proposed approach, mathematical models, algorithms can be used for problem solving of optimal redundancy on the basis of a variety of methods and control devices for fault and defects detection in technical systems, telecommunication networks, and energy systems.

Topology Optimization of Lightweight Lattice Structural Composites Inspired by Cuttlefish Bone

NASA Astrophysics Data System (ADS)

Hu, Zhong; Gadipudi, Varun Kumar; Salem, David R.

2018-03-01

Lattice structural composites are of great interest to various industries where lightweight multifunctionality is important, especially aerospace. However, strong coupling among the composition, microstructure, porous topology, and fabrication of such materials impedes conventional trial-and-error experimental development. In this work, a discontinuous carbon fiber reinforced polymer matrix composite was adopted for structural design. A reliable and robust design approach for developing lightweight multifunctional lattice structural composites was proposed, inspired by biomimetics and based on topology optimization. Three-dimensional periodic lattice blocks were initially designed, inspired by the cuttlefish bone microstructure. The topologies of the three-dimensional periodic blocks were further optimized by computer modeling, and the mechanical properties of the topology optimized lightweight lattice structures were characterized by computer modeling. The lattice structures with optimal performance were identified.

A multi-material topology optimization approach for wrinkle-free design of cable-suspended membrane structures

NASA Astrophysics Data System (ADS)

Luo, Yangjun; Niu, Yanzhuang; Li, Ming; Kang, Zhan

2017-06-01

In order to eliminate stress-related wrinkles in cable-suspended membrane structures and to provide simple and reliable deployment, this study presents a multi-material topology optimization model and an effective solution procedure for generating optimal connected layouts for membranes and cables. On the basis of the principal stress criterion of membrane wrinkling behavior and the density-based interpolation of multi-phase materials, the optimization objective is to maximize the total structural stiffness while satisfying principal stress constraints and specified material volume requirements. By adopting the cosine-type relaxation scheme to avoid the stress singularity phenomenon, the optimization model is successfully solved through a standard gradient-based algorithm. Four-corner tensioned membrane structures with different loading cases were investigated to demonstrate the effectiveness of the proposed method in automatically finding the optimal design composed of curved boundary cables and wrinkle-free membranes.

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual

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

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a theoretical manual for selected algorithms implemented within the Dakota software. It is not intended as a comprehensive theoretical treatment, since a number of existing texts cover general optimization theory, statistical analysis, and other introductory topics. Rather, this manual is intended to summarize a set of Dakota-related research publications in the areas of surrogate-based optimization, uncertainty quanti cation, and optimization under uncertainty that provide the foundation for many of Dakota's iterative analysis capabilities.« less

Design optimization under uncertainty and speed variability for a piezoelectric energy harvester powering a tire pressure monitoring sensor

NASA Astrophysics Data System (ADS)

Toghi Eshghi, Amin; Lee, Soobum; Kazem Sadoughi, Mohammad; Hu, Chao; Kim, Young-Cheol; Seo, Jong-Ho

2017-10-01

Energy harvesting (EH) technologies to power small sized electronic devices are attracting great attention. Wasted energy in a vehicle’s rotating tire has a great potential to enable self-powered tire pressure monitoring sensors (TPMS). Piezoelectric type energy harvesters can be used to collect vibrational energy and power such systems. Due to the presence of harsh acceleration in a rotating tire, a design tradeoff needs to be studied to prolong the harvester’s fatigue life as well as to ensure sufficient power generation. However, the design by traditional deterministic design optimization (DDO) does not show reliable performance due to the lack of consideration of various uncertainty factors (e.g., manufacturing tolerances, material properties, and loading conditions). In this study, we address a new EH design formulation that considers the uncertainty in car speed, dimensional tolerances and material properties, and solve this design problem using reliability-based design optimization (RBDO). The RBDO problem is formulated to maximize compactness and minimize weight of a TPMS harvester while satisfying power and durability requirements. A transient analysis has been done to measure the time varying response of EH such as power generation, dynamic strain, and stress. A conservative design formulation is proposed to consider the expected power from varied speed and stress at higher speed. When compared to the DDO, the RBDO results show that the reliability of EH is increased significantly by scarifying the objective function. Finally, experimental test has been conducted to demonstrate the merits of RBDO design over DDO.

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

Reliability-based optimization design of geosynthetic reinforced road embankment.

DOT National Transportation Integrated Search

2014-07-01

Road embankments are typically large earth structures, the construction of which requires for large amounts of competent fill soil. In order to limit costs, the utilization of geosynthetics in road embankments allows for construction of steep slopes ...

Strategies and Approaches to TPS Design

NASA Technical Reports Server (NTRS)

Kolodziej, Paul

2005-01-01

Thermal protection systems (TPS) insulate planetary probes and Earth re-entry vehicles from the aerothermal heating experienced during hypersonic deceleration to the planet s surface. The systems are typically designed with some additional capability to compensate for both variations in the TPS material and for uncertainties in the heating environment. This additional capability, or robustness, also provides a surge capability for operating under abnormal severe conditions for a short period of time, and for unexpected events, such as meteoroid impact damage, that would detract from the nominal performance. Strategies and approaches to developing robust designs must also minimize mass because an extra kilogram of TPS displaces one kilogram of payload. Because aircraft structures must be optimized for minimum mass, reliability-based design approaches for mechanical components exist that minimize mass. Adapting these existing approaches to TPS component design takes advantage of the extensive work, knowledge, and experience from nearly fifty years of reliability-based design of mechanical components. A Non-Dimensional Load Interference (NDLI) method for calculating the thermal reliability of TPS components is presented in this lecture and applied to several examples. A sensitivity analysis from an existing numerical simulation of a carbon phenolic TPS provides insight into the effects of the various design parameters, and is used to demonstrate how sensitivity analysis may be used with NDLI to develop reliability-based designs of TPS components.

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

Multidisciplinary Optimization of a Transport Aircraft Wing using Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw; Venter, Gerhard

2002-01-01

The purpose of this paper is to demonstrate the application of particle swarm optimization to a realistic multidisciplinary optimization test problem. The paper's new contributions to multidisciplinary optimization is the application of a new algorithm for dealing with the unique challenges associated with multidisciplinary optimization problems, and recommendations as to the utility of the algorithm in future multidisciplinary optimization applications. The selected example is a bi-level optimization problem that demonstrates severe numerical noise and has a combination of continuous and truly discrete design variables. The use of traditional gradient-based optimization algorithms is thus not practical. The numerical results presented indicate that the particle swarm optimization algorithm is able to reliably find the optimum design for the problem presented here. The algorithm is capable of dealing with the unique challenges posed by multidisciplinary optimization as well as the numerical noise and truly discrete variables present in the current example problem.

A new design approach to innovative spectrometers. Case study: TROPOLITE

NASA Astrophysics Data System (ADS)

Volatier, Jean-Baptiste; Baümer, Stefan; Kruizinga, Bob; Vink, Rob

2014-05-01

Designing a novel optical system is a nested iterative process. The optimization loop, from a starting point to final system is already mostly automated. However this loop is part of a wider loop which is not. This wider loop starts with an optical specification and ends with a manufacturability assessment. When designing a new spectrometer with emphasis on weight and cost, numerous iterations between the optical- and mechanical designer are inevitable. The optical designer must then be able to reliably produce optical designs based on new input gained from multidisciplinary studies. This paper presents a procedure that can automatically generate new starting points based on any kind of input or new constraint that might arise. These starting points can then be handed over to a generic optimization routine to make the design tasks extremely efficient. The optical designer job is then not to design optical systems, but to meta-design a procedure that produces optical systems paving the way for system level optimization. We present here this procedure and its application to the design of TROPOLITE a lightweight push broom imaging spectrometer.

Optimization of 3D Field Design

NASA Astrophysics Data System (ADS)

Logan, Nikolas; Zhu, Caoxiang

2017-10-01

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

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.

Applicability and Limitations of Reliability Allocation Methods

NASA Technical Reports Server (NTRS)

Cruz, Jose A.

2016-01-01

Reliability allocation process may be described as the process of assigning reliability requirements to individual components within a system to attain the specified system reliability. For large systems, the allocation process is often performed at different stages of system design. The allocation process often begins at the conceptual stage. As the system design develops, more information about components and the operating environment becomes available, different allocation methods can be considered. Reliability allocation methods are usually divided into two categories: weighting factors and optimal reliability allocation. When properly applied, these methods can produce reasonable approximations. Reliability allocation techniques have limitations and implied assumptions that need to be understood by system engineers. Applying reliability allocation techniques without understanding their limitations and assumptions can produce unrealistic results. This report addresses weighting factors, optimal reliability allocation techniques, and identifies the applicability and limitations of each reliability allocation technique.

Uncertainty-Based Multi-Objective Optimization of Groundwater Remediation Design

NASA Astrophysics Data System (ADS)

Singh, A.; Minsker, B.

2003-12-01

Management of groundwater contamination is a cost-intensive undertaking filled with conflicting objectives and substantial uncertainty. A critical source of this uncertainty in groundwater remediation design problems comes from the hydraulic conductivity values for the aquifer, upon which the prediction of flow and transport of contaminants are dependent. For a remediation solution to be reliable in practice it is important that it is robust over the potential error in the model predictions. This work focuses on incorporating such uncertainty within a multi-objective optimization framework, to get reliable as well as Pareto optimal solutions. Previous research has shown that small amounts of sampling within a single-objective genetic algorithm can produce highly reliable solutions. However with multiple objectives the noise can interfere with the basic operations of a multi-objective solver, such as determining non-domination of individuals, diversity preservation, and elitism. This work proposes several approaches to improve the performance of noisy multi-objective solvers. These include a simple averaging approach, taking samples across the population (which we call extended averaging), and a stochastic optimization approach. All the approaches are tested on standard multi-objective benchmark problems and a hypothetical groundwater remediation case-study; the best-performing approach is then tested on a field-scale case at Umatilla Army Depot.

A homotopy algorithm for digital optimal projection control GASD-HADOC

NASA Technical Reports Server (NTRS)

Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.

1993-01-01

The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-01-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Interconnect fatigue design for terrestrial photovoltaic modules

NASA Astrophysics Data System (ADS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1982-03-01

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

An intelligent case-adjustment algorithm for the automated design of population-based quality auditing protocols.

PubMed

Advani, Aneel; Jones, Neil; Shahar, Yuval; Goldstein, Mary K; Musen, Mark A

2004-01-01

We develop a method and algorithm for deciding the optimal approach to creating quality-auditing protocols for guideline-based clinical performance measures. An important element of the audit protocol design problem is deciding which guide-line elements to audit. Specifically, the problem is how and when to aggregate individual patient case-specific guideline elements into population-based quality measures. The key statistical issue involved is the trade-off between increased reliability with more general population-based quality measures versus increased validity from individually case-adjusted but more restricted measures done at a greater audit cost. Our intelligent algorithm for auditing protocol design is based on hierarchically modeling incrementally case-adjusted quality constraints. We select quality constraints to measure using an optimization criterion based on statistical generalizability coefficients. We present results of the approach from a deployed decision support system for a hypertension guideline.

System Design under Uncertainty: Evolutionary Optimization of the Gravity Probe-B Spacecraft

NASA Technical Reports Server (NTRS)

Pullen, Samuel P.; Parkinson, Bradford W.

1994-01-01

This paper discusses the application of evolutionary random-search algorithms (Simulated Annealing and Genetic Algorithms) to the problem of spacecraft design under performance uncertainty. Traditionally, spacecraft performance uncertainty has been measured by reliability. Published algorithms for reliability optimization are seldom used in practice because they oversimplify reality. The algorithm developed here uses random-search optimization to allow us to model the problem more realistically. Monte Carlo simulations are used to evaluate the objective function for each trial design solution. These methods have been applied to the Gravity Probe-B (GP-B) spacecraft being developed at Stanford University for launch in 1999, Results of the algorithm developed here for GP-13 are shown, and their implications for design optimization by evolutionary algorithms are discussed.

Use of nonlinear design optimization techniques in the comparison of battery discharger topologies for the space platform

NASA Technical Reports Server (NTRS)

Sable, Dan M.; Cho, Bo H.; Lee, Fred C.

1990-01-01

A detailed comparison of a boost converter, a voltage-fed, autotransformer converter, and a multimodule boost converter, designed specifically for the space platform battery discharger, is performed. Computer-based nonlinear optimization techniques are used to facilitate an objective comparison. The multimodule boost converter is shown to be the optimum topology at all efficiencies. The margin is greatest at 97 percent efficiency. The multimodule, multiphase boost converter combines the advantages of high efficiency, light weight, and ample margin on the component stresses, thus ensuring high reliability.

The Use of the Direct Optimized Probabilistic Calculation Method in Design of Bolt Reinforcement for Underground and Mining Workings

PubMed Central

Krejsa, Martin; Janas, Petr; Yilmaz, Işık; Marschalko, Marian; Bouchal, Tomas

2013-01-01

The load-carrying system of each construction should fulfill several conditions which represent reliable criteria in the assessment procedure. It is the theory of structural reliability which determines probability of keeping required properties of constructions. Using this theory, it is possible to apply probabilistic computations based on the probability theory and mathematic statistics. Development of those methods has become more and more popular; it is used, in particular, in designs of load-carrying structures with the required level or reliability when at least some input variables in the design are random. The objective of this paper is to indicate the current scope which might be covered by the new method—Direct Optimized Probabilistic Calculation (DOProC) in assessments of reliability of load-carrying structures. DOProC uses a purely numerical approach without any simulation techniques. This provides more accurate solutions to probabilistic tasks, and, in some cases, such approach results in considerably faster completion of computations. DOProC can be used to solve efficiently a number of probabilistic computations. A very good sphere of application for DOProC is the assessment of the bolt reinforcement in the underground and mining workings. For the purposes above, a special software application—“Anchor”—has been developed. PMID:23935412

DAKOTA Design Analysis Kit for Optimization and Terascale

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

Adams, Brian M.; Dalbey, Keith R.; Eldred, Michael S.

2010-02-24

The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes (computational models) and iterative analysis methods. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and analysis of computational models on high performance computers.A user provides a set of DAKOTA commands in an input file and launches DAKOTA. DAKOTA invokes instances of the computational models, collects their results, and performs systems analyses. DAKOTA contains algorithms for optimization with gradient and nongradient-basedmore » methods; uncertainty quantification with sampling, reliability, polynomial chaos, stochastic collocation, and epistemic methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as hybrid optimization, surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. Services for parallel computing, simulation interfacing, approximation modeling, fault tolerance, restart, and graphics are also included.« less

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

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.

Advanced power analysis methodology targeted to the optimization of a digital pixel readout chip design and its critical serial powering system

NASA Astrophysics Data System (ADS)

Marconi, S.; Orfanelli, S.; Karagounis, M.; Hemperek, T.; Christiansen, J.; Placidi, P.

2017-02-01

A dedicated power analysis methodology, based on modern digital design tools and integrated with the VEPIX53 simulation framework developed within RD53 collaboration, is being used to guide vital choices for the design and optimization of the next generation ATLAS and CMS pixel chips and their critical serial powering circuit (shunt-LDO). Power consumption is studied at different stages of the design flow under different operating conditions. Significant effort is put into extensive investigations of dynamic power variations in relation with the decoupling seen by the powering network. Shunt-LDO simulations are also reported to prove the reliability at the system level.

A reliability design method for a lithium-ion battery pack considering the thermal disequilibrium in electric vehicles

NASA Astrophysics Data System (ADS)

Xia, Quan; Wang, Zili; Ren, Yi; Sun, Bo; Yang, Dezhen; Feng, Qiang

2018-05-01

With the rapid development of lithium-ion battery technology in the electric vehicle (EV) industry, the lifetime of the battery cell increases substantially; however, the reliability of the battery pack is still inadequate. Because of the complexity of the battery pack, a reliability design method for a lithium-ion battery pack considering the thermal disequilibrium is proposed in this paper based on cell redundancy. Based on this method, a three-dimensional electric-thermal-flow-coupled model, a stochastic degradation model of cells under field dynamic conditions and a multi-state system reliability model of a battery pack are established. The relationships between the multi-physics coupling model, the degradation model and the system reliability model are first constructed to analyze the reliability of the battery pack and followed by analysis examples with different redundancy strategies. By comparing the reliability of battery packs of different redundant cell numbers and configurations, several conclusions for the redundancy strategy are obtained. More notably, the reliability does not monotonically increase with the number of redundant cells for the thermal disequilibrium effects. In this work, the reliability of a 6 × 5 parallel-series configuration is the optimal system structure. In addition, the effect of the cell arrangement and cooling conditions are investigated.

Methodological aspects of an adaptive multidirectional pattern search to optimize speech perception using three hearing-aid algorithms

NASA Astrophysics Data System (ADS)

Franck, Bas A. M.; Dreschler, Wouter A.; Lyzenga, Johannes

2004-12-01

In this study we investigated the reliability and convergence characteristics of an adaptive multidirectional pattern search procedure, relative to a nonadaptive multidirectional pattern search procedure. The procedure was designed to optimize three speech-processing strategies. These comprise noise reduction, spectral enhancement, and spectral lift. The search is based on a paired-comparison paradigm, in which subjects evaluated the listening comfort of speech-in-noise fragments. The procedural and nonprocedural factors that influence the reliability and convergence of the procedure are studied using various test conditions. The test conditions combine different tests, initial settings, background noise types, and step size configurations. Seven normal hearing subjects participated in this study. The results indicate that the reliability of the optimization strategy may benefit from the use of an adaptive step size. Decreasing the step size increases accuracy, while increasing the step size can be beneficial to create clear perceptual differences in the comparisons. The reliability also depends on starting point, stop criterion, step size constraints, background noise, algorithms used, as well as the presence of drifting cues and suboptimal settings. There appears to be a trade-off between reliability and convergence, i.e., when the step size is enlarged the reliability improves, but the convergence deteriorates. .

Deterministic Design Optimization of Structures in OpenMDAO Framework

NASA Technical Reports Server (NTRS)

Coroneos, Rula M.; Pai, Shantaram S.

2012-01-01

Nonlinear programming algorithms play an important role in structural design optimization. Several such algorithms have been implemented in OpenMDAO framework developed at NASA Glenn Research Center (GRC). OpenMDAO is an open source engineering analysis framework, written in Python, for analyzing and solving Multi-Disciplinary Analysis and Optimization (MDAO) problems. It provides a number of solvers and optimizers, referred to as components and drivers, which users can leverage to build new tools and processes quickly and efficiently. Users may download, use, modify, and distribute the OpenMDAO software at no cost. This paper summarizes the process involved in analyzing and optimizing structural components by utilizing the framework s structural solvers and several gradient based optimizers along with a multi-objective genetic algorithm. For comparison purposes, the same structural components were analyzed and optimized using CometBoards, a NASA GRC developed code. The reliability and efficiency of the OpenMDAO framework was compared and reported in this report.

Field design factors affecting the precision of ryegrass forage yield estimation

USDA-ARS?s Scientific Manuscript database

Field-based agronomic and genetic research relies heavily on the data generated from field evaluations. Therefore, it is imperative to optimize the precision and accuracy of yield estimates in cultivar evaluation trials to make reliable selections. Experimental error in yield trials is sensitive to ...

Development of a Multistage Reliability-Based Design Optimization Method

DTIC Science & Technology

2014-01-01

expressed using Eq. (7), where nx is the number of design variables P a0 þ Xnx i¼1 aini þ bið Þxi 0 " # a (7) Figures 3(a)–3(c) illustrates the...constraint equation can be expressed in the gen- eral form of Eq. (16), where again nx is the number of design variables P a0;j þ Xnx i¼1 ai;jnixi

System Risk Assessment and Allocation in Conceptual Design

NASA Technical Reports Server (NTRS)

Mahadevan, Sankaran; Smith, Natasha L.; Zang, Thomas A. (Technical Monitor)

2003-01-01

As aerospace systems continue to evolve in addressing newer challenges in air and space transportation, there exists a heightened priority for significant improvement in system performance, cost effectiveness, reliability, and safety. Tools, which synthesize multidisciplinary integration, probabilistic analysis, and optimization, are needed to facilitate design decisions allowing trade-offs between cost and reliability. This study investigates tools for probabilistic analysis and probabilistic optimization in the multidisciplinary design of aerospace systems. A probabilistic optimization methodology is demonstrated for the low-fidelity design of a reusable launch vehicle at two levels, a global geometry design and a local tank design. Probabilistic analysis is performed on a high fidelity analysis of a Navy missile system. Furthermore, decoupling strategies are introduced to reduce the computational effort required for multidisciplinary systems with feedback coupling.

Optimal Management of Redundant Control Authority for Fault Tolerance

NASA Technical Reports Server (NTRS)

Wu, N. Eva; Ju, Jianhong

2000-01-01

This paper is intended to demonstrate the feasibility of a solution to a fault tolerant control problem. It explains, through a numerical example, the design and the operation of a novel scheme for fault tolerant control. The fundamental principle of the scheme was formalized in [5] based on the notion of normalized nonspecificity. The novelty lies with the use of a reliability criterion for redundancy management, and therefore leads to a high overall system reliability.

A PC program to optimize system configuration for desired reliability at minimum cost

NASA Technical Reports Server (NTRS)

Hills, Steven W.; Siahpush, Ali S.

1994-01-01

High reliability is desired in all engineered systems. One way to improve system reliability is to use redundant components. When redundant components are used, the problem becomes one of allocating them to achieve the best reliability without exceeding other design constraints such as cost, weight, or volume. Systems with few components can be optimized by simply examining every possible combination but the number of combinations for most systems is prohibitive. A computerized iteration of the process is possible but anything short of a super computer requires too much time to be practical. Many researchers have derived mathematical formulations for calculating the optimum configuration directly. However, most of the derivations are based on continuous functions whereas the real system is composed of discrete entities. Therefore, these techniques are approximations of the true optimum solution. This paper describes a computer program that will determine the optimum configuration of a system of multiple redundancy of both standard and optional components. The algorithm is a pair-wise comparative progression technique which can derive the true optimum by calculating only a small fraction of the total number of combinations. A designer can quickly analyze a system with this program on a personal computer.

Reliability and availability evaluation of Wireless Sensor Networks for industrial applications.

PubMed

Silva, Ivanovitch; Guedes, Luiz Affonso; Portugal, Paulo; Vasques, Francisco

2012-01-01

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements.

Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial Applications

PubMed Central

Silva, Ivanovitch; Guedes, Luiz Affonso; Portugal, Paulo; Vasques, Francisco

2012-01-01

Wireless Sensor Networks (WSN) currently represent the best candidate to be adopted as the communication solution for the last mile connection in process control and monitoring applications in industrial environments. Most of these applications have stringent dependability (reliability and availability) requirements, as a system failure may result in economic losses, put people in danger or lead to environmental damages. Among the different type of faults that can lead to a system failure, permanent faults on network devices have a major impact. They can hamper communications over long periods of time and consequently disturb, or even disable, control algorithms. The lack of a structured approach enabling the evaluation of permanent faults, prevents system designers to optimize decisions that minimize these occurrences. In this work we propose a methodology based on an automatic generation of a fault tree to evaluate the reliability and availability of Wireless Sensor Networks, when permanent faults occur on network devices. The proposal supports any topology, different levels of redundancy, network reconfigurations, criticality of devices and arbitrary failure conditions. The proposed methodology is particularly suitable for the design and validation of Wireless Sensor Networks when trying to optimize its reliability and availability requirements. PMID:22368497

Design modification for the modular helium reactor for higher temperature operation and reliability studies for nuclear hydrogen production processes

NASA Astrophysics Data System (ADS)

Reza, S. M. Mohsin

Design options have been evaluated for the Modular Helium Reactor (MHR) for higher temperature operation. An alternative configuration for the MHR coolant inlet flow path is developed to reduce the peak vessel temperature (PVT). The coolant inlet path is shifted from the annular path between reactor core barrel and vessel wall through the permanent side reflector (PSR). The number and dimensions of coolant holes are varied to optimize the pressure drop, the inlet velocity, and the percentage of graphite removed from the PSR to create this inlet path. With the removal of ˜10% of the graphite from PSR the PVT is reduced from 541°C to 421°C. A new design for the graphite block core has been evaluated and optimized to reduce the inlet coolant temperature with the aim of further reduction of PVT. The dimensions and number of fuel rods and coolant holes, and the triangular pitch have been changed and optimized. Different packing fractions for the new core design have been used to conserve the number of fuel particles. Thermal properties for the fuel elements are calculated and incorporated into these analyses. The inlet temperature, mass flow and bypass flow are optimized to limit the peak fuel temperature (PFT) within an acceptable range. Using both of these modifications together, the PVT is reduced to ˜350°C while keeping the outlet temperature at 950°C and maintaining the PFT within acceptable limits. The vessel and fuel temperatures during low pressure conduction cooldown and high pressure conduction cooldown transients are found to be well below the design limits. The reliability and availability studies for coupled nuclear hydrogen production processes based on the sulfur iodine thermochemical process and high temperature electrolysis process have been accomplished. The fault tree models for both these processes are developed. Using information obtained on system configuration, component failure probability, component repair time and system operating modes and conditions, the system reliability and availability are assessed. Required redundancies are made to improve system reliability and to optimize the plant design for economic performance. The failure rates and outage factors of both processes are found to be well below the maximum acceptable range.

Design and control strategy for a hybrid green energy system for mobile telecommunication sites

NASA Astrophysics Data System (ADS)

Okundamiya, Michael S.; Emagbetere, Joy O.; Ogujor, Emmanuel A.

2014-07-01

The rising energy costs and carbon footprint of operating mobile telecommunication sites in the emerging world have increased research interests in green technology. The intermittent nature of most green energy sources creates the problem of designing the optimum configuration for a given location. This study presents the design analysis and control strategy for a cost effective and reliable operation of the hybrid green energy system (HGES) for GSM base transceiver station (BTS) sites in isolated regions. The design constrains the generation and distribution of power to reliably satisfy the energy demand while ensuring safe operation of the system. The overall process control applies the genetic algorithm-based technique for optimal techno-economic sizing of system's components. The process simulation utilized meteorological data for 3 locations (Abuja, Benin City and Sokoto) with varying climatic conditions in Nigeria. Simulation results presented for green GSM BTS sites are discussed and compared with existing approaches.

AMOVA ["Accumulative Manifold Validation Analysis"]: An Advanced Statistical Methodology Designed to Measure and Test the Validity, Reliability, and Overall Efficacy of Inquiry-Based Psychometric Instruments

ERIC Educational Resources Information Center

Osler, James Edward, II

2015-01-01

This monograph provides an epistemological rational for the Accumulative Manifold Validation Analysis [also referred by the acronym "AMOVA"] statistical methodology designed to test psychometric instruments. This form of inquiry is a form of mathematical optimization in the discipline of linear stochastic modelling. AMOVA is an in-depth…

Advanced propulsion engine assessment based on a cermet reactor

NASA Technical Reports Server (NTRS)

Parsley, Randy C.

1993-01-01

A preferred Pratt & Whitney conceptual Nuclear Thermal Rocket Engine (NTRE) has been designed based on the fundamental NASA priorities of safety, reliability, cost, and performance. The basic philosophy underlying the design of the XNR2000 is the utilization of the most reliable form of ultrahigh temperature nuclear fuel and development of a core configuration which is optimized for uniform power distribution, operational flexibility, power maneuverability, weight, and robustness. The P&W NTRE system employs a fast spectrum, cermet fueled reactor configured in an expander cycle to ensure maximum operational safety. The cermet fuel form provides retention of fuel and fission products as well as high strength. A high level of confidence is provided by benchmark analysis and independent evaluations.

A Network Coding Based Hybrid ARQ Protocol for Underwater Acoustic Sensor Networks

PubMed Central

Wang, Hao; Wang, Shilian; Zhang, Eryang; Zou, Jianbin

2016-01-01

Underwater Acoustic Sensor Networks (UASNs) have attracted increasing interest in recent years due to their extensive commercial and military applications. However, the harsh underwater channel causes many challenges for the design of reliable underwater data transport protocol. In this paper, we propose an energy efficient data transport protocol based on network coding and hybrid automatic repeat request (NCHARQ) to ensure reliability, efficiency and availability in UASNs. Moreover, an adaptive window length estimation algorithm is designed to optimize the throughput and energy consumption tradeoff. The algorithm can adaptively change the code rate and can be insensitive to the environment change. Extensive simulations and analysis show that NCHARQ significantly reduces energy consumption with short end-to-end delay. PMID:27618044

CFD-Based Design Optimization for Single Element Rocket Injector

NASA Technical Reports Server (NTRS)

Vaidyanathan, Rajkumar; Tucker, Kevin; Papila, Nilay; Shyy, Wei

2003-01-01

To develop future Reusable Launch Vehicle concepts, we have conducted design optimization for a single element rocket injector, with overall goals of improving reliability and performance while reducing cost. Computational solutions based on the Navier-Stokes equations, finite rate chemistry, and the k-E turbulence closure are generated with design of experiment techniques, and the response surface method is employed as the optimization tool. The design considerations are guided by four design objectives motivated by the consideration in both performance and life, namely, the maximum temperature on the oxidizer post tip, the maximum temperature on the injector face, the adiabatic wall temperature, and the length of the combustion zone. Four design variables are selected, namely, H2 flow angle, H2 and O2 flow areas with fixed flow rates, and O2 post tip thickness. In addition to establishing optimum designs by varying emphasis on the individual objectives, better insight into the interplay between design variables and their impact on the design objectives is gained. The investigation indicates that improvement in performance or life comes at the cost of the other. Best compromise is obtained when improvements in both performance and life are given equal importance.

A Homogenization Approach for Design and Simulation of Blast Resistant Composites

NASA Astrophysics Data System (ADS)

Sheyka, Michael

Structural composites have been used in aerospace and structural engineering due to their high strength to weight ratio. Composite laminates have been successfully and extensively used in blast mitigation. This dissertation examines the use of the homogenization approach to design and simulate blast resistant composites. Three case studies are performed to examine the usefulness of different methods that may be used in designing and optimizing composite plates for blast resistance. The first case study utilizes a single degree of freedom system to simulate the blast and a reliability based approach. The first case study examines homogeneous plates and the optimal stacking sequence and plate thicknesses are determined. The second and third case studies use the homogenization method to calculate the properties of composite unit cell made of two different materials. The methods are integrated with dynamic simulation environments and advanced optimization algorithms. The second case study is 2-D and uses an implicit blast simulation, while the third case study is 3-D and simulates blast using the explicit blast method. Both case studies 2 and 3 rely on multi-objective genetic algorithms for the optimization process. Pareto optimal solutions are determined in case studies 2 and 3. Case study 3 is an integrative method for determining optimal stacking sequence, microstructure and plate thicknesses. The validity of the different methods such as homogenization, reliability, explicit blast modeling and multi-objective genetic algorithms are discussed. Possible extension of the methods to include strain rate effects and parallel computation is also examined.

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

Photovoltaic design optimization for terrestrial applications

NASA Technical Reports Server (NTRS)

Ross, R. G., Jr.

1978-01-01

As part of the Jet Propulsion Laboratory's Low-Cost Solar Array Project, a comprehensive program of module cost-optimization has been carried out. The objective of these studies has been to define means of reducing the cost and improving the utility and reliability of photovoltaic modules for the broad spectrum of terrestrial applications. This paper describes one of the methods being used for module optimization, including the derivation of specific equations which allow the optimization of various module design features. The method is based on minimizing the life-cycle cost of energy for the complete system. Comparison of the life-cycle energy cost with the marginal cost of energy each year allows the logical plant lifetime to be determined. The equations derived allow the explicit inclusion of design parameters such as tracking, site variability, and module degradation with time. An example problem involving the selection of an optimum module glass substrate is presented.

High power diode lasers emitting from 639 nm to 690 nm

NASA Astrophysics Data System (ADS)

Bao, L.; Grimshaw, M.; DeVito, M.; Kanskar, M.; Dong, W.; Guan, X.; Zhang, S.; Patterson, J.; Dickerson, P.; Kennedy, K.; Li, S.; Haden, J.; Martinsen, R.

2014-03-01

There is increasing market demand for high power reliable red lasers for display and cinema applications. Due to the fundamental material system limit at this wavelength range, red diode lasers have lower efficiency and are more temperature sensitive, compared to 790-980 nm diode lasers. In terms of reliability, red lasers are also more sensitive to catastrophic optical mirror damage (COMD) due to the higher photon energy. Thus developing higher power-reliable red lasers is very challenging. This paper will present nLIGHT's released red products from 639 nm to 690nm, with established high performance and long-term reliability. These single emitter diode lasers can work as stand-alone singleemitter units or efficiently integrate into our compact, passively-cooled Pearl™ fiber-coupled module architectures for higher output power and improved reliability. In order to further improve power and reliability, new chip optimizations have been focused on improving epitaxial design/growth, chip configuration/processing and optical facet passivation. Initial optimization has demonstrated promising results for 639 nm diode lasers to be reliably rated at 1.5 W and 690nm diode lasers to be reliably rated at 4.0 W. Accelerated life-test has started and further design optimization are underway.

Optimizing the Reliability and Performance of Service Composition Applications with Fault Tolerance in Wireless Sensor Networks

PubMed Central

Wu, Zhao; Xiong, Naixue; Huang, Yannong; Xu, Degang; Hu, Chunyang

2015-01-01

The services composition technology provides flexible methods for building service composition applications (SCAs) in wireless sensor networks (WSNs). The high reliability and high performance of SCAs help services composition technology promote the practical application of WSNs. The optimization methods for reliability and performance used for traditional software systems are mostly based on the instantiations of software components, which are inapplicable and inefficient in the ever-changing SCAs in WSNs. In this paper, we consider the SCAs with fault tolerance in WSNs. Based on a Universal Generating Function (UGF) we propose a reliability and performance model of SCAs in WSNs, which generalizes a redundancy optimization problem to a multi-state system. Based on this model, an efficient optimization algorithm for reliability and performance of SCAs in WSNs is developed based on a Genetic Algorithm (GA) to find the optimal structure of SCAs with fault-tolerance in WSNs. In order to examine the feasibility of our algorithm, we have evaluated the performance. Furthermore, the interrelationships between the reliability, performance and cost are investigated. In addition, a distinct approach to determine the most suitable parameters in the suggested algorithm is proposed. PMID:26561818

A method of network topology optimization design considering application process characteristic

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Reliability Analysis of Sealing Structure of Electromechanical System Based on Kriging Model

NASA Astrophysics Data System (ADS)

Zhang, F.; Wang, Y. M.; Chen, R. W.; Deng, W. W.; Gao, Y.

2018-05-01

The sealing performance of aircraft electromechanical system has a great influence on flight safety, and the reliability of its typical seal structure is analyzed by researcher. In this paper, we regard reciprocating seal structure as a research object to study structural reliability. Having been based on the finite element numerical simulation method, the contact stress between the rubber sealing ring and the cylinder wall is calculated, and the relationship between the contact stress and the pressure of the hydraulic medium is built, and the friction force on different working conditions are compared. Through the co-simulation, the adaptive Kriging model obtained by EFF learning mechanism is used to describe the failure probability of the seal ring, so as to evaluate the reliability of the sealing structure. This article proposes a new idea of numerical evaluation for the reliability analysis of sealing structure, and also provides a theoretical basis for the optimal design of sealing structure.

SensoTube: A Scalable Hardware Design Architecture for Wireless Sensors and Actuators Networks Nodes in the Agricultural Domain.

PubMed

Piromalis, Dimitrios; Arvanitis, Konstantinos

2016-08-04

Wireless Sensor and Actuators Networks (WSANs) constitute one of the most challenging technologies with tremendous socio-economic impact for the next decade. Functionally and energy optimized hardware systems and development tools maybe is the most critical facet of this technology for the achievement of such prospects. Especially, in the area of agriculture, where the hostile operating environment comes to add to the general technological and technical issues, reliable and robust WSAN systems are mandatory. This paper focuses on the hardware design architectures of the WSANs for real-world agricultural applications. It presents the available alternatives in hardware design and identifies their difficulties and problems for real-life implementations. The paper introduces SensoTube, a new WSAN hardware architecture, which is proposed as a solution to the various existing design constraints of WSANs. The establishment of the proposed architecture is based, firstly on an abstraction approach in the functional requirements context, and secondly, on the standardization of the subsystems connectivity, in order to allow for an open, expandable, flexible, reconfigurable, energy optimized, reliable and robust hardware system. The SensoTube implementation reference model together with its encapsulation design and installation are analyzed and presented in details. Furthermore, as a proof of concept, certain use cases have been studied in order to demonstrate the benefits of migrating existing designs based on the available open-source hardware platforms to SensoTube architecture.

Autonomous optimal trajectory design employing convex optimization for powered descent on an asteroid

NASA Astrophysics Data System (ADS)

Pinson, Robin Marie

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 (fuel) optimal powered descent trajectory that can be quickly computed onboard the spacecraft, without interaction from ground control. The goal is to autonomously design the optimal powered descent trajectory onboard the spacecraft immediately prior to the descent burn for use during the burn. Compared to a planetary powered landing problem, the challenges that arise from designing an asteroid powered descent trajectory include complicated nonlinear gravity fields, small rotating bodies, and low thrust vehicles. The nonlinear gravity fields cannot be represented by a constant gravity model nor a Newtonian model. The trajectory design algorithm needs to be robust and efficient to guarantee a designed trajectory and complete the calculations in a reasonable time frame. This research investigates the following questions: Can convex optimization be used to design the minimum propellant powered descent trajectory for a soft landing on an asteroid? Is this method robust and reliable to allow autonomy onboard the spacecraft without interaction from ground control? This research designed a convex optimization based method that rapidly generates the propellant optimal asteroid powered descent trajectory. The solution to the convex optimization problem is the thrust magnitude and direction, which designs and determines the trajectory. The propellant optimal problem was formulated as a second order cone program, a subset of convex optimization, through relaxation techniques by including a slack variable, change of variables, and incorporation of the successive solution method. Convex optimization solvers, especially second order cone programs, are robust, reliable, and are guaranteed to find the global minimum provided one exists. In addition, an outer optimization loop using Brent's method determines the optimal flight time corresponding to the minimum propellant usage over all flight times. Inclusion of additional trajectory constraints, solely vertical motion near the landing site and glide slope, were evaluated. Through a theoretical proof involving the Minimum Principle from Optimal Control Theory and the Karush-Kuhn-Tucker conditions it was shown that the relaxed problem is identical to the original problem at the minimum point. Therefore, the optimal solution of the relaxed problem is an optimal solution of the original problem, referred to as lossless convexification. A key finding is that this holds for all levels of gravity model fidelity. The designed thrust magnitude profiles were the bang-bang predicted by Optimal Control Theory. The first high fidelity gravity model employed was the 2x2 spherical harmonics model assuming a perfect triaxial ellipsoid and placement of the coordinate frame at the asteroid's center of mass and aligned with the semi-major axes. The spherical harmonics model is not valid inside the Brillouin sphere and this becomes relevant for irregularly shaped asteroids. Then, a higher fidelity model was implemented combining the 4x4 spherical harmonics gravity model with the interior spherical Bessel gravity model. All gravitational terms in the equations of motion are evaluated with the position vector from the previous iteration, creating the successive solution method. Methodology success was shown by applying the algorithm to three triaxial ellipsoidal asteroids with four different rotation speeds using the 2x2 gravity model. Finally, the algorithm was tested using the irregularly shaped asteroid, Castalia.

Texture and haptic cues in slant discrimination: reliability-based cue weighting without statistically optimal cue combination

NASA Astrophysics Data System (ADS)

Rosas, Pedro; Wagemans, Johan; Ernst, Marc O.; Wichmann, Felix A.

2005-05-01

A number of models of depth-cue combination suggest that the final depth percept results from a weighted average of independent depth estimates based on the different cues available. The weight of each cue in such an average is thought to depend on the reliability of each cue. In principle, such a depth estimation could be statistically optimal in the sense of producing the minimum-variance unbiased estimator that can be constructed from the available information. Here we test such models by using visual and haptic depth information. Different texture types produce differences in slant-discrimination performance, thus providing a means for testing a reliability-sensitive cue-combination model with texture as one of the cues to slant. Our results show that the weights for the cues were generally sensitive to their reliability but fell short of statistically optimal combination - we find reliability-based reweighting but not statistically optimal cue combination.

Hierarchical Bayesian Model Averaging for Chance Constrained Remediation Designs

NASA Astrophysics Data System (ADS)

Chitsazan, N.; Tsai, F. T.

2012-12-01

Groundwater remediation designs are heavily relying on simulation models which are subjected to various sources of uncertainty in their predictions. To develop a robust remediation design, it is crucial to understand the effect of uncertainty sources. In this research, we introduce a hierarchical Bayesian model averaging (HBMA) framework to segregate and prioritize sources of uncertainty in a multi-layer frame, where each layer targets a source of uncertainty. The HBMA framework provides an insight to uncertainty priorities and propagation. In addition, HBMA allows evaluating model weights in different hierarchy levels and assessing the relative importance of models in each level. To account for uncertainty, we employ a chance constrained (CC) programming for stochastic remediation design. Chance constrained programming was implemented traditionally to account for parameter uncertainty. Recently, many studies suggested that model structure uncertainty is not negligible compared to parameter uncertainty. Using chance constrained programming along with HBMA can provide a rigorous tool for groundwater remediation designs under uncertainty. In this research, the HBMA-CC was applied to a remediation design in a synthetic aquifer. The design was to develop a scavenger well approach to mitigate saltwater intrusion toward production wells. HBMA was employed to assess uncertainties from model structure, parameter estimation and kriging interpolation. An improved harmony search optimization method was used to find the optimal location of the scavenger well. We evaluated prediction variances of chloride concentration at the production wells through the HBMA framework. The results showed that choosing the single best model may lead to a significant error in evaluating prediction variances for two reasons. First, considering the single best model, variances that stem from uncertainty in the model structure will be ignored. Second, considering the best model with non-dominant model weight may underestimate or overestimate prediction variances by ignoring other plausible propositions. Chance constraints allow developing a remediation design with a desirable reliability. However, considering the single best model, the calculated reliability will be different from the desirable reliability. We calculated the reliability of the design for the models at different levels of HBMA. The results showed that by moving toward the top layers of HBMA, the calculated reliability converges to the chosen reliability. We employed the chance constrained optimization along with the HBMA framework to find the optimal location and pumpage for the scavenger well. The results showed that using models at different levels in the HBMA framework, the optimal location of the scavenger well remained the same, but the optimal extraction rate was altered. Thus, we concluded that the optimal pumping rate was sensitive to the prediction variance. Also, the prediction variance was changed by using different extraction rate. Using very high extraction rate will cause prediction variances of chloride concentration at the production wells to approach zero regardless of which HBMA models used.

Fuzzy probabilistic design of water distribution networks

NASA Astrophysics Data System (ADS)

Fu, Guangtao; Kapelan, Zoran

2011-05-01

The primary aim of this paper is to present a fuzzy probabilistic approach for optimal design and rehabilitation of water distribution systems, combining aleatoric and epistemic uncertainties in a unified framework. The randomness and imprecision in future water consumption are characterized using fuzzy random variables whose realizations are not real but fuzzy numbers, and the nodal head requirements are represented by fuzzy sets, reflecting the imprecision in customers' requirements. The optimal design problem is formulated as a two-objective optimization problem, with minimization of total design cost and maximization of system performance as objectives. The system performance is measured by the fuzzy random reliability, defined as the probability that the fuzzy head requirements are satisfied across all network nodes. The satisfactory degree is represented by necessity measure or belief measure in the sense of the Dempster-Shafer theory of evidence. An efficient algorithm is proposed, within a Monte Carlo procedure, to calculate the fuzzy random system reliability and is effectively combined with the nondominated sorting genetic algorithm II (NSGAII) to derive the Pareto optimal design solutions. The newly proposed methodology is demonstrated with two case studies: the New York tunnels network and Hanoi network. The results from both cases indicate that the new methodology can effectively accommodate and handle various aleatoric and epistemic uncertainty sources arising from the design process and can provide optimal design solutions that are not only cost-effective but also have higher reliability to cope with severe future uncertainties.

Product modular design incorporating preventive maintenance issues

NASA Astrophysics Data System (ADS)

Gao, Yicong; Feng, Yixiong; Tan, Jianrong

2016-03-01

Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.

A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition

PubMed Central

Ciotti, Simone; Battaglia, Edoardo; Carbonaro, Nicola; Bicchi, Antonio; Tognetti, Alessandro; Bianchi, Matteo

2016-01-01

Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements) of wearable hand pose reconstruction (HPR) systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF) technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom) leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness. PMID:27271621

A Synergy-Based Optimally Designed Sensing Glove for Functional Grasp Recognition.

PubMed

Ciotti, Simone; Battaglia, Edoardo; Carbonaro, Nicola; Bicchi, Antonio; Tognetti, Alessandro; Bianchi, Matteo

2016-06-02

Achieving accurate and reliable kinematic hand pose reconstructions represents a challenging task. The main reason for this is the complexity of hand biomechanics, where several degrees of freedom are distributed along a continuous deformable structure. Wearable sensing can represent a viable solution to tackle this issue, since it enables a more natural kinematic monitoring. However, the intrinsic accuracy (as well as the number of sensing elements) of wearable hand pose reconstruction (HPR) systems can be severely limited by ergonomics and cost considerations. In this paper, we combined the theoretical foundations of the optimal design of HPR devices based on hand synergy information, i.e., the inter-joint covariation patterns, with textile goniometers based on knitted piezoresistive fabrics (KPF) technology, to develop, for the first time, an optimally-designed under-sensed glove for measuring hand kinematics. We used only five sensors optimally placed on the hand and completed hand pose reconstruction (described according to a kinematic model with 19 degrees of freedom) leveraging upon synergistic information. The reconstructions we obtained from five different subjects were used to implement an unsupervised method for the recognition of eight functional grasps, showing a high degree of accuracy and robustness.

Finite element based electric motor design optimization

NASA Technical Reports Server (NTRS)

Campbell, C. Warren

1993-01-01

The purpose of this effort was to develop a finite element code for the analysis and design of permanent magnet electric motors. These motors would drive electromechanical actuators in advanced rocket engines. The actuators would control fuel valves and thrust vector control systems. Refurbishing the hydraulic systems of the Space Shuttle after each flight is costly and time consuming. Electromechanical actuators could replace hydraulics, improve system reliability, and reduce down time.

An Efficient Variable Screening Method for Effective Surrogate Models for Reliability-Based Design Optimization

DTIC Science & Technology

2014-04-01

surrogate model generation is difficult for high -dimensional problems, due to the curse of dimensionality. Variable screening methods have been...a variable screening model was developed for the quasi-molecular treatment of ion-atom collision [16]. In engineering, a confidence interval of...for high -level radioactive waste [18]. Moreover, the design sensitivity method can be extended to the variable screening method because vital

Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design

NASA Astrophysics Data System (ADS)

Keum, Jongho; Coulibaly, Paulin; Razavi, Tara; Tapsoba, Dominique; Gobena, Adam; Weber, Frank; Pietroniro, Alain

2018-06-01

Snow has a unique characteristic in the water cycle, that is, snow falls during the entire winter season, but the discharge from snowmelt is typically delayed until the melting period and occurs in a relatively short period. Therefore, reliable observations from an optimal snow monitoring network are necessary for an efficient management of snowmelt water for flood prevention and hydropower generation. The Dual Entropy and Multiobjective Optimization is applied to design snow monitoring networks in La Grande River Basin in Québec and Columbia River Basin in British Columbia. While the networks are optimized to have the maximum amount of information with minimum redundancy based on entropy concepts, this study extends the traditional entropy applications to the hydrometric network design by introducing several improvements. First, several data quantization cases and their effects on the snow network design problems were explored. Second, the applicability the Snow Data Assimilation System (SNODAS) products as synthetic datasets of potential stations was demonstrated in the design of the snow monitoring network of the Columbia River Basin. Third, beyond finding the Pareto-optimal networks from the entropy with multi-objective optimization, the networks obtained for La Grande River Basin were further evaluated by applying three hydrologic models. The calibrated hydrologic models simulated discharges using the updated snow water equivalent data from the Pareto-optimal networks. Then, the model performances for high flows were compared to determine the best optimal network for enhanced spring runoff forecasting.

Design of a modular digital computer system

NASA Technical Reports Server (NTRS)

1973-01-01

A design tradeoff study is reported for a modular spaceborne computer system that is responsive to many mission types and phases. The computer uses redundancy to maximize reliability, and multiprocessing to maximize processing capacity. Fault detection and recovery features provide optimal reliability.

A reliability-based cost effective fail-safe design procedure

NASA Technical Reports Server (NTRS)

Hanagud, S.; Uppaluri, B.

1976-01-01

The authors have developed a methodology for cost-effective fatigue design of structures subject to random fatigue loading. A stochastic model for fatigue crack propagation under random loading has been discussed. Fracture mechanics is then used to estimate the parameters of the model and the residual strength of structures with cracks. The stochastic model and residual strength variations have been used to develop procedures for estimating the probability of failure and its changes with inspection frequency. This information on reliability is then used to construct an objective function in terms of either a total weight function or cost function. A procedure for selecting the design variables, subject to constraints, by optimizing the objective function has been illustrated by examples. In particular, optimum design of stiffened panel has been discussed.

Using wound care algorithms: a content validation study.

PubMed

Beitz, J M; van Rijswijk, L

1999-09-01

Valid and reliable heuristic devices facilitating optimal wound care are lacking. The objectives of this study were to establish content validation data for a set of wound care algorithms, to identify their associated strengths and weaknesses, and to gain insight into the wound care decision-making process. Forty-four registered nurse wound care experts were surveyed and interviewed at national and regional educational meetings. Using a cross-sectional study design and an 83-item, 4-point Likert-type scale, this purposive sample was asked to quantify the degree of validity of the algorithms' decisions and components. Participants' comments were tape-recorded, transcribed, and themes were derived. On a scale of 1 to 4, the mean score of the entire instrument was 3.47 (SD +/- 0.87), the instrument's Content Validity Index was 0.86, and the individual Content Validity Index of 34 of 44 participants was > 0.8. Item scores were lower for those related to packing deep wounds (P < .001). No other significant differences were observed. Qualitative data analysis revealed themes of difficulty associated with wound assessment and care issues, that is, the absence of valid and reliable definitions. The wound care algorithms studied proved valid. However, the lack of valid and reliable wound assessment and care definitions hinders optimal use of these instruments. Further research documenting their clinical use is warranted. Research-based practice recommendations should direct the development of future valid and reliable algorithms designed to help nurses provide optimal wound care.

Probabilistic Design of a Wind Tunnel Model to Match the Response of a Full-Scale Aircraft

NASA Technical Reports Server (NTRS)

Mason, Brian H.; Stroud, W. Jefferson; Krishnamurthy, T.; Spain, Charles V.; Naser, Ahmad S.

2005-01-01

approach is presented for carrying out the reliability-based design of a plate-like wing that is part of a wind tunnel model. The goal is to design the wind tunnel model to match the stiffness characteristics of the wing box of a flight vehicle while satisfying strength-based risk/reliability requirements that prevents damage to the wind tunnel model and fixtures. The flight vehicle is a modified F/A-18 aircraft. The design problem is solved using reliability-based optimization techniques. The objective function to be minimized is the difference between the displacements of the wind tunnel model and the corresponding displacements of the flight vehicle. The design variables control the thickness distribution of the wind tunnel model. Displacements of the wind tunnel model change with the thickness distribution, while displacements of the flight vehicle are a set of fixed data. The only constraint imposed is that the probability of failure is less than a specified value. Failure is assumed to occur if the stress caused by aerodynamic pressure loading is greater than the specified strength allowable. Two uncertain quantities are considered: the allowable stress and the thickness distribution of the wind tunnel model. Reliability is calculated using Monte Carlo simulation with response surfaces that provide approximate values of stresses. The response surface equations are, in turn, computed from finite element analyses of the wind tunnel model at specified design points. Because the response surface approximations were fit over a small region centered about the current design, the response surfaces were refit periodically as the design variables changed. Coarse-grained parallelism was used to simultaneously perform multiple finite element analyses. Studies carried out in this paper demonstrate that this scheme of using moving response surfaces and coarse-grained computational parallelism reduce the execution time of the Monte Carlo simulation enough to make the design problem tractable. The results of the reliability-based designs performed in this paper show that large decreases in the probability of stress-based failure can be realized with only small sacrifices in the ability of the wind tunnel model to represent the displacements of the full-scale vehicle.

Development of the hard and soft constraints based optimisation model for unit sizing of the hybrid renewable energy system designed for microgrid applications

NASA Astrophysics Data System (ADS)

Sundaramoorthy, Kumaravel

2017-02-01

The hybrid energy systems (HESs) based electricity generation system has become a more attractive solution for rural electrification nowadays. Economically feasible and technically reliable HESs are solidly based on an optimisation stage. This article discusses about the optimal unit sizing model with the objective function to minimise the total cost of the HES. Three typical rural sites from southern part of India have been selected for the application of the developed optimisation methodology. Feasibility studies and sensitivity analysis on the optimal HES are discussed elaborately in this article. A comparison has been carried out with the Hybrid Optimization Model for Electric Renewable optimisation model for three sites. The optimal HES is found with less total net present rate and rate of energy compared with the existing method

An expert system for integrated structural analysis and design optimization for aerospace structures

NASA Technical Reports Server (NTRS)

1992-01-01

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

An expert system for integrated structural analysis and design optimization for aerospace structures

NASA Astrophysics Data System (ADS)

1992-04-01

The results of a research study on the development of an expert system for integrated structural analysis and design optimization is presented. An Object Representation Language (ORL) was developed first in conjunction with a rule-based system. This ORL/AI shell was then used to develop expert systems to provide assistance with a variety of structural analysis and design optimization tasks, in conjunction with procedural modules for finite element structural analysis and design optimization. The main goal of the research study was to provide expertise, judgment, and reasoning capabilities in the aerospace structural design process. This will allow engineers performing structural analysis and design, even without extensive experience in the field, to develop error-free, efficient and reliable structural designs very rapidly and cost-effectively. This would not only improve the productivity of design engineers and analysts, but also significantly reduce time to completion of structural design. An extensive literature survey in the field of structural analysis, design optimization, artificial intelligence, and database management systems and their application to the structural design process was first performed. A feasibility study was then performed, and the architecture and the conceptual design for the integrated 'intelligent' structural analysis and design optimization software was then developed. An Object Representation Language (ORL), in conjunction with a rule-based system, was then developed using C++. Such an approach would improve the expressiveness for knowledge representation (especially for structural analysis and design applications), provide ability to build very large and practical expert systems, and provide an efficient way for storing knowledge. Functional specifications for the expert systems were then developed. The ORL/AI shell was then used to develop a variety of modules of expert systems for a variety of modeling, finite element analysis, and design optimization tasks in the integrated aerospace structural design process. These expert systems were developed to work in conjunction with procedural finite element structural analysis and design optimization modules (developed in-house at SAT, Inc.). The complete software, AutoDesign, so developed, can be used for integrated 'intelligent' structural analysis and design optimization. The software was beta-tested at a variety of companies, used by a range of engineers with different levels of background and expertise. Based on the feedback obtained by such users, conclusions were developed and are provided.

Reliable numerical computation in an optimal output-feedback design

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1991-01-01

A reliable algorithm is presented for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters. The algorithm is a part of a design algorithm for optimal linear dynamic output-feedback controller that minimizes a finite-time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control-law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed-loop eigensystem. This approach through the use of an accurate Pade series approximation does not require the closed-loop system matrix to be diagonalizable. The algorithm was included in a control design package for optimal robust low-order controllers. Usefulness of the proposed numerical algorithm was demonstrated using numerous practical design cases where degeneracies occur frequently in the closed-loop system under an arbitrary controller design initialization and during the numerical search.

Efficient sensitivity analysis and optimization of a helicopter rotor

NASA Technical Reports Server (NTRS)

Lim, Joon W.; Chopra, Inderjit

1989-01-01

Aeroelastic optimization of a system essentially consists of the determination of the optimum values of design variables which minimize the objective function and satisfy certain aeroelastic and geometric constraints. The process of aeroelastic optimization analysis is illustrated. To carry out aeroelastic optimization effectively, one needs a reliable analysis procedure to determine steady response and stability of a rotor system in forward flight. The rotor dynamic analysis used in the present study developed inhouse at the University of Maryland is based on finite elements in space and time. The analysis consists of two major phases: vehicle trim and rotor steady response (coupled trim analysis), and aeroelastic stability of the blade. For a reduction of helicopter vibration, the optimization process requires the sensitivity derivatives of the objective function and aeroelastic stability constraints. For this, the derivatives of steady response, hub loads and blade stability roots are calculated using a direct analytical approach. An automated optimization procedure is developed by coupling the rotor dynamic analysis, design sensitivity analysis and constrained optimization code CONMIN.

Optimization of deformation monitoring networks using finite element strain analysis

NASA Astrophysics Data System (ADS)

Alizadeh-Khameneh, M. Amin; Eshagh, Mehdi; Jensen, Anna B. O.

2018-04-01

An optimal design of a geodetic network can fulfill the requested precision and reliability of the network, and decrease the expenses of its execution by removing unnecessary observations. The role of an optimal design is highlighted in deformation monitoring network due to the repeatability of these networks. The core design problem is how to define precision and reliability criteria. This paper proposes a solution, where the precision criterion is defined based on the precision of deformation parameters, i. e. precision of strain and differential rotations. A strain analysis can be performed to obtain some information about the possible deformation of a deformable object. In this study, we split an area into a number of three-dimensional finite elements with the help of the Delaunay triangulation and performed the strain analysis on each element. According to the obtained precision of deformation parameters in each element, the precision criterion of displacement detection at each network point is then determined. The developed criterion is implemented to optimize the observations from the Global Positioning System (GPS) in Skåne monitoring network in Sweden. The network was established in 1989 and straddled the Tornquist zone, which is one of the most active faults in southern Sweden. The numerical results show that 17 out of all 21 possible GPS baseline observations are sufficient to detect minimum 3 mm displacement at each network point.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks.

PubMed

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-04-19

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs. However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%.

Cross Layer Design for Optimizing Transmission Reliability, Energy Efficiency, and Lifetime in Body Sensor Networks

PubMed Central

Chen, Xi; Xu, Yixuan; Liu, Anfeng

2017-01-01

High transmission reliability, energy efficiency, and long lifetime are pivotal issues for wireless body area networks (WBANs). However, these performance metrics are not independent of each other, making it hard to obtain overall improvements through optimizing one single aspect. Therefore, a Cross Layer Design Optimal (CLDO) scheme is proposed to simultaneously optimize transmission reliability, energy efficiency, and lifetime of WBANs from several layers. Firstly, due to the fact that the transmission power of nodes directly influences the reliability of links, the optimized transmission power of different nodes is deduced, which is able to maximize energy efficiency in theory under the premise that requirements on delay and jitter are fulfilled. Secondly, a relay decision algorithm is proposed to choose optimized relay nodes. Using this algorithm, nodes will choose relay nodes that ensure a balance of network energy consumption, provided that all nodes transmit with optimized transmission power and the same packet size. Thirdly, the energy consumption of nodes is still unbalanced even with optimized transmission power because of their different locations in the topology of the network. In addition, packet size also has an impact on final performance metrics. Therefore, a synthesized cross layer method for optimization is proposed. With this method, the transmission power of nodes with more residual energy will be enhanced while suitable packet size is determined for different links in the network, leading to further improvements in the WBAN system. Both our comprehensive theoretical analysis and experimental results indicate that the performance of our proposed scheme is better than reported in previous studies. Relative to the relay selection and power control game (RSPCG) scheme, the CLDO scheme can enhance transmission reliability by more than 44.6% and prolong the lifetime by as much as 33.2%. PMID:28422062

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.

PubMed

Van Derlinden, E; Bernaerts, K; Van Impe, J F

2010-05-21

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Turbine Performance Optimization Task Status

NASA Technical Reports Server (NTRS)

Griffin, Lisa W.; Turner, James E. (Technical Monitor)

2001-01-01

Capability to optimize for turbine performance and accurately predict unsteady loads will allow for increased reliability, Isp, and thrust-to-weight. The development of a fast, accurate aerodynamic design, analysis, and optimization system is required.

Design optimization using adjoint of Long-time LES for the trailing edge of a transonic turbine vane

NASA Astrophysics Data System (ADS)

Talnikar, Chaitanya; Wang, Qiqi

2017-11-01

Adjoint-based design optimization methods have been applied to low-fidelity simulation methods like Reynolds Averaged Navier-Stokes (RANS) and are useful for designing fluid machinery components. But to reliably capture the complex flow phenomena involved in turbomachinery, high fidelity simulations like large eddy simulation (LES) are required. Unfortunately due to the chaotic dynamics of turbulence, the unsteady adjoint method for LES diverges and produces incorrect gradients. Using a viscosity stabilized unsteady adjoint method developed for LES, the gradient can be obtained with reasonable accuracy. In this paper, design of the trailing edge of a gas turbine inlet guide vane is performed with the objective to reduce stagnation pressure loss and heat transfer over the surface of the vane. Slight changes in the shape of trailing edge can significantly impact these quantities by altering the boundary layer development process and separation points. The trailing edge is parameterized using a linear combination of 5 convex designs. Bayesian optimization is used as a global optimizer with the objective function evaluated from the LES and gradients obtained using the viscosity adjoint method. Results from the optimization, performed on the supercomputer Mira, are presented.

Layout designs of surface barrier coatings for boosting the capability of oxygen/vapor obstruction utilized in flexible electronics

NASA Astrophysics Data System (ADS)

Lee, Chang-Chun; Huang, Pei-Chen; He, Jing-Yan

2018-04-01

Organic light-emitting diode-based flexible and rollable displays have become a promising candidate for next-generation flexible electronics. For this reason, the design of surface multi-layered barriers should be optimized to enhance the long-term mechanical reliability of a flexible encapsulation that prevents the penetration of oxygen and vapor. In this study, finite element-based stress simulation was proposed to estimate the mechanical reliability of gas/vapor barrier design with low-k/silicon nitride (low-k/SiNx) stacking architecture. Consequently, stress-induced failure of critical thin films within the flexible display under various bending conditions must be considered. The feasibility of one pair SiO2/SiNx barrier design, which overcomes the complex lamination process, and the critical bending radius, which is decreased to 1.22 mm, were also examined. In addition, the influence of distance between neutral axes to the concerned layer surface dominated the induced-stress magnitude rather than the stress compliant mechanism provided from stacked low-k films.

Approaching the design of a failsafe turbine monitor with simple microcontroller blocks

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

Zapolin, R.E.

1995-12-31

The proper approach to early instrumentation design for tasks like failsafe turbine monitoring permits meeting requirements without resorting to traditional complex special-purpose electronics. Instead a small network of basic microcontroller building blocks can split the effort with each block optimized for its portion of the overall system. This paper discusses approaching design by partitioning intricate system specifications to permit each block to be optimized to the safety level appropriate for its portion of the overall task while retaining and production and reliability advantages of having common simple modules. It illustrates that approach with a modular microcontroller-based speed monitor which metmore » user needs for the latest in power plant monitoring equipment.« less

Ceramic Integration Technologies for Energy and Aerospace Applications

NASA Technical Reports Server (NTRS)

Singh, Mrityunjay; Asthana, Ralph N.

2007-01-01

Robust and affordable integration technologies for advanced ceramics are required to improve the performance, reliability, efficiency, and durability of components, devices, and systems based on them in a wide variety of energy, aerospace, and environmental applications. Many thermochemical and thermomechanical factors including joint design, analysis, and optimization must be considered in integration of similar and dissimilar material systems.

SensoTube: A Scalable Hardware Design Architecture for Wireless Sensors and Actuators Networks Nodes in the Agricultural Domain

PubMed Central

Piromalis, Dimitrios; Arvanitis, Konstantinos

2016-01-01

Wireless Sensor and Actuators Networks (WSANs) constitute one of the most challenging technologies with tremendous socio-economic impact for the next decade. Functionally and energy optimized hardware systems and development tools maybe is the most critical facet of this technology for the achievement of such prospects. Especially, in the area of agriculture, where the hostile operating environment comes to add to the general technological and technical issues, reliable and robust WSAN systems are mandatory. This paper focuses on the hardware design architectures of the WSANs for real-world agricultural applications. It presents the available alternatives in hardware design and identifies their difficulties and problems for real-life implementations. The paper introduces SensoTube, a new WSAN hardware architecture, which is proposed as a solution to the various existing design constraints of WSANs. The establishment of the proposed architecture is based, firstly on an abstraction approach in the functional requirements context, and secondly, on the standardization of the subsystems connectivity, in order to allow for an open, expandable, flexible, reconfigurable, energy optimized, reliable and robust hardware system. The SensoTube implementation reference model together with its encapsulation design and installation are analyzed and presented in details. Furthermore, as a proof of concept, certain use cases have been studied in order to demonstrate the benefits of migrating existing designs based on the available open-source hardware platforms to SensoTube architecture. PMID:27527180

Robust Design Optimization via Failure Domain Bounding

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2007-01-01

This paper extends and applies the strategies recently developed by the authors for handling constraints under uncertainty to robust design optimization. For the scope of this paper, robust optimization is a methodology aimed at problems for which some parameters are uncertain and are only known to belong to some uncertainty set. This set can be described by either a deterministic or a probabilistic model. In the methodology developed herein, optimization-based strategies are used to bound the constraint violation region using hyper-spheres and hyper-rectangles. By comparing the resulting bounding sets with any given uncertainty model, it can be determined whether the constraints are satisfied for all members of the uncertainty model (i.e., constraints are feasible) or not (i.e., constraints are infeasible). If constraints are infeasible and a probabilistic uncertainty model is available, upper bounds to the probability of constraint violation can be efficiently calculated. The tools developed enable approximating not only the set of designs that make the constraints feasible but also, when required, the set of designs for which the probability of constraint violation is below a prescribed admissible value. When constraint feasibility is possible, several design criteria can be used to shape the uncertainty model of performance metrics of interest. Worst-case, least-second-moment, and reliability-based design criteria are considered herein. Since the problem formulation is generic and the tools derived only require standard optimization algorithms for their implementation, these strategies are easily applicable to a broad range of engineering problems.

Multi-objective design optimization of antenna structures using sequential domain patching with automated patch size determination

NASA Astrophysics Data System (ADS)

Koziel, Slawomir; Bekasiewicz, Adrian

2018-02-01

In this article, a simple yet efficient and reliable technique for fully automated multi-objective design optimization of antenna structures using sequential domain patching (SDP) is discussed. The optimization procedure according to SDP is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between considered conflicting objectives, and (ii) Pareto set refinement for yielding the optimal designs at the high-fidelity electromagnetic (EM) simulation model level. For the sake of computational efficiency, the first step is realized at the level of a low-fidelity (coarse-discretization) EM model by sequential construction and relocation of small design space segments (patches) in order to create a path connecting the extreme Pareto front designs obtained beforehand. The second stage involves response correction techniques and local response surface approximation models constructed by reusing EM simulation data acquired in the first step. A major contribution of this work is an automated procedure for determining the patch dimensions. It allows for appropriate selection of the number of patches for each geometry variable so as to ensure reliability of the optimization process while maintaining its low cost. The importance of this procedure is demonstrated by comparing it with uniform patch dimensions.

Optimization of marine waste based-growth media for microbial lipase production using mixture design methodology.

PubMed

Sellami, Mohamed; Kedachi, Samiha; Frikha, Fakher; Miled, Nabil; Ben Rebah, Faouzi

2013-01-01

Lipase production by Staphylococcus xylosus and Rhizopus oryzae was investigated using a culture medium based on a mixture of synthetic medium and supernatants generated from tuna by-products and Ulva rigida biomass. The proportion of the three medium components was optimized using the simplex-centroid mixture design method (SCMD). Results indicated that the experimental data were in good agreement with predicted values, indicating that SCMD was a reliable method for determining the optimum mixture proportion of the growth medium. Maximal lipase activities of 12.5 and 23.5 IU/mL were obtained with a 50:50 (v:v) mixture of synthetic medium and tuna by-product supernatant for Staphylococcus xylosus and Rhizopus oryzae, respectively. The predicted responses from these mixture proportions were also validated experimentally.

Automating Structural Analysis of Spacecraft Vehicles

NASA Technical Reports Server (NTRS)

Hrinda, Glenn A.

2004-01-01

A major effort within NASA's vehicle analysis discipline has been to automate structural analysis and sizing optimization during conceptual design studies of advanced spacecraft. Traditional spacecraft structural sizing has involved detailed finite element analysis (FEA) requiring large degree-of-freedom (DOF) finite element models (FEM). Creation and analysis of these models can be time consuming and limit model size during conceptual designs. The goal is to find an optimal design that meets the mission requirements but produces the lightest structure. A structural sizing tool called HyperSizer has been successfully used in the conceptual design phase of a reusable launch vehicle and planetary exploration spacecraft. The program couples with FEA to enable system level performance assessments and weight predictions including design optimization of material selections and sizing of spacecraft members. The software's analysis capabilities are based on established aerospace structural methods for strength, stability and stiffness that produce adequately sized members and reliable structural weight estimates. The software also helps to identify potential structural deficiencies early in the conceptual design so changes can be made without wasted time. HyperSizer's automated analysis and sizing optimization increases productivity and brings standardization to a systems study. These benefits will be illustrated in examining two different types of conceptual spacecraft designed using the software. A hypersonic air breathing, single stage to orbit (SSTO), reusable launch vehicle (RLV) will be highlighted as well as an aeroshell for a planetary exploration vehicle used for aerocapture at Mars. By showing the two different types of vehicles, the software's flexibility will be demonstrated with an emphasis on reducing aeroshell structural weight. Member sizes, concepts and material selections will be discussed as well as analysis methods used in optimizing the structure. Analysis based on the HyperSizer structural sizing software will be discussed. Design trades required to optimize structural weight will be presented.

Microgrid Design Toolkit (MDT) Technical Documentation and Component Summaries

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

Arguello, Bryan; Gearhart, Jared Lee; Jones, Katherine A.

2015-09-01

The Microgrid Design Toolkit (MDT) is a decision support software tool for microgrid designers to use during the microgrid design process. The models that support the two main capabilities in MDT are described. The first capability, the Microgrid Sizing Capability (MSC), is used to determine the size and composition of a new microgrid in the early stages of the design process. MSC is a mixed-integer linear program that is focused on developing a microgrid that is economically viable when connected to the grid. The second capability is focused on refining a microgrid design for operation in islanded mode. This secondmore » capability relies on two models: the Technology Management Optimization (TMO) model and Performance Reliability Model (PRM). TMO uses a genetic algorithm to create and refine a collection of candidate microgrid designs. It uses PRM, a simulation based reliability model, to assess the performance of these designs. TMO produces a collection of microgrid designs that perform well with respect to one or more performance metrics.« less

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Grabbe, Shon; Mukherjee, Avijit

2010-01-01

The optimization of traffic flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and efficiency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air traffic constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

Power system modeling and optimization methods vis-a-vis integrated resource planning (IRP)

NASA Astrophysics Data System (ADS)

Arsali, Mohammad H.

1998-12-01

The state-of-the-art restructuring of power industries is changing the fundamental nature of retail electricity business. As a result, the so-called Integrated Resource Planning (IRP) strategies implemented on electric utilities are also undergoing modifications. Such modifications evolve from the imminent considerations to minimize the revenue requirements and maximize electrical system reliability vis-a-vis capacity-additions (viewed as potential investments). IRP modifications also provide service-design bases to meet the customer needs towards profitability. The purpose of this research as deliberated in this dissertation is to propose procedures for optimal IRP intended to expand generation facilities of a power system over a stretched period of time. Relevant topics addressed in this research towards IRP optimization are as follows: (1) Historical prospective and evolutionary aspects of power system production-costing models and optimization techniques; (2) A survey of major U.S. electric utilities adopting IRP under changing socioeconomic environment; (3) A new technique designated as the Segmentation Method for production-costing via IRP optimization; (4) Construction of a fuzzy relational database of a typical electric power utility system for IRP purposes; (5) A genetic algorithm based approach for IRP optimization using the fuzzy relational database.

Cost optimization in low volume VLSI circuits

NASA Technical Reports Server (NTRS)

Cook, K. B., Jr.; Kerns, D. V., Jr.

1982-01-01

The relationship of integrated circuit (IC) cost to electronic system cost is developed using models for integrated circuit cost which are based on design/fabrication approach. Emphasis is on understanding the relationship between cost and volume for custom circuits suitable for NASA applications. In this report, reliability is a major consideration in the models developed. Results are given for several typical IC designs using off the shelf, full custom, and semicustom IC's with single and double level metallization.

Simulative design in macroscale for prospective application to micro-catheters.

PubMed

Ha, Cheol Woo

2018-02-09

In this paper, a motion-transforming element is applied to the development of a new catheter device. The motion-transforming element structure allows a reduction of linear movement and converts linear movement to rotational movement. The simulative design of micro-catheters is based on a proposed structure called the Operating Mini Station (OMS). OMS is operated by movement of a motion-transforming element. A new motion-transforming element is designed using multiple links that are connected by hinged joints based on an elastic design. The design of the links and the hinges are optimized for precise and reliable movement of the motion-transforming element. Because of the elastic design, it is possible to realize a catheter that allows various movements in small spaces like capillaries.

Hybrid computational and experimental approach for the study and optimization of mechanical components

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1998-05-01

Increased demands on the performance and efficiency of mechanical components impose challenges on their engineering design and optimization, especially when new and more demanding applications must be developed in relatively short periods of time while satisfying design objectives, as well as cost and manufacturability. In addition, reliability and durability must be taken into consideration. As a consequence, effective quantitative methodologies, computational and experimental, should be applied in the study and optimization of mechanical components. Computational investigations enable parametric studies and the determination of critical engineering design conditions, while experimental investigations, especially those using optical techniques, provide qualitative and quantitative information on the actual response of the structure of interest to the applied load and boundary conditions. We discuss a hybrid experimental and computational approach for investigation and optimization of mechanical components. The approach is based on analytical, computational, and experimental resolutions methodologies in the form of computational, noninvasive optical techniques, and fringe prediction analysis tools. Practical application of the hybrid approach is illustrated with representative examples that demonstrate the viability of the approach as an effective engineering tool for analysis and optimization.

Cascade Optimization Strategy for Aircraft and Air-Breathing Propulsion System Concepts

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Lavelle, Thomas M.; Hopkins, Dale A.; Coroneos, Rula M.

1996-01-01

Design optimization for subsonic and supersonic aircraft and for air-breathing propulsion engine concepts has been accomplished by soft-coupling the Flight Optimization System (FLOPS) and the NASA Engine Performance Program analyzer (NEPP), to the NASA Lewis multidisciplinary optimization tool COMETBOARDS. Aircraft and engine design problems, with their associated constraints and design variables, were cast as nonlinear optimization problems with aircraft weight and engine thrust as the respective merit functions. Because of the diversity of constraint types and the overall distortion of the design space, the most reliable single optimization algorithm available in COMETBOARDS could not produce a satisfactory feasible optimum solution. Some of COMETBOARDS' unique features, which include a cascade strategy, variable and constraint formulations, and scaling devised especially for difficult multidisciplinary applications, successfully optimized the performance of both aircraft and engines. The cascade method has two principal steps: In the first, the solution initiates from a user-specified design and optimizer, in the second, the optimum design obtained in the first step with some random perturbation is used to begin the next specified optimizer. The second step is repeated for a specified sequence of optimizers or until a successful solution of the problem is achieved. A successful solution should satisfy the specified convergence criteria and have several active constraints but no violated constraints. The cascade strategy available in the combined COMETBOARDS, FLOPS, and NEPP design tool converges to the same global optimum solution even when it starts from different design points. This reliable and robust design tool eliminates manual intervention in the design of aircraft and of air-breathing propulsion engines where it eases the cycle analysis procedures. The combined code is also much easier to use, which is an added benefit. This paper describes COMETBOARDS and its cascade strategy and illustrates the capability of the combined design tool through the optimization of a subsonic aircraft and a high-bypass-turbofan wave-rotor-topped engine.

Multiple objective optimization in reliability demonstration test

DOE PAGES

Lu, Lu; Anderson-Cook, Christine Michaela; Li, Mingyang

2016-10-01

Reliability demonstration tests are usually performed in product design or validation processes to demonstrate whether a product meets specified requirements on reliability. For binomial demonstration tests, the zero-failure test has been most commonly used due to its simplicity and use of minimum sample size to achieve an acceptable consumer’s risk level. However, this test can often result in unacceptably high risk for producers as well as a low probability of passing the test even when the product has good reliability. This paper explicitly explores the interrelationship between multiple objectives that are commonly of interest when planning a demonstration test andmore » proposes structured decision-making procedures using a Pareto front approach for selecting an optimal test plan based on simultaneously balancing multiple criteria. Different strategies are suggested for scenarios with different user priorities and graphical tools are developed to help quantify the trade-offs between choices and to facilitate informed decision making. As a result, potential impacts of some subjective user inputs on the final decision are studied to offer insights and useful guidance for general applications.« less

Genome-wide characterization and selection of expressed sequence tag simple sequence repeat primers for optimized marker distribution and reliability in peach

USDA-ARS?s Scientific Manuscript database

Expressed sequence tag (EST) simple sequence repeats (SSRs) in Prunus were mined, and flanking primers designed and used for genome-wide characterization and selection of primers to optimize marker distribution and reliability. A total of 12,618 contigs were assembled from 84,727 ESTs, along with 34...

A Unified Statistical Rain-Attenuation Model for Communication Link Fade Predictions and Optimal Stochastic Fade Control Design Using a Location-Dependent Rain-Statistic Database

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1990-01-01

A static and dynamic rain-attenuation model is presented which describes the statistics of attenuation on an arbitrarily specified satellite link for any location for which there are long-term rainfall statistics. The model may be used in the design of the optimal stochastic control algorithms to mitigate the effects of attenuation and maintain link reliability. A rain-statistics data base is compiled, which makes it possible to apply the model to any location in the continental U.S. with a resolution of 0-5 degrees in latitude and longitude. The model predictions are compared with experimental observations, showing good agreement.

Reliability considerations in long-life outer planet spacecraft system design

NASA Technical Reports Server (NTRS)

Casani, E. K.

1975-01-01

A Mariner Jupiter/Saturn mission has been planned for 1977. System reliability questions are discussed, taking into account the actual and design lifetime, causes of mission termination, in-flight failures and their consequences for the mission, and the use of redundancy to avoid failures. The design process employed optimizes the use of proven subsystem and system designs and then makes the necessary improvements to increase the lifetime as required.

Empirical Recommendations for Improving the Stability of the Dot-Probe Task in Clinical Research

PubMed Central

Price, Rebecca B.; Kuckertz, Jennie M.; Siegle, Greg J.; Ladouceur, Cecile D.; Silk, Jennifer S.; Ryan, Neal D.; Dahl, Ronald E.; Amir, Nader

2014-01-01

The dot-probe task has been widely used in research to produce an index of biased attention based on reaction times (RTs). Despite its popularity, very few published studies have examined psychometric properties of the task, including test-retest reliability, and no previous study has examined reliability in clinically anxious samples or systematically explored the effects of task design and analysis decisions on reliability. In the current analysis, we utilized dot-probe data from three studies where attention bias towards threat-related faces was assessed at multiple (≥5) timepoints. Two of the studies were similar (adults with Social Anxiety Disorder, similar design features) while one was much more disparate (pediatric healthy volunteers, distinct task design). We explored the effects of analysis choices (e.g., bias score calculation formula, methods for outlier handling) on reliability and searched for convergence of findings across the three studies. We found that, when considering the three studies concurrently, the most reliable RT bias index utilized data from dot-bottom trials, comparing congruent to incongruent trials, with rescaled outliers, particularly after averaging across more than one assessment point. Although reliability of RT bias indices was moderate to low under most circumstances, within-session variability in bias (attention bias variability; ABV), a recently proposed RT index, was more reliable across sessions. Several eyetracking-based indices of attention bias (available in the pediatric healthy sample only) showed reliability that matched the optimal RT index (ABV). On the basis of these findings, we make specific recommendations to researchers using the dot probe, particularly those wishing to investigate individual differences and/or single-patient applications. PMID:25419646

Interval estimation and optimal design for the within-subject coefficient of variation for continuous and binary variables

PubMed Central

Shoukri, Mohamed M; Elkum, Nasser; Walter, Stephen D

2006-01-01

Background In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval construction within the framework of a one-way random effects model. We investigate sample size requirements for the within-subject coefficient of variation for continuous and binary variables. Methods We investigate the validity of the approximate normal confidence interval by Monte Carlo simulations. In designing a reliability study, a crucial issue is the balance between the number of subjects to be recruited and the number of repeated measurements per subject. We discuss efficiency of estimation and cost considerations for the optimal allocation of the sample resources. The approach is illustrated by an example on Magnetic Resonance Imaging (MRI). We also discuss the issue of sample size estimation for dichotomous responses with two examples. Results For the continuous variable we found that the variance stabilizing transformation improves the asymptotic coverage probabilities on the within-subject coefficient of variation for the continuous variable. The maximum like estimation and sample size estimation based on pre-specified width of confidence interval are novel contribution to the literature for the binary variable. Conclusion Using the sample size formulas, we hope to help clinical epidemiologists and practicing statisticians to efficiently design reliability studies using the within-subject coefficient of variation, whether the variable of interest is continuous or binary. PMID:16686943

A Practical Solution to Optimizing the Reliability of Teaching Observation Measures under Budget Constraints

ERIC Educational Resources Information Center

Meyer, J. Patrick; Liu, Xiang; Mashburn, Andrew J.

2014-01-01

Researchers often use generalizability theory to estimate relative error variance and reliability in teaching observation measures. They also use it to plan future studies and design the best possible measurement procedures. However, designing the best possible measurement procedure comes at a cost, and researchers must stay within their budget…

Topology and boundary shape optimization as an integrated design tool

NASA Technical Reports Server (NTRS)

Bendsoe, Martin Philip; Rodrigues, Helder Carrico

1990-01-01

The optimal topology of a two dimensional linear elastic body can be computed by regarding the body as a domain of the plane with a high density of material. Such an optimal topology can then be used as the basis for a shape optimization method that computes the optimal form of the boundary curves of the body. This results in an efficient and reliable design tool, which can be implemented via common FEM mesh generator and CAD type input-output facilities.

An optimization design for evacuation planning based on fuzzy credibility theory and genetic algorithm

NASA Astrophysics Data System (ADS)

Zhang, D.; Zhang, W. Y.

2017-08-01

Evacuation planning is an important activity in disaster management. It has to be planned in advance due to the unpredictable occurrence of disasters. It is necessary that the evacuation plans are as close as possible to the real evacuation work. However, the evacuation plan is extremely challenging because of the inherent uncertainty of the required information. There is a kind of vehicle routing problem based on the public traffic evacuation. In this paper, the demand for each evacuation set point is a fuzzy number, and each routing selection of the point is based on the fuzzy credibility preference index. This paper proposes an approximate optimal solution for this problem by the genetic algorithm based on the fuzzy reliability theory. Finally, the algorithm is applied to an optimization model, and the experiment result shows that the algorithm is effective.

A novel optimal configuration form redundant MEMS inertial sensors based on the orthogonal rotation method.

PubMed

Cheng, Jianhua; Dong, Jinlu; Landry, Rene; Chen, Daidai

2014-07-29

In order to improve the accuracy and reliability of micro-electro mechanical systems (MEMS) navigation systems, an orthogonal rotation method-based nine-gyro redundant MEMS configuration is presented. By analyzing the accuracy and reliability characteristics of an inertial navigation system (INS), criteria for redundant configuration design are introduced. Then the orthogonal rotation configuration is formed through a two-rotation of a set of orthogonal inertial sensors around a space vector. A feasible installation method is given for the real engineering realization of this proposed configuration. The performances of the novel configuration and another six configurations are comprehensively compared and analyzed. Simulation and experimentation are also conducted, and the results show that the orthogonal rotation configuration has the best reliability, accuracy and fault detection and isolation (FDI) performance when the number of gyros is nine.

Design technique for all-dielectric non-polarizing beam splitter plate

NASA Astrophysics Data System (ADS)

Rizea, A.

2012-03-01

There are many situations when, for the proper working, an opto-electronic device requiring optical components does not change the polarization state of light after a reflection, splitting or filtering. In this paper, a design for a non-polarizing beam splitter plate is proposed. Based on certain optical properties of homogeneous dielectric materials we will establish a reliable thin film package formula, excellent for the start of optimization to obtain a 20-nm bandwidth non-polarizing beam splitter.

Optimal hydraulic design of new-type shaft tubular pumping system

NASA Astrophysics Data System (ADS)

Zhu, H. G.; Zhang, R. T.; Zhou, J. R.

2012-11-01

Based on the characteristics of large flow rate, low-head, short annual operation time and high reliability of city flood-control pumping stations, a new-type shaft tubular pumping system featuring shaft suction box, siphon-type discharge passage with vacuum breaker as cutoff device was put forward, which possesses such advantages as simpler structure, reliable cutoff and higher energy performance. According to the design parameters of a city flood control pumping station, a numerical computation model was set up including shaft-type suction box, siphon-type discharge passage, pump impeller and guide vanes. By using commercial CFD software Fluent, RNG κ-epsilon turbulence model was adopted to close the three-dimensional time-averaged incompressible N-S equations. After completing optimal hydraulic design of shaft-type suction box, and keeping the parameters of total length, maximum width and outlet section unchanged, siphon-type discharge passages of three hump locations and three hump heights were designed and numerical analysis on the 9 hydraulic design schemes of pumping system were proceeded. The computational results show that the changing of hump locations and hump heights directly affects the internal flow patterns of discharge passages and hydraulic performances of the system, and when hump is located 3.66D from the inlet section and hump height is about 0.65D (D is the diameter of pump impeller), the new-type shaft tubular pumping system achieves better energy performances. A pumping system model test of the optimal designed scheme was carried out. The result shows that the highest pumping system efficiency reaches 75.96%, and when at design head of 1.15m the flow rate and system efficiency were 0.304m3/s and 63.10%, respectively. Thus, the validity of optimal design method was verified by the model test, and a solid foundation was laid for the application and extension of the new-type shaft tubular pumping system.

Methodology for safety optimization of highway cross-sections for horizontal curves with restricted sight distance.

PubMed

Ibrahim, Shewkar E; Sayed, Tarek; Ismail, Karim

2012-11-01

Several earlier studies have noted the shortcomings with existing geometric design guides which provide deterministic standards. In these standards the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from the standards. To mitigate these shortcomings, probabilistic geometric design has been advocated where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a mechanism for risk measurement to evaluate the safety impact of deviations from design standards. This paper applies reliability analysis for optimizing the safety of highway cross-sections. The paper presents an original methodology to select a suitable combination of cross-section elements with restricted sight distance to result in reduced collisions and consistent risk levels. The purpose of this optimization method is to provide designers with a proactive approach to the design of cross-section elements in order to (i) minimize the risk associated with restricted sight distance, (ii) balance the risk across the two carriageways of the highway, and (iii) reduce the expected collision frequency. A case study involving nine cross-sections that are parts of two major highway developments in British Columbia, Canada, was presented. The results showed that an additional reduction in collisions can be realized by incorporating the reliability component, P(nc) (denoting the probability of non-compliance), in the optimization process. The proposed approach results in reduced and consistent risk levels for both travel directions in addition to further collision reductions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bulk Data Dissemination in Low Power Sensor Networks: Present and Future Directions

PubMed Central

Xu, Zhirong; Hu, Tianlei; Song, Qianshu

2017-01-01

Wireless sensor network-based (WSN-based) applications need an efficient and reliable data dissemination service to facilitate maintenance, management and data distribution tasks. As WSNs nowadays are becoming pervasive and data intensive, bulk data dissemination protocols have been extensively studied recently. This paper provides a comprehensive survey of the state-of-the-art bulk data dissemination protocols. The large number of papers available in the literature propose various techniques to optimize the dissemination protocols. Different from the existing survey works which separately explores the building blocks of dissemination, our work categorizes the literature according to the optimization purposes: Reliability, Scalability and Transmission/Energy efficiency. By summarizing and reviewing the key insights and techniques, we further discuss on the future directions for each category. Our survey helps unveil three key findings for future direction: (1) The recent advances in wireless communications (e.g., study on cross-technology interference, error estimating codes, constructive interference, capture effect) can be potentially exploited to support further optimization on the reliability and energy efficiency of dissemination protocols; (2) Dissemination in multi-channel, multi-task and opportunistic networks requires more efforts to fully exploit the spatial-temporal network resources to enhance the data propagation; (3) Since many designs incur changes on MAC layer protocols, the co-existence of dissemination with other network protocols is another problem left to be addressed. PMID:28098830

Genetic Algorithm Optimization of a Cost Competitive Hybrid Rocket Booster

NASA Technical Reports Server (NTRS)

Story, George

2015-01-01

Performance, reliability and cost have always been drivers in the rocket business. Hybrid rockets have been late entries into the launch business due to substantial early development work on liquid rockets and solid rockets. Slowly the technology readiness level of hybrids has been increasing due to various large scale testing and flight tests of hybrid rockets. One remaining issue is the cost of hybrids versus the existing launch propulsion systems. This paper will review the known state-of-the-art hybrid development work to date and incorporate it into a genetic algorithm to optimize the configuration based on various parameters. A cost module will be incorporated to the code based on the weights of the components. The design will be optimized on meeting the performance requirements at the lowest cost.

Genetic Algorithm Optimization of a Cost Competitive Hybrid Rocket Booster

NASA Technical Reports Server (NTRS)

Story, George

2014-01-01

Performance, reliability and cost have always been drivers in the rocket business. Hybrid rockets have been late entries into the launch business due to substantial early development work on liquid rockets and later on solid rockets. Slowly the technology readiness level of hybrids has been increasing due to various large scale testing and flight tests of hybrid rockets. A remaining issue is the cost of hybrids vs the existing launch propulsion systems. This paper will review the known state of the art hybrid development work to date and incorporate it into a genetic algorithm to optimize the configuration based on various parameters. A cost module will be incorporated to the code based on the weights of the components. The design will be optimized on meeting the performance requirements at the lowest cost.

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

DOE PAGES

Pan, Wenxiao; Yang, Xiu; Bao, Jie; ...

2017-01-01

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed basedmore » on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.« less

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

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

Pan, Wenxiao; Yang, Xiu; Bao, Jie

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed basedmore » on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.« less

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system.

PubMed

Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel

2017-10-01

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

Optimizing preventive maintenance policy: A data-driven application for a light rail braking system

PubMed Central

Corman, Francesco; Kraijema, Sander; Godjevac, Milinko; Lodewijks, Gabriel

2017-01-01

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions. PMID:29278245

Study of fail-safe abort system for an actively cooled hypersonic aircraft, volume 2

NASA Technical Reports Server (NTRS)

Peeples, M. E.; Herring, R. L.

1976-01-01

Conceptual designs of a fail-safe abort system for hydrogen fueled actively cooled high speed aircraft are examined. The fail-safe concept depends on basically three factors: (1) a reliable method of detecting a failure or malfunction in the active cooling system, (2) the optimization of abort trajectories which minimize the descent heat load to the aircraft, and (3) fail-safe thermostructural concepts to minimize both the weight and the maximum temperature the structure will reach during descent. These factors are examined and promising approaches are evaluated based on weight, reliability, ease of manufacture and cost.

Design and control of the precise tracking bed based on complex electromechanical design theory

NASA Astrophysics Data System (ADS)

Ren, Changzhi; Liu, Zhao; Wu, Liao; Chen, Ken

2010-05-01

The precise tracking technology is wide used in astronomical instruments, satellite tracking and aeronautic test bed. However, the precise ultra low speed tracking drive system is one high integrated electromechanical system, which one complexly electromechanical design method is adopted to improve the efficiency, reliability and quality of the system during the design and manufacture circle. The precise Tracking Bed is one ultra-exact, ultra-low speed, high precision and huge inertial instrument, which some kind of mechanism and environment of the ultra low speed is different from general technology. This paper explores the design process based on complex electromechanical optimizing design theory, one non-PID with a CMAC forward feedback control method is used in the servo system of the precise tracking bed and some simulation results are discussed.

Optimization of life support systems and their systems reliability

NASA Technical Reports Server (NTRS)

Fan, L. T.; Hwang, C. L.; Erickson, L. E.

1971-01-01

The identification, analysis, and optimization of life support systems and subsystems have been investigated. For each system or subsystem that has been considered, the procedure involves the establishment of a set of system equations (or mathematical model) based on theory and experimental evidences; the analysis and simulation of the model; the optimization of the operation, control, and reliability; analysis of sensitivity of the system based on the model; and, if possible, experimental verification of the theoretical and computational results. Research activities include: (1) modeling of air flow in a confined space; (2) review of several different gas-liquid contactors utilizing centrifugal force: (3) review of carbon dioxide reduction contactors in space vehicles and other enclosed structures: (4) application of modern optimal control theory to environmental control of confined spaces; (5) optimal control of class of nonlinear diffusional distributed parameter systems: (6) optimization of system reliability of life support systems and sub-systems: (7) modeling, simulation and optimal control of the human thermal system: and (8) analysis and optimization of the water-vapor eletrolysis cell.

The Advanced Gamma-ray Imaging System (AGIS): Camera Electronics Designs

NASA Astrophysics Data System (ADS)

Tajima, H.; Buckley, J.; Byrum, K.; Drake, G.; Falcone, A.; Funk, S.; Holder, J.; Horan, D.; Krawczynski, H.; Ong, R.; Swordy, S.; Wagner, R.; Williams, D.

2008-04-01

AGIS, a next generation of atmospheric Cherenkov telescope arrays, aims to achieve a sensitivity level of a milliCrab for gamma-ray observations in the energy band of 40 GeV to 100 TeV. Such improvement requires cost reduction of individual components with high reliability in order to equip the order of 100 telescopes necessary to achieve the sensitivity goal. We are exploring several design concepts to reduce the cost of camera electronics while improving their performance. These design concepts include systems based on multi-channel waveform sampling ASIC optimized for AGIS, a system based on IIT (image intensifier tube) for large channel (order of 1 million channels) readout as well as a multiplexed FADC system based on the current VERITAS readout design. Here we present trade-off in the studies of these design concepts.

The Advanced Gamma-ray Imaging System (AGIS): Camera Electronics Designs

NASA Astrophysics Data System (ADS)

Tajima, Hiroyasu; Buckley, J.; Byrum, K.; Drake, G.; Falcone, A.; Funk, S.; Holder, J.; Horan, D.; Krawczynski, H.; Ong, R.; Swordy, S.; Wagner, R.; Wakely, S.; Williams, D.; Camera Electronics Working Group; AGIS Collaboration

2008-03-01

AGIS, a next generation of atmospheric Cherenkov telescope arrays, aims to achieve a sensitivity level of a milliCrab for gamma-ray observations in in the energy band of 40 GeV to 100 TeV. Such improvement requires cost reduction of individual components with high reliability in order to equip the order of 100 telescopes necessary to achieve the sensitivity goal. We are exploring several design concepts to reduce the cost of camera electronics while improving their performance. These design concepts include systems based on multi-channel waveform sampling ASIC optimized for AGIS, a system based on IIT (image intensifier tube) for large channel (order of 1 million channels) readout as well as a multiplexed FADC system based on the current VERITAS readout design. Here we present trade-off studies of these design concepts.

Sensor Selection and Optimization for Health Assessment of Aerospace Systems

NASA Technical Reports Server (NTRS)

Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

2007-01-01

Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service. These research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, dependable sensor suite to address system health assessment requirements.

Sensor Selection and Optimization for Health Assessment of Aerospace Systems

NASA Technical Reports Server (NTRS)

Maul, William A.; Kopasakis, George; Santi, Louis M.; Sowers, Thomas S.; Chicatelli, Amy

2008-01-01

Aerospace systems are developed similarly to other large-scale systems through a series of reviews, where designs are modified as system requirements are refined. For space-based systems few are built and placed into service these research vehicles have limited historical experience to draw from and formidable reliability and safety requirements, due to the remote and severe environment of space. Aeronautical systems have similar reliability and safety requirements, and while these systems may have historical information to access, commercial and military systems require longevity under a range of operational conditions and applied loads. Historically, the design of aerospace systems, particularly the selection of sensors, is based on the requirements for control and performance rather than on health assessment needs. Furthermore, the safety and reliability requirements are met through sensor suite augmentation in an ad hoc, heuristic manner, rather than any systematic approach. A review of the current sensor selection practice within and outside of the aerospace community was conducted and a sensor selection architecture is proposed that will provide a justifiable, defendable sensor suite to address system health assessment requirements.

Numerical aerodynamic simulation facility. Preliminary study extension

NASA Technical Reports Server (NTRS)

1978-01-01

The production of an optimized design of key elements of the candidate facility was the primary objective of this report. This was accomplished by effort in the following tasks: (1) to further develop, optimize and describe the function description of the custom hardware; (2) to delineate trade off areas between performance, reliability, availability, serviceability, and programmability; (3) to develop metrics and models for validation of the candidate systems performance; (4) to conduct a functional simulation of the system design; (5) to perform a reliability analysis of the system design; and (6) to develop the software specifications to include a user level high level programming language, a correspondence between the programming language and instruction set and outline the operation system requirements.

Enhancing healthcare process design with human factors engineering and reliability science, part 1: setting the context.

PubMed

Boston-Fleischhauer, Carol

2008-01-01

The design and implementation of efficient, effective, and safe processes are never-ending challenges in healthcare. Less than optimal performance levels and rising concerns about patient safety suggest that traditional process design methods are insufficient to meet design requirements. In this 2-part series, the author presents human factors engineering and reliability science as important knowledge to enhance existing operational and clinical process design methods in healthcare. An examination of these theories, application approaches, and examples are presented.

Taguchi Based Performance and Reliability Improvement of an Ion Chamber Amplifier for Enhanced Nuclear Reactor Safety

NASA Astrophysics Data System (ADS)

Kulkarni, R. D.; Agarwal, Vivek

2008-08-01

An ion chamber amplifier (ICA) is used as a safety device for neutronic power (flux) measurement in regulation and protection systems of nuclear reactors. Therefore, performance reliability of an ICA is an important issue. Appropriate quality engineering is essential to achieve a robust design and performance of the ICA circuit. It is observed that the low input bias current operational amplifiers used in the input stage of the ICA circuit are the most critical devices for proper functioning of the ICA. They are very sensitive to the gamma radiation present in their close vicinity. Therefore, the response of the ICA deteriorates with exposure to gamma radiation resulting in a decrease in the overall reliability, unless desired performance is ensured under all conditions. This paper presents a performance enhancement scheme for an ICA operated in the nuclear environment. The Taguchi method, which is a proven technique for reliability enhancement, has been used in this work. It is demonstrated that if a statistical, optimal design approach, like the Taguchi method is used, the cost of high quality and reliability may be brought down drastically. The complete methodology and statistical calculations involved are presented, as are the experimental and simulation results to arrive at a robust design of the ICA.

A Survey of Reliability, Maintainability, Supportability, and Testability Software Tools

DTIC Science & Technology

1991-04-01

designs in terms of their contributions toward forced mission termination and vehicle or function loss . Includes the ability to treat failure modes of...ABSTRACT: Inputs: MTBFs, MTTRs, support equipment costs, equipment weights and costs, available targets, military occupational specialty skill level and...US Army CECOM NAME: SPARECOST ABSTRACT: Calculates expected number of failures and performs spares holding optimization based on cost, weight , or

Analytical display design for flight tasks conducted under instrument meteorological conditions. [human factors engineering of pilot performance for display device design in instrument landing systems

NASA Technical Reports Server (NTRS)

Hess, R. A.

1976-01-01

Paramount to proper utilization of electronic displays is a method for determining pilot-centered display requirements. Display design should be viewed fundamentally as a guidance and control problem which has interactions with the designer's knowledge of human psychomotor activity. From this standpoint, reliable analytical models of human pilots as information processors and controllers can provide valuable insight into the display design process. A relatively straightforward, nearly algorithmic procedure for deriving model-based, pilot-centered display requirements was developed and is presented. The optimal or control theoretic pilot model serves as the backbone of the design methodology, which is specifically directed toward the synthesis of head-down, electronic, cockpit display formats. Some novel applications of the optimal pilot model are discussed. An analytical design example is offered which defines a format for the electronic display to be used in a UH-1H helicopter in a landing approach task involving longitudinal and lateral degrees of freedom.

Systematic optimization model and algorithm for binding sequence selection in computational enzyme design

PubMed Central

Huang, Xiaoqiang; Han, Kehang; Zhu, Yushan

2013-01-01

A systematic optimization model for binding sequence selection in computational enzyme design was developed based on the transition state theory of enzyme catalysis and graph-theoretical modeling. The saddle point on the free energy surface of the reaction system was represented by catalytic geometrical constraints, and the binding energy between the active site and transition state was minimized to reduce the activation energy barrier. The resulting hyperscale combinatorial optimization problem was tackled using a novel heuristic global optimization algorithm, which was inspired and tested by the protein core sequence selection problem. The sequence recapitulation tests on native active sites for two enzyme catalyzed hydrolytic reactions were applied to evaluate the predictive power of the design methodology. The results of the calculation show that most of the native binding sites can be successfully identified if the catalytic geometrical constraints and the structural motifs of the substrate are taken into account. Reliably predicting active site sequences may have significant implications for the creation of novel enzymes that are capable of catalyzing targeted chemical reactions. PMID:23649589

Robust optimization based energy dispatch in smart grids considering demand uncertainty

NASA Astrophysics Data System (ADS)

Nassourou, M.; Puig, V.; Blesa, J.

2017-01-01

In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands. The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in one-layer and two-layer approaches was carried out. The goal of this research is to design a controller based on Economic MPC strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.

Optimal experimental designs for the estimation of thermal properties of composite materials

NASA Technical Reports Server (NTRS)

Scott, Elaine P.; Moncman, Deborah A.

1994-01-01

Reliable estimation of thermal properties is extremely important in the utilization of new advanced materials, such as composite materials. The accuracy of these estimates can be increased if the experiments are designed carefully. The objectives of this study are to design optimal experiments to be used in the prediction of these thermal properties and to then utilize these designs in the development of an estimation procedure to determine the effective thermal properties (thermal conductivity and volumetric heat capacity). The experiments were optimized by choosing experimental parameters that maximize the temperature derivatives with respect to all of the unknown thermal properties. This procedure has the effect of minimizing the confidence intervals of the resulting thermal property estimates. Both one-dimensional and two-dimensional experimental designs were optimized. A heat flux boundary condition is required in both analyses for the simultaneous estimation of the thermal properties. For the one-dimensional experiment, the parameters optimized were the heating time of the applied heat flux, the temperature sensor location, and the experimental time. In addition to these parameters, the optimal location of the heat flux was also determined for the two-dimensional experiments. Utilizing the optimal one-dimensional experiment, the effective thermal conductivity perpendicular to the fibers and the effective volumetric heat capacity were then estimated for an IM7-Bismaleimide composite material. The estimation procedure used is based on the minimization of a least squares function which incorporates both calculated and measured temperatures and allows for the parameters to be estimated simultaneously.

Optimal design of the first stage of the plate-fin heat exchanger for the EAST cryogenic system

NASA Astrophysics Data System (ADS)

Qingfeng, JIANG; Zhigang, ZHU; Qiyong, ZHANG; Ming, ZHUANG; Xiaofei, LU

2018-03-01

The size of the heat exchanger is an important factor determining the dimensions of the cold box in helium cryogenic systems. In this paper, a counter-flow multi-stream plate-fin heat exchanger is optimized by means of a spatial interpolation method coupled with a hybrid genetic algorithm. Compared with empirical correlations, this spatial interpolation algorithm based on a kriging model can be adopted to more precisely predict the Colburn heat transfer factors and Fanning friction factors of offset-strip fins. Moreover, strict computational fluid dynamics simulations can be carried out to predict the heat transfer and friction performance in the absence of reliable experimental data. Within the constraints of heat exchange requirements, maximum allowable pressure drop, existing manufacturing techniques and structural strength, a mathematical model of an optimized design with discrete and continuous variables based on a hybrid genetic algorithm is established in order to minimize the volume. The results show that for the first-stage heat exchanger in the EAST refrigerator, the structural size could be decreased from the original 2.200 × 0.600 × 0.627 (m3) to the optimized 1.854 × 0.420 × 0.340 (m3), with a large reduction in volume. The current work demonstrates that the proposed method could be a useful tool to achieve optimization in an actual engineering project during the practical design process.

Beyond reliability to profitability

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

Bond, T.H.; Mitchell, J.S.

1996-07-01

Reliability concerns have controlled much of power generation design and operations. Emerging from a strictly regulated environment, profitability is becoming a much more important concept for today`s power generation executives. This paper discusses the conceptual advance-view power plant maintenance as a profit center, go beyond reliability, and embrace profitability. Profit Centered Maintenance begins with the premise that financial considerations, namely profitability, drive most aspects of modern process and manufacturing operations. Profit Centered Maintenance is a continuous process of reliability and administrative improvement and optimization. For the power generation executives with troublesome maintenance programs, Profit Centered Maintenance can be the blueprintmore » to increased profitability. It requires the culture change to make decisions based on value, to reengineer the administration of maintenance, and to enable the people performing and administering maintenance to make the most of available maintenance information technology. The key steps are to optimize the physical function of maintenance and to resolve recurring maintenance problems so that the need for maintenance can be reduced. Profit Centered Maintenance is more than just an attitude it is a path to profitability, be it resulting in increased profits or increased market share.« less

A sequential linear optimization approach for controller design

NASA Technical Reports Server (NTRS)

Horta, L. G.; Juang, J.-N.; Junkins, J. L.

1985-01-01

A linear optimization approach with a simple real arithmetic algorithm is presented for reliable controller design and vibration suppression of flexible structures. Using first order sensitivity of the system eigenvalues with respect to the design parameters in conjunction with a continuation procedure, the method converts a nonlinear optimization problem into a maximization problem with linear inequality constraints. The method of linear programming is then applied to solve the converted linear optimization problem. The general efficiency of the linear programming approach allows the method to handle structural optimization problems with a large number of inequality constraints on the design vector. The method is demonstrated using a truss beam finite element model for the optimal sizing and placement of active/passive-structural members for damping augmentation. Results using both the sequential linear optimization approach and nonlinear optimization are presented and compared. The insensitivity to initial conditions of the linear optimization approach is also demonstrated.

Space Based Radar-System Architecture Design and Optimization for a Space Based Replacement to AWACS

DTIC Science & Technology

1997-09-08

Davis Highway, Suite 1204, Arlington, VA 22202-4302, aod to the Office of Maoagement aod Bidget , Paperwork Reductioo Project 10704-0188), Washiogtoo...waveforms delayed by a time increment equal to the wave travel time. Note that the cross-correlation between the signal and noise is approximately zero. This...the discrete increments of satellites that can be lost The paradigm of reliability for losing a certain number of satellites is an inn-1 0.95

Finite element analysis of wirelessly interrogated implantable bio-MEMS

NASA Astrophysics Data System (ADS)

Dissanayake, Don W.; Al-Sarawi, Said F.; Lu, Tien-Fu; Abbott, Derek

2008-12-01

Wirelessly interrogated bio-MEMS devices are becoming more popular due to many challenges, such as improving the diagnosis, monitoring, and patient wellbeing. The authors present here a passive, low power and small area device, which can be interrogated wirelessly using a uniquely coded signal for a secure and reliable operation. The proposed new approach relies on converting the interrogating coded signal to surface acoustic wave that is then correlated with an embedded code. The suggested method is implemented to operate a micropump, which consist of a specially designed corrugated microdiaphragm to modulate the fluid flow in microchannels. Finite Element Analysis of the micropump operation is presented and a performance was analysed. Design parameters of the diaphragm design were finetuned for optimal performance and different polymer based materials were used in various parts of the micropump to allow for better flexibility and high reliability.

On the design of high-rise buildings with a specified level of reliability

NASA Astrophysics Data System (ADS)

Dolganov, Andrey; Kagan, Pavel

2018-03-01

High-rise buildings have a specificity, which significantly distinguishes them from traditional buildings of high-rise and multi-storey buildings. Steel structures in high-rise buildings are advisable to be used in earthquake-proof regions, since steel, due to its plasticity, provides damping of the kinetic energy of seismic impacts. These aspects should be taken into account when choosing a structural scheme of a high-rise building and designing load-bearing structures. Currently, modern regulatory documents do not quantify the reliability of structures. Although the problem of assigning an optimal level of reliability has existed for a long time. The article shows the possibility of designing metal structures of high-rise buildings with specified reliability. Currently, modern regulatory documents do not quantify the reliability of high-rise buildings. Although the problem of assigning an optimal level of reliability has existed for a long time. It is proposed to establish the value of reliability 0.99865 (3σ) for constructions of buildings and structures of a normal level of responsibility in calculations for the first group of limiting states. For increased (construction of high-rise buildings) and reduced levels of responsibility for the provision of load-bearing capacity, it is proposed to assign respectively 0.99997 (4σ) and 0.97725 (2σ). The coefficients of the use of the cross section of a metal beam for different levels of security are given.

Wind farm optimization using evolutionary algorithms

NASA Astrophysics Data System (ADS)

Ituarte-Villarreal, Carlos M.

In recent years, the wind power industry has focused its efforts on solving the Wind Farm Layout Optimization (WFLO) problem. Wind resource assessment is a pivotal step in optimizing the wind-farm design and siting and, in determining whether a project is economically feasible or not. In the present work, three (3) different optimization methods are proposed for the solution of the WFLO: (i) A modified Viral System Algorithm applied to the optimization of the proper location of the components in a wind-farm to maximize the energy output given a stated wind environment of the site. The optimization problem is formulated as the minimization of energy cost per unit produced and applies a penalization for the lack of system reliability. The viral system algorithm utilized in this research solves three (3) well-known problems in the wind-energy literature; (ii) a new multiple objective evolutionary algorithm to obtain optimal placement of wind turbines while considering the power output, cost, and reliability of the system. The algorithm presented is based on evolutionary computation and the objective functions considered are the maximization of power output, the minimization of wind farm cost and the maximization of system reliability. The final solution to this multiple objective problem is presented as a set of Pareto solutions and, (iii) A hybrid viral-based optimization algorithm adapted to find the proper component configuration for a wind farm with the introduction of the universal generating function (UGF) analytical approach to discretize the different operating or mechanical levels of the wind turbines in addition to the various wind speed states. The proposed methodology considers the specific probability functions of the wind resource to describe their proper behaviors to account for the stochastic comportment of the renewable energy components, aiming to increase their power output and the reliability of these systems. The developed heuristic considers a variable number of system components and wind turbines with different operating characteristics and sizes, to have a more heterogeneous model that can deal with changes in the layout and in the power generation requirements over the time. Moreover, the approach evaluates the impact of the wind-wake effect of the wind turbines upon one another to describe and evaluate the power production capacity reduction of the system depending on the layout distribution of the wind turbines.

Optimizing the Information Presentation on Mining Potential by using Web Services Technology with Restful Protocol

NASA Astrophysics Data System (ADS)

Abdillah, T.; Dai, R.; Setiawan, E.

2018-02-01

This study aims to develop the application of Web Services technology with RestFul Protocol to optimize the information presentation on mining potential. This study used User Interface Design approach for the information accuracy and relevance as well as the Web Service for the reliability in presenting the information. The results show that: the information accuracy and relevance regarding mining potential can be seen from the achievement of User Interface implementation in the application that is based on the following rules: The consideration of the appropriate colours and objects, the easiness of using the navigation, and users’ interaction with the applications that employs symbols and languages understood by the users; the information accuracy and relevance related to mining potential can be observed by the information presented by using charts and Tool Tip Text to help the users understand the provided chart/figure; the reliability of the information presentation is evident by the results of Web Services testing in Figure 4.5.6. This study finds out that User Interface Design and Web Services approaches (for the access of different Platform apps) are able to optimize the presentation. The results of this study can be used as a reference for software developers and Provincial Government of Gorontalo.

Solar-cell interconnect design for terrestrial photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1984-01-01

Useful solar cell interconnect reliability design and life prediction algorithms are presented, together with experimental data indicating that the classical strain cycle (fatigue) curve for the interconnect material does not account for the statistical scatter that is required in reliability predictions. This shortcoming is presently addressed by fitting a functional form to experimental cumulative interconnect failure rate data, which thereby yields statistical fatigue curves enabling not only the prediction of cumulative interconnect failures during the design life of an array field, but also the quantitative interpretation of data from accelerated thermal cycling tests. Optimal interconnect cost reliability design algorithms are also derived which may allow the minimization of energy cost over the design life of the array field.

Solar-cell interconnect design for terrestrial photovoltaic modules

NASA Astrophysics Data System (ADS)

Mon, G. R.; Moore, D. M.; Ross, R. G., Jr.

1984-11-01

Useful solar cell interconnect reliability design and life prediction algorithms are presented, together with experimental data indicating that the classical strain cycle (fatigue) curve for the interconnect material does not account for the statistical scatter that is required in reliability predictions. This shortcoming is presently addressed by fitting a functional form to experimental cumulative interconnect failure rate data, which thereby yields statistical fatigue curves enabling not only the prediction of cumulative interconnect failures during the design life of an array field, but also the quantitative interpretation of data from accelerated thermal cycling tests. Optimal interconnect cost reliability design algorithms are also derived which may allow the minimization of energy cost over the design life of the array field.

Hard and Soft Constraints in Reliability-Based Design Optimization

NASA Technical Reports Server (NTRS)

Crespo, L.uis G.; Giesy, Daniel P.; Kenny, Sean P.

2006-01-01

This paper proposes a framework for the analysis and design optimization of models subject to parametric uncertainty where design requirements in the form of inequality constraints are present. Emphasis is given to uncertainty models prescribed by norm bounded perturbations from a nominal parameter value and by sets of componentwise bounded uncertain variables. These models, which often arise in engineering problems, allow for a sharp mathematical manipulation. Constraints can be implemented in the hard sense, i.e., constraints must be satisfied for all parameter realizations in the uncertainty model, and in the soft sense, i.e., constraints can be violated by some realizations of the uncertain parameter. In regard to hard constraints, this methodology allows (i) to determine if a hard constraint can be satisfied for a given uncertainty model and constraint structure, (ii) to generate conclusive, formally verifiable reliability assessments that allow for unprejudiced comparisons of competing design alternatives and (iii) to identify the critical combination of uncertain parameters leading to constraint violations. In regard to soft constraints, the methodology allows the designer (i) to use probabilistic uncertainty models, (ii) to calculate upper bounds to the probability of constraint violation, and (iii) to efficiently estimate failure probabilities via a hybrid method. This method integrates the upper bounds, for which closed form expressions are derived, along with conditional sampling. In addition, an l(sub infinity) formulation for the efficient manipulation of hyper-rectangular sets is also proposed.

Performance analysis of complex repairable industrial systems using PSO and fuzzy confidence interval based methodology.

PubMed

Garg, Harish

2013-03-01

The main objective of the present paper is to propose a methodology for analyzing the behavior of the complex repairable industrial systems. In real-life situations, it is difficult to find the most optimal design policies for MTBF (mean time between failures), MTTR (mean time to repair) and related costs by utilizing available resources and uncertain data. For this, the availability-cost optimization model has been constructed for determining the optimal design parameters for improving the system design efficiency. The uncertainties in the data related to each component of the system are estimated with the help of fuzzy and statistical methodology in the form of the triangular fuzzy numbers. Using these data, the various reliability parameters, which affects the system performance, are obtained in the form of the fuzzy membership function by the proposed confidence interval based fuzzy Lambda-Tau (CIBFLT) methodology. The computed results by CIBFLT are compared with the existing fuzzy Lambda-Tau methodology. Sensitivity analysis on the system MTBF has also been addressed. The methodology has been illustrated through a case study of washing unit, the main part of the paper industry. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Design of optimized piezoelectric HDD-sliders

NASA Astrophysics Data System (ADS)

Nakasone, Paulo H.; Yoo, Jeonghoon; Silva, Emilio C. N.

2010-04-01

As storage data density in hard-disk drives (HDDs) increases for constant or miniaturizing sizes, precision positioning of HDD heads becomes a more relevant issue to ensure enormous amounts of data to be properly written and read. Since the traditional single-stage voice coil motor (VCM) cannot satisfy the positioning requirement of high-density tracks per inch (TPI) HDDs, dual-stage servo systems have been proposed to overcome this matter, by using VCMs to coarsely move the HDD head while piezoelectric actuators provides fine and fast positioning. Thus, the aim of this work is to apply topology optimization method (TOM) to design novel piezoelectric HDD heads, by finding optimal placement of base-plate and piezoelectric material to high precision positioning HDD heads. Topology optimization method is a structural optimization technique that combines the finite element method (FEM) with optimization algorithms. The laminated finite element employs the MITC (mixed interpolation of tensorial components) formulation to provide accurate and reliable results. The topology optimization uses a rational approximation of material properties to vary the material properties between 'void' and 'filled' portions. The design problem consists in generating optimal structures that provide maximal displacements, appropriate structural stiffness and resonance phenomena avoidance. The requirements are achieved by applying formulations to maximize displacements, minimize structural compliance and maximize resonance frequencies. This paper presents the implementation of the algorithms and show results to confirm the feasibility of this approach.

An Optimization-Based Approach to Determine Requirements and Aircraft Design under Multi-domain Uncertainties

NASA Astrophysics Data System (ADS)

Govindaraju, Parithi

Determining the optimal requirements for and design variable values of new systems, which operate along with existing systems to provide a set of overarching capabilities, as a single task is challenging due to the highly interconnected effects that setting requirements on a new system's design can have on how an operator uses this newly designed system. This task of determining the requirements and the design variable values becomes even more difficult because of the presence of uncertainties in the new system design and in the operational environment. This research proposed and investigated aspects of a framework that generates optimum design requirements of new, yet-to-be-designed systems that, when operating alongside other systems, will optimize fleet-level objectives while considering the effects of various uncertainties. Specifically, this research effort addresses the issues of uncertainty in the design of the new system through reliability-based design optimization methods, and uncertainty in the operations of the fleet through descriptive sampling methods and robust optimization formulations. In this context, fleet-level performance metrics result from using the new system alongside other systems to accomplish an overarching objective or mission. This approach treats the design requirements of a new system as decision variables in an optimization problem formulation that a user in the position of making an acquisition decision could solve. This solution would indicate the best new system requirements-and an associated description of the best possible design variable variables for that new system-to optimize the fleet level performance metric(s). Using a problem motivated by recorded operations of the United States Air Force Air Mobility Command for illustration, the approach is demonstrated first for a simplified problem that only considers demand uncertainties in the service network and the proposed methodology is used to identify the optimal design requirements and optimal aircraft sizing variables of new, yet-to-be-introduced aircraft. With this new aircraft serving alongside other existing aircraft, the fleet of aircraft satisfy the desired demand for cargo transportation, while maximizing fleet productivity and minimizing fuel consumption via a multi-objective problem formulation. The approach is then extended to handle uncertainties in both the design of the new system and in the operations of the fleet. The propagation of uncertainties associated with the conceptual design of the new aircraft to the uncertainties associated with the subsequent operations of the new and existing aircraft in the fleet presents some unique challenges. A computationally tractable hybrid robust counterpart formulation efficiently handles the confluence of the two types of domain-specific uncertainties. This hybrid formulation is tested on a larger route network problem to demonstrate the scalability of the approach. Following the presentation of the results obtained, a summary discussion indicates how decision-makers might use these results to set requirements for new aircraft that meet operational needs while balancing the environmental impact of the fleet with fleet-level performance. Comparing the solutions from the uncertainty-based and deterministic formulations via a posteriori analysis demonstrates the efficacy of the robust and reliability-based optimization formulations in addressing the different domain-specific uncertainties. Results suggest that the aircraft design requirements and design description determined through the hybrid robust counterpart formulation approach differ from solutions obtained from the simplistic deterministic approach, and leads to greater fleet-level fuel savings, when subjected to real-world uncertain scenarios (more robust to uncertainty). The research, though applied to a specific air cargo application, is technically agnostic in nature and can be applied to other facets of policy and acquisition management, to explore capability trade spaces for different vehicle systems, mitigate risks, define policy and potentially generate better returns on investment. Other domains relevant to policy and acquisition decisions could utilize the problem formulation and solution approach proposed in this dissertation provided that the problem can be split into a non-linear programming problem to describe the new system sizing and the fleet operations problem can be posed as a linear/integer programming problem.

Modified Bayesian Kriging for Noisy Response Problems for Reliability Analysis

DTIC Science & Technology

2015-01-01

52242, USA nicholas-gaul@uiowa.edu Mary Kathryn Cowles Department of Statistics & Actuarial Science College of Liberal Arts and Sciences , The...Forrester, A. I. J., & Keane, A. J. (2009). Recent advances in surrogate-based optimization. Progress in Aerospace Sciences , 45(1–3), 50-79. doi...Wiley. [27] Sacks, J., Welch, W. J., Toby J. Mitchell, & Wynn, H. P. (1989). Design and analysis of computer experiments. Statistical Science , 4

Perceptual attraction in tool use: evidence for a reliability-based weighting mechanism.

PubMed

Debats, Nienke B; Ernst, Marc O; Heuer, Herbert

2017-04-01

Humans are well able to operate tools whereby their hand movement is linked, via a kinematic transformation, to a spatially distant object moving in a separate plane of motion. An everyday example is controlling a cursor on a computer monitor. Despite these separate reference frames, the perceived positions of the hand and the object were found to be biased toward each other. We propose that this perceptual attraction is based on the principles by which the brain integrates redundant sensory information of single objects or events, known as optimal multisensory integration. That is, 1 ) sensory information about the hand and the tool are weighted according to their relative reliability (i.e., inverse variances), and 2 ) the unisensory reliabilities sum up in the integrated estimate. We assessed whether perceptual attraction is consistent with optimal multisensory integration model predictions. We used a cursor-control tool-use task in which we manipulated the relative reliability of the unisensory hand and cursor position estimates. The perceptual biases shifted according to these relative reliabilities, with an additional bias due to contextual factors that were present in experiment 1 but not in experiment 2 The biased position judgments' variances were, however, systematically larger than the predicted optimal variances. Our findings suggest that the perceptual attraction in tool use results from a reliability-based weighting mechanism similar to optimal multisensory integration, but that certain boundary conditions for optimality might not be satisfied. NEW & NOTEWORTHY Kinematic tool use is associated with a perceptual attraction between the spatially separated hand and the effective part of the tool. We provide a formal account for this phenomenon, thereby showing that the process behind it is similar to optimal integration of sensory information relating to single objects. Copyright © 2017 the American Physiological Society.

Orbit transfer vehicle engine study, phase A, extension 1: Volume 2: Study results

NASA Technical Reports Server (NTRS)

Mellish, J. A.

1981-01-01

Because of the advantage of the Advanced Expander Cycle Engine brought out in initial studies, further design optimization and comparative analyses were undertaken. The major results and conclusion derived are summarized. The primary areas covered are (1) thrust chamber geometry optimization, (2) expander cycle optimization, (3) alternate low thrust capability, (4) safety and reliability, (5) development risk comparison, and (6) cost comparisons. All of the results obtained were used to baseline the initial design concept for the OTV Advanced Expander Cycle Engine Point Design Study.

Study of a fail-safe abort system for an actively cooled hypersonic aircraft. Volume 1: Technical summary

NASA Technical Reports Server (NTRS)

Pirello, C. J.; Herring, R. L.

1976-01-01

Conceptual designs of a fail-safe abort system for hydrogen fueled actively cooled high speed aircraft are examined. The fail-safe concept depends on basically three factors: (1) a reliable method of detecting a failure or malfunction in the active cooling system, (2) the optimization of abort trajectories which minimize the descent heat load to the aircraft, and (3) fail-safe thermostructural concepts to minimize both the weight and the maximum temperature the structure will reach during descent. These factors are examined and promising approaches are evaluated based on weight, reliability, ease of manufacture and cost.

Mechanically and optically reliable folding structure with a hyperelastic material for seamless foldable displays

NASA Astrophysics Data System (ADS)

Kwon, Hyuk-Jun; Shim, HongShik; Kim, Sunkook; Choi, Woong; Chun, Youngtea; Kee, InSeo; Lee, SangYoon

2011-04-01

We report a mechanically and optically robust folding structure to realize a foldable active matrix organic-light-emitting-diode (AMOLED) display without a visible crease at the junction. A nonlinear stress analysis, based on a finite element method, provided an optimized design. The folding-unfolding test on the structure exhibited negligible deterioration of the relative brightness at the junction of the individual panels up to 105 cycles at a folding radius of 1 mm, indicating highly reliable mechanical and optical tolerances. These results demonstrate the feasibility of seamless foldable AMOLED displays, with potentially important technical implications on fabricating large size flexible displays.

Total systems design analysis of high performance structures

NASA Technical Reports Server (NTRS)

Verderaime, V.

1993-01-01

Designer-control parameters were identified at interdiscipline interfaces to optimize structural systems performance and downstream development and operations with reliability and least life-cycle cost. Interface tasks and iterations are tracked through a matrix of performance disciplines integration versus manufacturing, verification, and operations interactions for a total system design analysis. Performance integration tasks include shapes, sizes, environments, and materials. Integrity integrating tasks are reliability and recurring structural costs. Significant interface designer control parameters were noted as shapes, dimensions, probability range factors, and cost. Structural failure concept is presented, and first-order reliability and deterministic methods, benefits, and limitations are discussed. A deterministic reliability technique combining benefits of both is proposed for static structures which is also timely and economically verifiable. Though launch vehicle environments were primarily considered, the system design process is applicable to any surface system using its own unique filed environments.

Absorbable energy monitoring scheme: new design protocol to test vehicle structural crashworthiness.

PubMed

Ofochebe, Sunday M; Enibe, Samuel O; Ozoegwu, Chigbogu G

2016-05-01

In vehicle crashworthiness design optimization detailed system evaluation capable of producing reliable results are basically achieved through high-order numerical computational (HNC) models such as the dynamic finite element model, mesh-free model etc. However the application of these models especially during optimization studies is basically challenged by their inherent high demand on computational resources, conditional stability of the solution process, and lack of knowledge of viable parameter range for detailed optimization studies. The absorbable energy monitoring scheme (AEMS) presented in this paper suggests a new design protocol that attempts to overcome such problems in evaluation of vehicle structure for crashworthiness. The implementation of the AEMS involves studying crash performance of vehicle components at various absorbable energy ratios based on a 2DOF lumped-mass-spring (LMS) vehicle impact model. This allows for prompt prediction of useful parameter values in a given design problem. The application of the classical one-dimensional LMS model in vehicle crash analysis is further improved in the present work by developing a critical load matching criterion which allows for quantitative interpretation of the results of the abstract model in a typical vehicle crash design. The adequacy of the proposed AEMS for preliminary vehicle crashworthiness design is demonstrated in this paper, however its extension to full-scale design-optimization problem involving full vehicle model that shows greater structural detail requires more theoretical development.

Evaluating information content of SNPs for sample-tagging in re-sequencing projects.

PubMed

Hu, Hao; Liu, Xiang; Jin, Wenfei; Hilger Ropers, H; Wienker, Thomas F

2015-05-15

Sample-tagging is designed for identification of accidental sample mix-up, which is a major issue in re-sequencing studies. In this work, we develop a model to measure the information content of SNPs, so that we can optimize a panel of SNPs that approach the maximal information for discrimination. The analysis shows that as low as 60 optimized SNPs can differentiate the individuals in a population as large as the present world, and only 30 optimized SNPs are in practice sufficient in labeling up to 100 thousand individuals. In the simulated populations of 100 thousand individuals, the average Hamming distances, generated by the optimized set of 30 SNPs are larger than 18, and the duality frequency, is lower than 1 in 10 thousand. This strategy of sample discrimination is proved robust in large sample size and different datasets. The optimized sets of SNPs are designed for Whole Exome Sequencing, and a program is provided for SNP selection, allowing for customized SNP numbers and interested genes. The sample-tagging plan based on this framework will improve re-sequencing projects in terms of reliability and cost-effectiveness.

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems

PubMed Central

2017-01-01

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data. PMID:28806754

Short-term prediction of solar energy in Saudi Arabia using automated-design fuzzy logic systems.

PubMed

Almaraashi, Majid

2017-01-01

Solar energy is considered as one of the main sources for renewable energy in the near future. However, solar energy and other renewable energy sources have a drawback related to the difficulty in predicting their availability in the near future. This problem affects optimal exploitation of solar energy, especially in connection with other resources. Therefore, reliable solar energy prediction models are essential to solar energy management and economics. This paper presents work aimed at designing reliable models to predict the global horizontal irradiance (GHI) for the next day in 8 stations in Saudi Arabia. The designed models are based on computational intelligence methods of automated-design fuzzy logic systems. The fuzzy logic systems are designed and optimized with two models using fuzzy c-means clustering (FCM) and simulated annealing (SA) algorithms. The first model uses FCM based on the subtractive clustering algorithm to automatically design the predictor fuzzy rules from data. The second model is using FCM followed by simulated annealing algorithm to enhance the prediction accuracy of the fuzzy logic system. The objective of the predictor is to accurately predict next-day global horizontal irradiance (GHI) using previous-day meteorological and solar radiation observations. The proposed models use observations of 10 variables of measured meteorological and solar radiation data to build the model. The experimentation and results of the prediction are detailed where the root mean square error of the prediction was approximately 88% for the second model tuned by simulated annealing compared to 79.75% accuracy using the first model. This results demonstrate a good modeling accuracy of the second model despite that the training and testing of the proposed models were carried out using spatially and temporally independent data.

A reliability and mass perspective of SP-100 Stirling cycle lunar-base powerplant designs

NASA Technical Reports Server (NTRS)

Bloomfield, Harvey S.

1991-01-01

The purpose was to obtain reliability and mass perspectives on selection of space power system conceptual designs based on SP-100 reactor and Stirling cycle power-generation subsystems. The approach taken was to: (1) develop a criterion for an acceptable overall reliability risk as a function of the expected range of emerging technology subsystem unit reliabilities; (2) conduct reliability and mass analyses for a diverse matrix of 800-kWe lunar-base design configurations employing single and multiple powerplants with both full and partial subsystem redundancy combinations; and (3) derive reliability and mass perspectives on selection of conceptual design configurations that meet an acceptable reliability criterion with the minimum system mass increase relative to reference powerplant design. The developed perspectives provided valuable insight into the considerations required to identify and characterize high-reliability and low-mass lunar-base powerplant conceptual design.

Towards Robust Designs Via Multiple-Objective Optimization Methods

NASA Technical Reports Server (NTRS)

Man Mohan, Rai

2006-01-01

Fabricating and operating complex systems involves dealing with uncertainty in the relevant variables. In the case of aircraft, flow conditions are subject to change during operation. Efficiency and engine noise may be different from the expected values because of manufacturing tolerances and normal wear and tear. Engine components may have a shorter life than expected because of manufacturing tolerances. In spite of the important effect of operating- and manufacturing-uncertainty on the performance and expected life of the component or system, traditional aerodynamic shape optimization has focused on obtaining the best design given a set of deterministic flow conditions. Clearly it is important to both maintain near-optimal performance levels at off-design operating conditions, and, ensure that performance does not degrade appreciably when the component shape differs from the optimal shape due to manufacturing tolerances and normal wear and tear. These requirements naturally lead to the idea of robust optimal design wherein the concept of robustness to various perturbations is built into the design optimization procedure. The basic ideas involved in robust optimal design will be included in this lecture. The imposition of the additional requirement of robustness results in a multiple-objective optimization problem requiring appropriate solution procedures. Typically the costs associated with multiple-objective optimization are substantial. Therefore efficient multiple-objective optimization procedures are crucial to the rapid deployment of the principles of robust design in industry. Hence the companion set of lecture notes (Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks ) deals with methodology for solving multiple-objective Optimization problems efficiently, reliably and with little user intervention. Applications of the methodologies presented in the companion lecture to robust design will be included here. The evolutionary method (DE) is first used to solve a relatively difficult problem in extended surface heat transfer wherein optimal fin geometries are obtained for different safe operating base temperatures. The objective of maximizing the safe operating base temperature range is in direct conflict with the objective of maximizing fin heat transfer. This problem is a good example of achieving robustness in the context of changing operating conditions. The evolutionary method is then used to design a turbine airfoil; the two objectives being reduced sensitivity of the pressure distribution to small changes in the airfoil shape and the maximization of the trailing edge wedge angle with the consequent increase in airfoil thickness and strength. This is a relevant example of achieving robustness to manufacturing tolerances and wear and tear in the presence of other objectives.

Design and multiphysics analysis of a 176Â MHz continuous-wave radio-frequency quadrupole

NASA Astrophysics Data System (ADS)

Kutsaev, S. V.; Mustapha, B.; Ostroumov, P. N.; Barcikowski, A.; Schrage, D.; Rodnizki, J.; Berkovits, D.

2014-07-01

We have developed a new design for a 176 MHz cw radio-frequency quadrupole (RFQ) for the SARAF upgrade project. At this frequency, the proposed design is a conventional four-vane structure. The main design goals are to provide the highest possible shunt impedance while limiting the required rf power to about 120 kW for reliable cw operation, and the length to about 4 meters. If built as designed, the proposed RFQ will be the first four-vane cw RFQ built as a single cavity (no resonant coupling required) that does not require π-mode stabilizing loops or dipole rods. For this, we rely on very detailed 3D simulations of all aspects of the structure and the level of machining precision achieved on the recently developed ATLAS upgrade RFQ. A full 3D model of the structure including vane modulation was developed. The design was optimized using electromagnetic and multiphysics simulations. Following the choice of the vane type and geometry, the vane undercuts were optimized to produce a flat field along the structure. The final design has good mode separation and should not need dipole rods if built as designed, but their effect was studied in the case of manufacturing errors. The tuners were also designed and optimized to tune the main mode without affecting the field flatness. Following the electromagnetic (EM) design optimization, a multiphysics engineering analysis of the structure was performed. The multiphysics analysis is a coupled electromagnetic, thermal and mechanical analysis. The cooling channels, including their paths and sizes, were optimized based on the limiting temperature and deformation requirements. The frequency sensitivity to the RFQ body and vane cooling water temperatures was carefully studied in order to use it for frequency fine-tuning. Finally, an inductive rf power coupler design based on the ATLAS RFQ coupler was developed and simulated. The EM design optimization was performed using cst Microwave Studio and the results were verified using both hfss and ansys. The engineering analysis was performed using hfss and ansys and most of the results were verified using the newly developed cst Multiphysics package.

Design for Reliability and Safety Approach for the NASA New Launch Vehicle

NASA Technical Reports Server (NTRS)

Safie, Fayssal, M.; Weldon, Danny M.

2007-01-01

The United States National Aeronautics and Space Administration (NASA) is in the midst of a space exploration program intended for sending crew and cargo to the international Space Station (ISS), to the moon, and beyond. This program is called Constellation. As part of the Constellation program, NASA is developing new launch vehicles aimed at significantly increase safety and reliability, reduce the cost of accessing space, and provide a growth path for manned space exploration. Achieving these goals requires a rigorous process that addresses reliability, safety, and cost upfront and throughout all the phases of the life cycle of the program. This paper discusses the "Design for Reliability and Safety" approach for the NASA new crew launch vehicle called ARES I. The ARES I is being developed by NASA Marshall Space Flight Center (MSFC) in support of the Constellation program. The ARES I consists of three major Elements: A solid First Stage (FS), an Upper Stage (US), and liquid Upper Stage Engine (USE). Stacked on top of the ARES I is the Crew exploration vehicle (CEV). The CEV consists of a Launch Abort System (LAS), Crew Module (CM), Service Module (SM), and a Spacecraft Adapter (SA). The CEV development is being led by NASA Johnson Space Center (JSC). Designing for high reliability and safety require a good integrated working environment and a sound technical design approach. The "Design for Reliability and Safety" approach addressed in this paper discusses both the environment and the technical process put in place to support the ARES I design. To address the integrated working environment, the ARES I project office has established a risk based design group called "Operability Design and Analysis" (OD&A) group. This group is an integrated group intended to bring together the engineering, design, and safety organizations together to optimize the system design for safety, reliability, and cost. On the technical side, the ARES I project has, through the OD&A environment, implemented a probabilistic approach to analyze and evaluate design uncertainties and understand their impact on safety, reliability, and cost. This paper focuses on the use of the various probabilistic approaches that have been pursued by the ARES I project. Specifically, the paper discusses an integrated functional probabilistic analysis approach that addresses upffont some key areas to support the ARES I Design Analysis Cycle (DAC) pre Preliminary Design (PD) Phase. This functional approach is a probabilistic physics based approach that combines failure probabilities with system dynamics and engineering failure impact models to identify key system risk drivers and potential system design requirements. The paper also discusses other probabilistic risk assessment approaches planned by the ARES I project to support the PD phase and beyond.

Semidefinite Relaxation-Based Optimization of Multiple-Input Wireless Power Transfer Systems

NASA Astrophysics Data System (ADS)

Lang, Hans-Dieter; Sarris, Costas D.

2017-11-01

An optimization procedure for multi-transmitter (MISO) wireless power transfer (WPT) systems based on tight semidefinite relaxation (SDR) is presented. This method ensures physical realizability of MISO WPT systems designed via convex optimization -- a robust, semi-analytical and intuitive route to optimizing such systems. To that end, the nonconvex constraints requiring that power is fed into rather than drawn from the system via all transmitter ports are incorporated in a convex semidefinite relaxation, which is efficiently and reliably solvable by dedicated algorithms. A test of the solution then confirms that this modified problem is equivalent (tight relaxation) to the original (nonconvex) one and that the true global optimum has been found. This is a clear advantage over global optimization methods (e.g. genetic algorithms), where convergence to the true global optimum cannot be ensured or tested. Discussions of numerical results yielded by both the closed-form expressions and the refined technique illustrate the importance and practicability of the new method. It, is shown that this technique offers a rigorous optimization framework for a broad range of current and emerging WPT applications.

FAST: a framework for simulation and analysis of large-scale protein-silicon biosensor circuits.

PubMed

Gu, Ming; Chakrabartty, Shantanu

2013-08-01

This paper presents a computer aided design (CAD) framework for verification and reliability analysis of protein-silicon hybrid circuits used in biosensors. It is envisioned that similar to integrated circuit (IC) CAD design tools, the proposed framework will be useful for system level optimization of biosensors and for discovery of new sensing modalities without resorting to laborious fabrication and experimental procedures. The framework referred to as FAST analyzes protein-based circuits by solving inverse problems involving stochastic functional elements that admit non-linear relationships between different circuit variables. In this regard, FAST uses a factor-graph netlist as a user interface and solving the inverse problem entails passing messages/signals between the internal nodes of the netlist. Stochastic analysis techniques like density evolution are used to understand the dynamics of the circuit and estimate the reliability of the solution. As an example, we present a complete design flow using FAST for synthesis, analysis and verification of our previously reported conductometric immunoassay that uses antibody-based circuits to implement forward error-correction (FEC).

Reliability and paste process optimization of eutectic and lead-free for mixed packaging

NASA Technical Reports Server (NTRS)

Ramkumar, S. M.; Ganeshan, V.; Thenalur, K.; Ghaffarian, R.

2002-01-01

This paper reports the results of an experiment that utilized the JPL's area array consortium test vehicle design, containing a myriad of mixed technology components with an OSP finish. The details of the reliability study are presented in this paper.

Computer-based mechanical design of overhead lines

NASA Astrophysics Data System (ADS)

Rusinaru, D.; Bratu, C.; Dinu, R. C.; Manescu, L. G.

2016-02-01

Beside the performance, the safety level according to the actual standards is a compulsory condition for distribution grids’ operation. Some of the measures leading to improvement of the overhead lines reliability ask for installations’ modernization. The constraints imposed to the new lines components refer to the technical aspects as thermal stress or voltage drop, and look for economic efficiency, too. The mechanical sizing of the overhead lines is after all an optimization problem. More precisely, the task in designing of the overhead line profile is to size poles, cross-arms and stays and locate poles along a line route so that the total costs of the line's structure to be minimized and the technical and safety constraints to be fulfilled.The authors present in this paper an application for the Computer-Based Mechanical Design of the Overhead Lines and the features of the corresponding Visual Basic program, adjusted to the distribution lines. The constraints of the optimization problem are adjusted to the existing weather and loading conditions of Romania. The outputs of the software application for mechanical design of overhead lines are: the list of components chosen for the line: poles, cross-arms, stays; the list of conductor tension and forces for each pole, cross-arm and stay for different weather conditions; the line profile drawings.The main features of the mechanical overhead lines design software are interactivity, local optimization function and high-level user-interface

Numerical analysis and design optimization of supersonic after-burning with strut fuel injectors for scramjet engines

NASA Astrophysics Data System (ADS)

Candon, M. J.; Ogawa, H.

2018-06-01

Scramjets are a class of hypersonic airbreathing engine that offer promise for economical, reliable and high-speed access-to-space and atmospheric transport. The expanding flow in the scramjet nozzle comprises of unburned hydrogen. An after-burning scheme can be used to effectively utilize the remaining hydrogen by supplying additional oxygen into the nozzle, aiming to augment the thrust. This paper presents the results of a single-objective design optimization for a strut fuel injection scheme considering four design variables with the objective of maximizing thrust augmentation. Thrust is found to be augmented significantly owing to a combination of contributions from aerodynamic and combustion effects. Further understanding and physical insights have been gained by performing variance-based global sensitivity analysis, scrutinizing the nozzle flowfields, analyzing the distributions and contributions of the forces acting on the nozzle wall, and examining the combustion efficiency.

Advanced Cogeneration Technology Economic Optimization Study (ACTEOS)

NASA Technical Reports Server (NTRS)

Nanda, P.; Ansu, Y.; Manuel, E. H., Jr.; Price, W. G., Jr.

1980-01-01

The advanced cogeneration technology economic optimization study (ACTEOS) was undertaken to extend the results of the cogeneration technology alternatives study (CTAS). Cost comparisons were made between designs involving advanced cogeneration technologies and designs involving either conventional cogeneration technologies or not involving cogeneration. For the specific equipment cost and fuel price assumptions made, it was found that: (1) coal based cogeneration systems offered appreciable cost savings over the no cogeneration case, while systems using coal derived liquids offered no costs savings; and (2) the advanced cogeneration systems provided somewhat larger cost savings than the conventional systems. Among the issues considered in the study included: (1) temporal variations in steam and electric demands; (2) requirements for reliability/standby capacity; (3) availability of discrete equipment sizes; (4) regional variations in fuel and electricity prices; (5) off design system performance; and (6) separate demand and energy charges for purchased electricity.

Stochastic Methods for Aircraft Design

NASA Technical Reports Server (NTRS)

Pelz, Richard B.; Ogot, Madara

1998-01-01

The global stochastic optimization method, simulated annealing (SA), was adapted and applied to various problems in aircraft design. The research was aimed at overcoming the problem of finding an optimal design in a space with multiple minima and roughness ubiquitous to numerically generated nonlinear objective functions. SA was modified to reduce the number of objective function evaluations for an optimal design, historically the main criticism of stochastic methods. SA was applied to many CFD/MDO problems including: low sonic-boom bodies, minimum drag on supersonic fore-bodies, minimum drag on supersonic aeroelastic fore-bodies, minimum drag on HSCT aeroelastic wings, FLOPS preliminary design code, another preliminary aircraft design study with vortex lattice aerodynamics, HSR complete aircraft aerodynamics. In every case, SA provided a simple, robust and reliable optimization method which found optimal designs in order 100 objective function evaluations. Perhaps most importantly, from this academic/industrial project, technology has been successfully transferred; this method is the method of choice for optimization problems at Northrop Grumman.

Behavior and neural basis of near-optimal visual search

PubMed Central

Ma, Wei Ji; Navalpakkam, Vidhya; Beck, Jeffrey M; van den Berg, Ronald; Pouget, Alexandre

2013-01-01

The ability to search efficiently for a target in a cluttered environment is one of the most remarkable functions of the nervous system. This task is difficult under natural circumstances, as the reliability of sensory information can vary greatly across space and time and is typically a priori unknown to the observer. In contrast, visual-search experiments commonly use stimuli of equal and known reliability. In a target detection task, we randomly assigned high or low reliability to each item on a trial-by-trial basis. An optimal observer would weight the observations by their trial-to-trial reliability and combine them using a specific nonlinear integration rule. We found that humans were near-optimal, regardless of whether distractors were homogeneous or heterogeneous and whether reliability was manipulated through contrast or shape. We present a neural-network implementation of near-optimal visual search based on probabilistic population coding. The network matched human performance. PMID:21552276

CFD-Based Design Optimization Tool Developed for Subsonic Inlet

NASA Technical Reports Server (NTRS)

1995-01-01

The traditional approach to the design of engine inlets for commercial transport aircraft is a tedious process that ends with a less-than-optimum design. With the advent of high-speed computers and the availability of more accurate and reliable computational fluid dynamics (CFD) solvers, numerical optimization processes can effectively be used to design an aerodynamic inlet lip that enhances engine performance. The designers' experience at Boeing Corporation showed that for a peak Mach number on the inlet surface beyond some upper limit, the performance of the engine degrades excessively. Thus, our objective was to optimize efficiency (minimize the peak Mach number) at maximum cruise without compromising performance at other operating conditions. Using a CFD code NPARC, the NASA Lewis Research Center, in collaboration with Boeing, developed an integrated procedure at Lewis to find the optimum shape of a subsonic inlet lip and a numerical optimization code, ADS. We used a GRAPE-based three-dimensional grid generator to help automate the optimization procedure. The inlet lip shape at the crown and the keel was described as a superellipse, and the superellipse exponents and radii ratios were considered as design variables. Three operating conditions: cruise, takeoff, and rolling takeoff, were considered in this study. Three-dimensional Euler computations were carried out to obtain the flow field. At the initial design, the peak Mach numbers for maximum cruise, takeoff, and rolling takeoff conditions were 0.88, 1.772, and 1.61, respectively. The acceptable upper limits on the takeoff and rolling takeoff Mach numbers were 1.55 and 1.45. Since the initial design provided by Boeing was found to be optimum with respect to the maximum cruise condition, the sum of the peak Mach numbers at takeoff and rolling takeoff were minimized in the current study while the maximum cruise Mach number was constrained to be close to that at the existing design. With this objective, the optimum design satisfied the upper limits at takeoff and rolling takeoff while retaining the desirable cruise performance. Further studies are being conducted to include static and cross-wind operating conditions in the design optimization procedure. This work was carried out in collaboration with Dr. E.S. Reddy of NYMA, Inc.

Award-Winning CARES/Life Ceramics Durability Evaluation Software Is Making Advanced Technology Accessible

NASA Technical Reports Server (NTRS)

1997-01-01

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CARES/Life software developed at the NASA Lewis Research Center eases this by providing a tool that uses probabilistic reliability analysis techniques to optimize the design and manufacture of brittle material components. CARES/Life is an integrated package that predicts the probability of a monolithic ceramic component's failure as a function of its time in service. It couples commercial finite element programs--which resolve a component's temperature and stress distribution - with reliability evaluation and fracture mechanics routines for modeling strength - limiting defects. These routines are based on calculations of the probabilistic nature of the brittle material's strength.

Optimization of a PCRAM Chip for high-speed read and highly reliable reset operations

NASA Astrophysics Data System (ADS)

Li, Xiaoyun; Chen, Houpeng; Li, Xi; Wang, Qian; Fan, Xi; Hu, Jiajun; Lei, Yu; Zhang, Qi; Tian, Zhen; Song, Zhitang

2016-10-01

The widely used traditional Flash memory suffers from its performance limits such as its serious crosstalk problems, and increasing complexity of floating gate scaling. Phase change random access memory (PCRAM) becomes one of the most potential nonvolatile memories among the new memory techniques. In this paper, a 1M-bit PCRAM chip is designed based on the SMIC 40nm CMOS technology. Focusing on the read and write performance, two new circuits with high-speed read operation and highly reliable reset operation are proposed. The high-speed read circuit effectively reduces the reading time from 74ns to 40ns. The double-mode reset circuit improves the chip yield. This 1M-bit PCRAM chip has been simulated on cadence. After layout design is completed, the chip will be taped out for post-test.

Optimal periodic proof test based on cost-effective and reliability criteria

NASA Technical Reports Server (NTRS)

Yang, J.-N.

1976-01-01

An exploratory study for the optimization of periodic proof tests for fatigue-critical structures is presented. The optimal proof load level and the optimal number of periodic proof tests are determined by minimizing the total expected (statistical average) cost, while the constraint on the allowable level of structural reliability is satisfied. The total expected cost consists of the expected cost of proof tests, the expected cost of structures destroyed by proof tests, and the expected cost of structural failure in service. It is demonstrated by numerical examples that significant cost saving and reliability improvement for fatigue-critical structures can be achieved by the application of the optimal periodic proof test. The present study is relevant to the establishment of optimal maintenance procedures for fatigue-critical structures.

Characterization of interfade duration for satellite communication systems design and optimization in a temperate climate

NASA Astrophysics Data System (ADS)

Jorge, Flávio; Riva, Carlo; Rocha, Armando

2016-03-01

The characterization of the fade dynamics on Earth-satellite links is an important subject when designing the so called fade mitigation techniques that contribute to the proper reliability of the satellite communication systems and the customers' quality of service (QoS). The interfade duration, defined as the period between two consecutive fade events, has been only poorly analyzed using limited data sets, but its complete characterization would enable the design and optimization of the satellite communication systems by estimating the system requirements to recover in time before the next propagation impairment. Depending on this analysis, several actions can be taken ensuring the service maintenance. In this paper we present for the first time a detailed and comprehensive analysis of the interfade events statistical properties based on 9 years of in-excess attenuation measurements at Ka band (19.7 GHz) with very high availability that is required to build a reliable data set mainly for the longer interfade duration events. The number of years necessary to reach the statistical stability of interfade duration is also evaluated for the first time, providing a reference when accessing the relevance of the results published in the past. The study is carried out in Aveiro, Portugal, which is conditioned by temperate Mediterranean climate with Oceanic influences.

Optimization of multiplexed PCR on an integrated microfluidic forensic platform for rapid DNA analysis.

PubMed

Estes, Matthew D; Yang, Jianing; Duane, Brett; Smith, Stan; Brooks, Carla; Nordquist, Alan; Zenhausern, Frederic

2012-12-07

This study reports the design, prototyping, and assay development of multiplexed polymerase chain reaction (PCR) on a plastic microfluidic device. Amplification of 17 DNA loci is carried out directly on-chip as part of a system for continuous workflow processing from sample preparation (SP) to capillary electrophoresis (CE). For enhanced performance of on-chip PCR amplification, improved control systems have been developed making use of customized Peltier assemblies, valve actuators, software, and amplification chemistry protocols. Multiple enhancements to the microfluidic chip design have been enacted to improve the reliability of sample delivery through the various on-chip modules. This work has been enabled by the encapsulation of PCR reagents into a solid phase material through an optimized Solid Phase Encapsulating Assay Mix (SPEAM) bead-based hydrogel fabrication process. SPEAM bead technology is reliably coupled with precise microfluidic metering and dispensing for efficient amplification and subsequent DNA short tandem repeat (STR) fragment analysis. This provides a means of on-chip reagent storage suitable for microfluidic automation, with the long shelf-life necessary for point-of-care (POC) or field deployable applications. This paper reports the first high quality 17-plex forensic STR amplification from a reference sample in a microfluidic chip with preloaded solid phase reagents, that is designed for integration with up and downstream processing.

New technologies for advanced three-dimensional optimum shape design in aeronautics

NASA Astrophysics Data System (ADS)

Dervieux, Alain; Lanteri, Stéphane; Malé, Jean-Michel; Marco, Nathalie; Rostaing-Schmidt, Nicole; Stoufflet, Bruno

1999-05-01

The analysis of complex flows around realistic aircraft geometries is becoming more and more predictive. In order to obtain this result, the complexity of flow analysis codes has been constantly increasing, involving more refined fluid models and sophisticated numerical methods. These codes can only run on top computers, exhausting their memory and CPU capabilities. It is, therefore, difficult to introduce best analysis codes in a shape optimization loop: most previous works in the optimum shape design field used only simplified analysis codes. Moreover, as the most popular optimization methods are the gradient-based ones, the more complex the flow solver, the more difficult it is to compute the sensitivity code. However, emerging technologies are contributing to make such an ambitious project, of including a state-of-the-art flow analysis code into an optimisation loop, feasible. Among those technologies, there are three important issues that this paper wishes to address: shape parametrization, automated differentiation and parallel computing. Shape parametrization allows faster optimization by reducing the number of design variable; in this work, it relies on a hierarchical multilevel approach. The sensitivity code can be obtained using automated differentiation. The automated approach is based on software manipulation tools, which allow the differentiation to be quick and the resulting differentiated code to be rather fast and reliable. In addition, the parallel algorithms implemented in this work allow the resulting optimization software to run on increasingly larger geometries. Copyright

Performance enhancement of Pt/TiO2/Si UV-photodetector by optimizing light trapping capability and interdigitated electrodes geometry

NASA Astrophysics Data System (ADS)

Bencherif, H.; Djeffal, F.; Ferhati, H.

2016-09-01

This paper presents a hybrid approach based on an analytical and metaheuristic investigation to study the impact of the interdigitated electrodes engineering on both speed and optical performance of an Interdigitated Metal-Semiconductor-Metal Ultraviolet Photodetector (IMSM-UV-PD). In this context, analytical models regarding the speed and optical performance have been developed and validated by experimental results, where a good agreement has been recorded. Moreover, the developed analytical models have been used as objective functions to determine the optimized design parameters, including the interdigit configuration effect, via a Multi-Objective Genetic Algorithm (MOGA). The ultimate goal of the proposed hybrid approach is to identify the optimal design parameters associated with the maximum of electrical and optical device performance. The optimized IMSM-PD not only reveals superior performance in terms of photocurrent and response time, but also illustrates higher optical reliability against the optical losses due to the active area shadowing effects. The advantages offered by the proposed design methodology suggest the possibility to overcome the most challenging problem with the communication speed and power requirements of the UV optical interconnect: high derived current and commutation speed in the UV receiver.

Optimization of Microelectronic Devices for Sensor Applications

NASA Technical Reports Server (NTRS)

Cwik, Tom; Klimeck, Gerhard

2000-01-01

The NASA/JPL goal to reduce payload in future space missions while increasing mission capability demands miniaturization of active and passive sensors, analytical instruments and communication systems among others. Currently, typical system requirements include the detection of particular spectral lines, associated data processing, and communication of the acquired data to other systems. Advances in lithography and deposition methods result in more advanced devices for space application, while the sub-micron resolution currently available opens a vast design space. Though an experimental exploration of this widening design space-searching for optimized performance by repeated fabrication efforts-is unfeasible, it does motivate the development of reliable software design tools. These tools necessitate models based on fundamental physics and mathematics of the device to accurately model effects such as diffraction and scattering in opto-electronic devices, or bandstructure and scattering in heterostructure devices. The software tools must have convenient turn-around times and interfaces that allow effective usage. The first issue is addressed by the application of high-performance computers and the second by the development of graphical user interfaces driven by properly developed data structures. These tools can then be integrated into an optimization environment, and with the available memory capacity and computational speed of high performance parallel platforms, simulation of optimized components can proceed. In this paper, specific applications of the electromagnetic modeling of infrared filtering, as well as heterostructure device design will be presented using genetic algorithm global optimization methods.

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.

Modeling of liquid flow in surface discontinuities

NASA Astrophysics Data System (ADS)

Lobanova, I. S.; Meshcheryakov, V. A.; Kalinichenko, A. N.

2018-01-01

Polymer composite and metallic materials have found wide application in various industries such as aviation, rocket, car manufacturing, ship manufacturing, etc. Many design elements need permanent quality control. Ensuring high quality and reliability of products is impossible without effective nondestructive testing methods. One of these methods is penetrant testing using penetrating substances based on liquid penetration into defect cavities. In this paper, we propose a model of liquid flow to determine the rates of filling the defect cavities with various materials and, based on this, to choose optimal control modes.

ADVANCED SEISMIC BASE ISOLATION METHODS FOR MODULAR REACTORS

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

E. Blanford; E. Keldrauk; M. Laufer

2010-09-20

Advanced technologies for structural design and construction have the potential for major impact not only on nuclear power plant construction time and cost, but also on the design process and on the safety, security and reliability of next generation of nuclear power plants. In future Generation IV (Gen IV) reactors, structural and seismic design should be much more closely integrated with the design of nuclear and industrial safety systems, physical security systems, and international safeguards systems. Overall reliability will be increased, through the use of replaceable and modular equipment, and through design to facilitate on-line monitoring, in-service inspection, maintenance, replacement,more » and decommissioning. Economics will also receive high design priority, through integrated engineering efforts to optimize building arrangements to minimize building heights and footprints. Finally, the licensing approach will be transformed by becoming increasingly performance based and technology neutral, using best-estimate simulation methods with uncertainty and margin quantification. In this context, two structural engineering technologies, seismic base isolation and modular steel-plate/concrete composite structural walls, are investigated. These technologies have major potential to (1) enable standardized reactor designs to be deployed across a wider range of sites, (2) reduce the impact of uncertainties related to site-specific seismic conditions, and (3) alleviate reactor equipment qualification requirements. For Gen IV reactors the potential for deliberate crashes of large aircraft must also be considered in design. This report concludes that base-isolated structures should be decoupled from the reactor external event exclusion system. As an example, a scoping analysis is performed for a rectangular, decoupled external event shell designed as a grillage. This report also reviews modular construction technology, particularly steel-plate/concrete construction using factory prefabricated structural modules, for application to external event shell and base isolated structures.« less

Towards computational materials design from first principles using alchemical changes and derivatives.

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

von Lilienfeld-Toal, Otto Anatole

2010-11-01

The design of new materials with specific physical, chemical, or biological properties is a central goal of much research in materials and medicinal sciences. Except for the simplest and most restricted cases brute-force computational screening of all possible compounds for interesting properties is beyond any current capacity due to the combinatorial nature of chemical compound space (set of stoichiometries and configurations). Consequently, when it comes to computationally optimizing more complex systems, reliable optimization algorithms must not only trade-off sufficient accuracy and computational speed of the models involved, they must also aim for rapid convergence in terms of number of compoundsmore » 'visited'. I will give an overview on recent progress on alchemical first principles paths and gradients in compound space that appear to be promising ingredients for more efficient property optimizations. Specifically, based on molecular grand canonical density functional theory an approach will be presented for the construction of high-dimensional yet analytical property gradients in chemical compound space. Thereafter, applications to molecular HOMO eigenvalues, catalyst design, and other problems and systems shall be discussed.« less

Managing Reliability in the 21st Century

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

Dellin, T.A.

1998-11-23

The rapid pace of change at Ike end of the 20th Century should continue unabated well into the 21st Century. The driver will be the marketplace imperative of "faster, better, cheaper." This imperative has already stimulated a revolution-in-engineering in design and manufacturing. In contrast, to date, reliability engineering has not undergone a similar level of change. It is critical that we implement a corresponding revolution-in-reliability-engineering as we enter the new millennium. If we are still using 20th Century reliability approaches in the 21st Century, then reliability issues will be the limiting factor in faster, better, and cheaper. At the heartmore » of this reliability revolution will be a science-based approach to reliability engineering. Science-based reliability will enable building-in reliability, application-specific products, virtual qualification, and predictive maintenance. The purpose of this paper is to stimulate a dialogue on the future of reliability engineering. We will try to gaze into the crystal ball and predict some key issues that will drive reliability programs in the new millennium. In the 21st Century, we will demand more of our reliability programs. We will need the ability to make accurate reliability predictions that will enable optimizing cost, performance and time-to-market to meet the needs of every market segment. We will require that all of these new capabilities be in place prior to the stint of a product development cycle. The management of reliability programs will be driven by quantifiable metrics of value added to the organization business objectives.« less

Reliability, Risk and Cost Trade-Offs for Composite Designs

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.

1996-01-01

Risk and cost trade-offs have been simulated using a probabilistic method. The probabilistic method accounts for all naturally-occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry and loading conditions. The probability density function of first buckling load for a set of uncertain variables is computed. The probabilistic sensitivity factors of uncertain variables to the first buckling load is calculated. The reliability-based cost for a composite fuselage panel is defined and minimized with respect to requisite design parameters. The optimization is achieved by solving a system of nonlinear algebraic equations whose coefficients are functions of probabilistic sensitivity factors. With optimum design parameters such as the mean and coefficient of variation (representing range of scatter) of uncertain variables, the most efficient and economical manufacturing procedure can be selected. In this paper, optimum values of the requisite design parameters for a predetermined cost due to failure occurrence are computationally determined. The results for the fuselage panel analysis show that the higher the cost due to failure occurrence, the smaller the optimum coefficient of variation of fiber modulus (design parameter) in longitudinal direction.

WE-EF-207-03: Design and Optimization of a CBCT Head Scanner for Detection of Acute Intracranial Hemorrhage

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

Xu, J; Sisniega, A; Zbijewski, W

Purpose: To design a dedicated x-ray cone-beam CT (CBCT) system suitable to deployment at the point-of-care and offering reliable detection of acute intracranial hemorrhage (ICH), traumatic brain injury (TBI), stroke, and other head and neck injuries. Methods: A comprehensive task-based image quality model was developed to guide system design and optimization of a prototype head scanner suitable to imaging of acute TBI and ICH. Previously reported models were expanded to include the effects of x-ray scatter correction necessary for detection of low contrast ICH and the contribution of bit depth (digitization noise) to imaging performance. Task-based detectablity index provided themore » objective function for optimization of system geometry, x-ray source, detector type, anti-scatter grid, and technique at 10–25 mGy dose. Optimal characteristics were experimentally validated using a custom head phantom with 50 HU contrast ICH inserts imaged on a CBCT imaging bench allowing variation of system geometry, focal spot size, detector, grid selection, and x-ray technique. Results: The model guided selection of system geometry with a nominal source-detector distance 1100 mm and optimal magnification of 1.50. Focal spot size ∼0.6 mm was sufficient for spatial resolution requirements in ICH detection. Imaging at 90 kVp yielded the best tradeoff between noise and contrast. The model provided quantitation of tradeoffs between flat-panel and CMOS detectors with respect to electronic noise, field of view, and readout speed required for imaging of ICH. An anti-scatter grid was shown to provide modest benefit in conjunction with post-acquisition scatter correction. Images of the head phantom demonstrate visualization of millimeter-scale simulated ICH. Conclusions: Performance consistent with acute TBI and ICH detection is feasible with model-based system design and robust artifact correction in a dedicated head CBCT system. Further improvements can be achieved with incorporation of model-based iterative reconstruction techniques also within the scope of the task-based optimization framework. David Foos and Xiaohui Wang are employees of Carestream Health.« less

Evaluating the Effect of Minimizing Screws on Stabilization of Symphysis Mandibular Fracture by 3D Finite Element Analysis.

PubMed

Kharmanda, Ghias; Kharma, Mohamed-Yaser

2017-06-01

The objective of this work is to integrate structural optimization and reliability concepts into mini-plate fixation strategy used in symphysis mandibular fractures. The structural reliability levels are next estimated when considering a single failure mode and multiple failure modes. A 3-dimensional finite element model is developed in order to evaluate the ability of reducing the negative effect due to the stabilization of the fracture. Topology optimization process is considered in the conceptual design stage to predict possible fixation layouts. In the detailed design stage, suitable mini-plates are selected taking into account the resulting topology and different anatomical considerations. Several muscle forces are considered in order to obtain realistic predictions. Since some muscles can be cut or harmed during the surgery and cannot operate at its maximum capacity, there is a strong motivation to introduce the loading uncertainties in order to obtain reliable designs. The structural reliability is carried out for a single failure mode and multiple failure modes. The different results are validated with a clinical case of a male patient with symphysis fracture. In this case while use of the upper plate fixation with four holes, only two screws were applied to protect adjacent vital structure. This behavior does not affect the stability of the fracture. The proposed strategy to optimize bone plates leads to fewer complications and second surgeries, less patient discomfort, and shorter time of healing.

SEEK: A FORTRAN optimization program using a feasible directions gradient search

NASA Technical Reports Server (NTRS)

Savage, M.

1995-01-01

This report describes the use of computer program 'SEEK' which works in conjunction with two user-written subroutines and an input data file to perform an optimization procedure on a user's problem. The optimization method uses a modified feasible directions gradient technique. SEEK is written in ANSI standard Fortran 77, has an object size of about 46K bytes, and can be used on a personal computer running DOS. This report describes the use of the program and discusses the optimizing method. The program use is illustrated with four example problems: a bushing design, a helical coil spring design, a gear mesh design, and a two-parameter Weibull life-reliability curve fit.

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

PubMed

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

2011-04-04

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

New Vistas in Chemical Product and Process Design.

PubMed

Zhang, Lei; Babi, Deenesh K; Gani, Rafiqul

2016-06-07

Design of chemicals-based products is broadly classified into those that are process centered and those that are product centered. In this article, the designs of both classes of products are reviewed from a process systems point of view; developments related to the design of the chemical product, its corresponding process, and its integration are highlighted. Although significant advances have been made in the development of systematic model-based techniques for process design (also for optimization, operation, and control), much work is needed to reach the same level for product design. Timeline diagrams illustrating key contributions in product design, process design, and integrated product-process design are presented. The search for novel, innovative, and sustainable solutions must be matched by consideration of issues related to the multidisciplinary nature of problems, the lack of data needed for model development, solution strategies that incorporate multiscale options, and reliability versus predictive power. The need for an integrated model-experiment-based design approach is discussed together with benefits of employing a systematic computer-aided framework with built-in design templates.

EUVL back-insertion layout optimization

NASA Astrophysics Data System (ADS)

Civay, D.; Laffosse, E.; Chesneau, A.

2018-03-01

Extreme ultraviolet lithography (EUVL) is targeted for front-up insertion at advanced technology nodes but will be evaluated for back insertion at more mature nodes. EUVL can put two or more mask levels back on one mask, depending upon what level(s) in the process insertion occurs. In this paper, layout optimization methods are discussed that can be implemented when EUVL back insertion is implemented. The layout optimizations can be focused on improving yield, reliability or density, depending upon the design needs. The proposed methodology modifies the original two or more colored layers and generates an optimized single color EUVL layout design.

Reliability Constrained Priority Load Shedding for Aerospace Power System Automation

NASA Technical Reports Server (NTRS)

Momoh, James A.; Zhu, Jizhong; Kaddah, Sahar S.; Dolce, James L. (Technical Monitor)

2000-01-01

The need for improving load shedding on board the space station is one of the goals of aerospace power system automation. To accelerate the optimum load-shedding functions, several constraints must be involved. These constraints include congestion margin determined by weighted probability contingency, component/system reliability index, generation rescheduling. The impact of different faults and indices for computing reliability were defined before optimization. The optimum load schedule is done based on priority, value and location of loads. An optimization strategy capable of handling discrete decision making, such as Everett optimization, is proposed. We extended Everett method to handle expected congestion margin and reliability index as constraints. To make it effective for real time load dispatch process, a rule-based scheme is presented in the optimization method. It assists in selecting which feeder load to be shed, the location of the load, the value, priority of the load and cost benefit analysis of the load profile is included in the scheme. The scheme is tested using a benchmark NASA system consisting of generators, loads and network.

Design optimization for cost and quality: The robust design approach

NASA Technical Reports Server (NTRS)

Unal, Resit

1990-01-01

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

Toward reliable and repeatable automated STEM-EDS metrology with high throughput

NASA Astrophysics Data System (ADS)

Zhong, Zhenxin; Donald, Jason; Dutrow, Gavin; Roller, Justin; Ugurlu, Ozan; Verheijen, Martin; Bidiuk, Oleksii

2018-03-01

New materials and designs in complex 3D architectures in logic and memory devices have raised complexity in S/TEM metrology. In this paper, we report about a newly developed, automated, scanning transmission electron microscopy (STEM) based, energy dispersive X-ray spectroscopy (STEM-EDS) metrology method that addresses these challenges. Different methodologies toward repeatable and efficient, automated STEM-EDS metrology with high throughput are presented: we introduce the best known auto-EDS acquisition and quantification methods for robust and reliable metrology and present how electron exposure dose impacts the EDS metrology reproducibility, either due to poor signalto-noise ratio (SNR) at low dose or due to sample modifications at high dose conditions. Finally, we discuss the limitations of the STEM-EDS metrology technique and propose strategies to optimize the process both in terms of throughput and metrology reliability.

Design, optimization, and analysis of a self-deploying PV tent array

NASA Astrophysics Data System (ADS)

Collozza, Anthony J.

1991-06-01

A tent shaped PV array was designed and the design was optimized for maximum specific power. In order to minimize output power variation a tent angle of 60 deg was chosen. Based on the chosen tent angle an array structure was designed. The design considerations were minimal deployment time, high reliability, and small stowage volume. To meet these considerations the array was chosen to be self-deployable, form a compact storage configuration, using a passive pressurized gas deployment mechanism. Each structural component of the design was analyzed to determine the size necessary to withstand the various forces to which it would be subjected. Through this analysis the component weights were determined. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power for a given PV blanket. This optimization was performed for both lunar and Martian environmental conditions. Other factors such as PV blanket types, structural material, and wind velocity (for Mars array), were varied to determine what influence they had on the design point. The performance specifications for the array at both locations and with each type of PV blanket were determined. These specifications were calculated using the Arimid fiber composite as the structural material. The four PV blanket types considered were silicon, GaAs/Ge, GaAsCLEFT, and amorphous silicon. The specifications used for each blanket represented either present day or near term technology. For both the Moon and Mars the amorphous silicon arrays produced the highest specific power.

ANSYS-Based Simulation and Optimization on Temperature Field of Amorphous Ingot Made by Water Quenching

NASA Astrophysics Data System (ADS)

Zhao, W.; Sun, Z.; Tang, Z.; Liaw, P. K.; Li, J.; Liu, R. P.; Li, Gong

2014-05-01

2D finite element analysis was conducted on the temperature field to create an amorphous ingot by vacuum water quenching. An optimized analysis document was then written by ANSYS parametric design language, and the optimal design modules of ANSYS were used to study the inside diameter and wall thickness of the quartz tube, as well as the water temperature. The microstructure and the phase structure of the amorphous ingot were evaluated by scanning electron microscopy and X-ray diffraction, respectively. Results show that during the cooling process, the thinner wall thickness, smaller diameter of the ingot, or lower temperature of the water environment can result in higher cooling rate at a given temperature. Besides, the gap between the different cooling rates induced by wall thickness or diameter of the ingot narrows down as the temperature decreases, and the gap between the different cooling rates induced by temperature of the water environment remains constant. The process parameters in creating an amorphous ingot, which is optimized by the finite element analysis on the temperature field, are reliable.

Determining the psychometric properties of the Enhancing Decision-making Assessment in Midwifery (EDAM) measure in a cross cultural context.

PubMed

Jefford, Elaine; Jomeen, Julie; Martin, Colin R

2016-04-28

The ability to act on and justify clinical decisions as autonomous accountable midwifery practitioners, is encompassed within many international regulatory frameworks, yet decision-making within midwifery is poorly defined. Decision-making theories from medicine and nursing may have something to offer, but fail to take into consideration midwifery context and philosophy and the decisional autonomy of women. Using an underpinning qualitative methodology, a decision-making framework was developed, which identified Good Clinical Reasoning and Good Midwifery Practice as two conditions necessary to facilitate optimal midwifery decision-making during 2nd stage labour. This study aims to confirm the robustness of the framework and describe the development of Enhancing Decision-making Assessment in Midwifery (EDAM) as a measurement tool through testing of its factor structure, validity and reliability. A cross-sectional design for instrument development and a 2 (country; Australia/UK) x 2 (Decision-making; optimal/sub-optimal) between-subjects design for instrument evaluation using exploratory and confirmatory factor analysis, internal consistency and known-groups validity. Two 'expert' maternity panels, based in Australia and the UK, comprising of 42 participants assessed 16 midwifery real care episode vignettes using the empirically derived 26 item framework. Each item was answered on a 5 point likert scale based on the level of agreement to which the participant felt each item was present in each of the vignettes. Participants were then asked to rate the overall decision-making (optimal/sub-optimal). Post factor analysis the framework was reduced to a 19 item EDAM measure, and confirmed as two distinct scales of 'Clinical Reasoning' (CR) and 'Midwifery Practice' (MP). The CR scale comprised of two subscales; 'the clinical reasoning process' and 'integration and intervention'. The MP scale also comprised two subscales; women's relationship with the midwife' and 'general midwifery practice'. EDAM would generally appear to be a robust, valid and reliable psychometric instrument for measuring midwifery decision-making, which performs consistently across differing international contexts. The 'women's relationship with midwife' subscale marginally failed to meet the threshold for determining good instrument reliability, which may be due to its brevity. Further research using larger samples and in a wider international context to confirm the veracity of the instrument's measurement properties and its wider global utility, would be advantageous.

Microgrid Design Analysis Using Technology Management Optimization and the Performance Reliability Model

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

Stamp, Jason E.; Eddy, John P.; Jensen, Richard P.

Microgrids are a focus of localized energy production that support resiliency, security, local con- trol, and increased access to renewable resources (among other potential benefits). The Smart Power Infrastructure Demonstration for Energy Reliability and Security (SPIDERS) Joint Capa- bility Technology Demonstration (JCTD) program between the Department of Defense (DOD), Department of Energy (DOE), and Department of Homeland Security (DHS) resulted in the pre- liminary design and deployment of three microgrids at military installations. This paper is focused on the analysis process and supporting software used to determine optimal designs for energy surety microgrids (ESMs) in the SPIDERS project. There aremore » two key pieces of software, an ex- isting software application developed by Sandia National Laboratories (SNL) called Technology Management Optimization (TMO) and a new simulation developed for SPIDERS called the per- formance reliability model (PRM). TMO is a decision support tool that performs multi-objective optimization over a mixed discrete/continuous search space for which the performance measures are unrestricted in form. The PRM is able to statistically quantify the performance and reliability of a microgrid operating in islanded mode (disconnected from any utility power source). Together, these two software applications were used as part of the ESM process to generate the preliminary designs presented by SNL-led DOE team to the DOD. Acknowledgements Sandia National Laboratories and the SPIDERS technical team would like to acknowledge the following for help in the project: * Mike Hightower, who has been the key driving force for Energy Surety Microgrids * Juan Torres and Abbas Akhil, who developed the concept of microgrids for military instal- lations * Merrill Smith, U.S. Department of Energy SPIDERS Program Manager * Ross Roley and Rich Trundy from U.S. Pacific Command * Bill Waugaman and Bill Beary from U.S. Northern Command * Tarek Abdallah, Melanie Johnson, and Harold Sanborn of the U.S. Army Corps of Engineers Construction Engineering Research Laboratory * Colleagues from Sandia National Laboratories (SNL) for their reviews, suggestions, and participation in the work.« less

Reliability-based optimization of maintenance scheduling of mechanical components under fatigue

PubMed Central

Beaurepaire, P.; Valdebenito, M.A.; Schuëller, G.I.; Jensen, H.A.

2012-01-01

This study presents the optimization of the maintenance scheduling of mechanical components under fatigue loading. The cracks of damaged structures may be detected during non-destructive inspection and subsequently repaired. Fatigue crack initiation and growth show inherent variability, and as well the outcome of inspection activities. The problem is addressed under the framework of reliability based optimization. The initiation and propagation of fatigue cracks are efficiently modeled using cohesive zone elements. The applicability of the method is demonstrated by a numerical example, which involves a plate with two holes subject to alternating stress. PMID:23564979

Evidence-based approach to assess passive diffusion and carrier-mediated drug transport.

PubMed

Di, Li; Artursson, Per; Avdeef, Alex; Ecker, Gerhard F; Faller, Bernard; Fischer, Holger; Houston, J Brian; Kansy, Manfred; Kerns, Edward H; Krämer, Stefanie D; Lennernäs, Hans; Sugano, Kiyohiko

2012-08-01

Evidence supporting the action of passive diffusion and carrier-mediated (CM) transport in drug bioavailability and disposition is discussed to refute the recently proposed theory that drug transport is CM-only and that new transporters will be discovered that possess transport characteristics ascribed to passive diffusion. Misconceptions and faulty speculations are addressed to provide reliable guidance on choosing appropriate tools for drug design and optimization. Copyright © 2012 Elsevier Ltd. All rights reserved.

Design and Performance Evaluation of a 200 deg C Interleaved Boost Converter (Preprint)

DTIC Science & Technology

2012-09-01

applications in which longer life operation is desired, SiC die are brazed in metal TO-257 hermetic packages, which do provide superior high temperature ...reliability. Optimization of a high temperature X-perm core based coupled inductor architecture, in terms of ac flux balancing and dc flux cancellation...by ~60% due to the rapid decline in X7R capacitance at the high temperature extreme. The results obtained during this study suggest that the

Operation and planning of coordinated natural gas and electricity infrastructures

NASA Astrophysics Data System (ADS)

Zhang, Xiaping

Natural gas is becoming rapidly the optimal choice for fueling new generating units in electric power system driven by abundant natural gas supplies and environmental regulations that are expected to cause coal-fired generation retirements. The growing reliance on natural gas as a dominant fuel for electricity generation throughout North America has brought the interaction between the natural gas and power grids into sharp focus. The primary concern and motivation of this research is to address the emerging interdependency issues faced by the electric power and natural gas industry. This thesis provides a comprehensive analysis of the interactions between the two systems regarding the short-term operation and long-term infrastructure planning. Natural gas and renewable energy appear complementary in many respects regarding fuel price and availability, environmental impact, resource distribution and dispatchability. In addition, demand response has also held the promise of making a significant contribution to enhance system operations by providing incentives to customers for a more flat load profile. We investigated the coordination between natural gas-fired generation and prevailing nontraditional resources including renewable energy, demand response so as to provide economical options for optimizing the short-term scheduling with the intense natural gas delivery constraints. As the amount and dispatch of gas-fired generation increases, the long-term interdependency issue is whether there is adequate pipeline capacity to provide sufficient gas to natural gas-fired generation during the entire planning horizon while it is widely used outside the power sector. This thesis developed a co-optimization planning model by incorporating the natural gas transportation system into the multi-year resource and transmission system planning problem. This consideration would provide a more comprehensive decision for the investment and accurate assessment for system adequacy and reliability. With the growing reliance on natural gas and widespread utilization of highly efficient combined heat and power (CHP), it is also questionable that whether the independent design of infrastructures can meet potential challenges of future energy supply. To address this issue, this thesis proposed an optimization framework for a sustainable multiple energy system expansion planning based on an energy hub model while considering the energy efficiency, emission and reliability performance. In addition, we introduced the probabilistic reliability evaluation and flow network analysis into the multiple energy system design in order to obtain an optimal and reliable network topology.

Reducing random measurement error in assessing postural load on the back in epidemiologic surveys.

PubMed

Burdorf, A

1995-02-01

The goal of this study was to design strategies to assess postural load on the back in occupational epidemiology by taking into account the reliability of measurement methods and the variability of exposure among the workers under study. Intermethod reliability studies were evaluated to estimate the systematic bias (accuracy) and random measurement error (precision) of various methods to assess postural load on the back. Intramethod reliability studies were reviewed to estimate random variability of back load over time. Intermethod surveys have shown that questionnaires have a moderate reliability for gross activities such as sitting, whereas duration of trunk flexion and rotation should be assessed by observation methods or inclinometers. Intramethod surveys indicate that exposure variability can markedly affect the reliability of estimates of back load if the estimates are based upon a single measurement over a certain time period. Equations have been presented to evaluate various study designs according to the reliability of the measurement method, the optimum allocation of the number of repeated measurements per subject, and the number of subjects in the study. Prior to a large epidemiologic study, an exposure-oriented survey should be conducted to evaluate the performance of measurement instruments and to estimate sources of variability for back load. The strategy for assessing back load can be optimized by balancing the number of workers under study and the number of repeated measurements per worker.

Designing a reliable leak bio-detection system for natural gas pipelines.

PubMed

Batzias, F A; Siontorou, C G; Spanidis, P-M P

2011-02-15

Monitoring of natural gas (NG) pipelines is an important task for economical/safety operation, loss prevention and environmental protection. Timely and reliable leak detection of gas pipeline, therefore, plays a key role in the overall integrity management for the pipeline system. Owing to the various limitations of the currently available techniques and the surveillance area that needs to be covered, the research on new detector systems is still thriving. Biosensors are worldwide considered as a niche technology in the environmental market, since they afford the desired detector capabilities at low cost, provided they have been properly designed/developed and rationally placed/networked/maintained by the aid of operational research techniques. This paper addresses NG leakage surveillance through a robust cooperative/synergistic scheme between biosensors and conventional detector systems; the network is validated in situ and optimized in order to provide reliable information at the required granularity level. The proposed scheme is substantiated through a knowledge based approach and relies on Fuzzy Multicriteria Analysis (FMCA), for selecting the best biosensor design that suits both, the target analyte and the operational micro-environment. This approach is illustrated in the design of leak surveying over a pipeline network in Greece. Copyright © 2010 Elsevier B.V. All rights reserved.

Optimal PGU operation strategy in CHP systems

NASA Astrophysics Data System (ADS)

Yun, Kyungtae

Traditional power plants only utilize about 30 percent of the primary energy that they consume, and the rest of the energy is usually wasted in the process of generating or transmitting electricity. On-site and near-site power generation has been considered by business, labor, and environmental groups to improve the efficiency and the reliability of power generation. Combined heat and power (CHP) systems are a promising alternative to traditional power plants because of the high efficiency and low CO2 emission achieved by recovering waste thermal energy produced during power generation. A CHP operational algorithm designed to optimize operational costs must be relatively simple to implement in practice such as to minimize the computational requirements from the hardware to be installed. This dissertation focuses on the following aspects pertaining the design of a practical CHP operational algorithm designed to minimize the operational costs: (a) real-time CHP operational strategy using a hierarchical optimization algorithm; (b) analytic solutions for cost-optimal power generation unit operation in CHP Systems; (c) modeling of reciprocating internal combustion engines for power generation and heat recovery; (d) an easy to implement, effective, and reliable hourly building load prediction algorithm.

Design of a sensor network for structural health monitoring of a full-scale composite horizontal tail

NASA Astrophysics Data System (ADS)

Gao, Dongyue; Wang, Yishou; Wu, Zhanjun; Rahim, Gorgin; Bai, Shengbao

2014-05-01

The detection capability of a given structural health monitoring (SHM) system strongly depends on its sensor network placement. In order to minimize the number of sensors while maximizing the detection capability, optimal design of the PZT sensor network placement is necessary for structural health monitoring (SHM) of a full-scale composite horizontal tail. In this study, the sensor network optimization was simplified as a problem of determining the sensor array placement between stiffeners to achieve the desired the coverage rate. First, an analysis of the structural layout and load distribution of a composite horizontal tail was performed. The constraint conditions of the optimal design were presented. Then, the SHM algorithm of the composite horizontal tail under static load was proposed. Based on the given SHM algorithm, a sensor network was designed for the full-scale composite horizontal tail structure. Effective profiles of cross-stiffener paths (CRPs) and uncross-stiffener paths (URPs) were estimated by a Lamb wave propagation experiment in a multi-stiffener composite specimen. Based on the coverage rate and the redundancy requirements, a seven-sensor array-network was chosen as the optimal sensor network for each airfoil. Finally, a preliminary SHM experiment was performed on a typical composite aircraft structure component. The reliability of the SHM result for a composite horizontal tail structure under static load was validated. In the result, the red zone represented the delamination damage. The detection capability of the optimized sensor network was verified by SHM of a full-scale composite horizontal tail; all the diagnosis results were obtained in two minutes. The result showed that all the damage in the monitoring region was covered by the sensor network.

Reduced Design Load Basis for Ultimate Blade Loads Estimation in Multidisciplinary Design Optimization Frameworks

NASA Astrophysics Data System (ADS)

Pavese, Christian; Tibaldi, Carlo; Larsen, Torben J.; Kim, Taeseong; Thomsen, Kenneth

2016-09-01

The aim is to provide a fast and reliable approach to estimate ultimate blade loads for a multidisciplinary design optimization (MDO) framework. For blade design purposes, the standards require a large amount of computationally expensive simulations, which cannot be efficiently run each cost function evaluation of an MDO process. This work describes a method that allows integrating the calculation of the blade load envelopes inside an MDO loop. Ultimate blade load envelopes are calculated for a baseline design and a design obtained after an iteration of an MDO. These envelopes are computed for a full standard design load basis (DLB) and a deterministic reduced DLB. Ultimate loads extracted from the two DLBs with the two blade designs each are compared and analyzed. Although the reduced DLB supplies ultimate loads of different magnitude, the shape of the estimated envelopes are similar to the one computed using the full DLB. This observation is used to propose a scheme that is computationally cheap, and that can be integrated inside an MDO framework, providing a sufficiently reliable estimation of the blade ultimate loading. The latter aspect is of key importance when design variables implementing passive control methodologies are included in the formulation of the optimization problem. An MDO of a 10 MW wind turbine blade is presented as an applied case study to show the efficacy of the reduced DLB concept.

Reliability and Productivity Modeling for the Optimization of Separated Spacecraft Interferometers

NASA Technical Reports Server (NTRS)

Kenny, Sean (Technical Monitor); Wertz, Julie

2002-01-01

As technological systems grow in capability, they also grow in complexity. Due to this complexity, it is no longer possible for a designer to use engineering judgement to identify the components that have the largest impact on system life cycle metrics, such as reliability, productivity, cost, and cost effectiveness. One way of identifying these key components is to build quantitative models and analysis tools that can be used to aid the designer in making high level architecture decisions. Once these key components have been identified, two main approaches to improving a system using these components exist: add redundancy or improve the reliability of the component. In reality, the most effective approach to almost any system will be some combination of these two approaches, in varying orders of magnitude for each component. Therefore, this research tries to answer the question of how to divide funds, between adding redundancy and improving the reliability of components, to most cost effectively improve the life cycle metrics of a system. While this question is relevant to any complex system, this research focuses on one type of system in particular: Separate Spacecraft Interferometers (SSI). Quantitative models are developed to analyze the key life cycle metrics of different SSI system architectures. Next, tools are developed to compare a given set of architectures in terms of total performance, by coupling different life cycle metrics together into one performance metric. Optimization tools, such as simulated annealing and genetic algorithms, are then used to search the entire design space to find the "optimal" architecture design. Sensitivity analysis tools have been developed to determine how sensitive the results of these analyses are to uncertain user defined parameters. Finally, several possibilities for the future work that could be done in this area of research are presented.

Rolling Contact Fatigue Life and Spall Propagation Characteristics of AISI M50, M50 NiL, and AISI 52100. Part 1. Experimental Results (Preprint)

DTIC Science & Technology

2009-10-01

phase and factors which may cause accelerated growth rates is key to achieving a reliable and robust bearing design . The end goal is to identify...key to achieving a reliable and robust bearing design . The end goal is to identify control parameters for optimizing bearing materials for improved...25.0 nm and were each fabricated from same material heats respectively to a custom design print to ABEC 5 quality and had split inner rings. Each had

Nodal failure index approach to groundwater remediation design

USGS Publications Warehouse

Lee, J.; Reeves, H.W.; Dowding, C.H.

2008-01-01

Computer simulations often are used to design and to optimize groundwater remediation systems. We present a new computationally efficient approach that calculates the reliability of remedial design at every location in a model domain with a single simulation. The estimated reliability and other model information are used to select a best remedial option for given site conditions, conceptual model, and available data. To evaluate design performance, we introduce the nodal failure index (NFI) to determine the number of nodal locations at which the probability of success is below the design requirement. The strength of the NFI approach is that selected areas of interest can be specified for analysis and the best remedial design determined for this target region. An example application of the NFI approach using a hypothetical model shows how the spatial distribution of reliability can be used for a decision support system in groundwater remediation design. ?? 2008 ASCE.

Functionalization of MEMS cantilever beams for interconnect reliability investigation: development practice

NASA Astrophysics Data System (ADS)

Bieniek, T.; Janczyk, G.; Dobrowolski, R.; Wojciechowska, K.; Malinowska, A.; Panas, A.; Nieprzecki, M.; Kłos, H.

2016-11-01

This paper covers research results on development of the cantilevers beams test structures for interconnects reliability and robustness investigation. Presented results include design, modelling, simulation, optimization and finally fabrication stage performed on 4 inch Si wafers using the ITE microfabrication facility. This paper also covers experimental results from the test structures characterization.

Optimisation study of a vehicle bumper subsystem with fuzzy parameters

NASA Astrophysics Data System (ADS)

Farkas, L.; Moens, D.; Donders, S.; Vandepitte, D.

2012-10-01

This paper deals with the design and optimisation for crashworthiness of a vehicle bumper subsystem, which is a key scenario for vehicle component design. The automotive manufacturers and suppliers have to find optimal design solutions for such subsystems that comply with the conflicting requirements of the regulatory bodies regarding functional performance (safety and repairability) and regarding the environmental impact (mass). For the bumper design challenge, an integrated methodology for multi-attribute design engineering of mechanical structures is set up. The integrated process captures the various tasks that are usually performed manually, this way facilitating the automated design iterations for optimisation. Subsequently, an optimisation process is applied that takes the effect of parametric uncertainties into account, such that the system level of failure possibility is acceptable. This optimisation process is referred to as possibility-based design optimisation and integrates the fuzzy FE analysis applied for the uncertainty treatment in crash simulations. This process is the counterpart of the reliability-based design optimisation used in a probabilistic context with statistically defined parameters (variabilities).

Optimization of dynamic envelope measurement system for high speed train based on monocular vision

NASA Astrophysics Data System (ADS)

Wu, Bin; Liu, Changjie; Fu, Luhua; Wang, Zhong

2018-01-01

The definition of dynamic envelope curve is the maximum limit outline caused by various adverse effects during the running process of the train. It is an important base of making railway boundaries. At present, the measurement work of dynamic envelope curve of high-speed vehicle is mainly achieved by the way of binocular vision. There are some problems of the present measuring system like poor portability, complicated process and high cost. A new measurement system based on the monocular vision measurement theory and the analysis on the test environment is designed and the measurement system parameters, the calibration of camera with wide field of view, the calibration of the laser plane are designed and optimized in this paper. The accuracy has been verified to be up to 2mm by repeated tests and experimental data analysis. The feasibility and the adaptability of the measurement system is validated. There are some advantages of the system like lower cost, a simpler measurement and data processing process, more reliable data. And the system needs no matching algorithm.

A sensor network based virtual beam-like structure method for fault diagnosis and monitoring of complex structures with Improved Bacterial Optimization

NASA Astrophysics Data System (ADS)

Wang, H.; Jing, X. J.

2017-02-01

This paper proposes a novel method for the fault diagnosis of complex structures based on an optimized virtual beam-like structure approach. A complex structure can be regarded as a combination of numerous virtual beam-like structures considering the vibration transmission path from vibration sources to each sensor. The structural 'virtual beam' consists of a sensor chain automatically obtained by an Improved Bacterial Optimization Algorithm (IBOA). The biologically inspired optimization method (i.e. IBOA) is proposed for solving the discrete optimization problem associated with the selection of the optimal virtual beam for fault diagnosis. This novel virtual beam-like-structure approach needs less or little prior knowledge. Neither does it require stationary response data, nor is it confined to a specific structure design. It is easy to implement within a sensor network attached to the monitored structure. The proposed fault diagnosis method has been tested on the detection of loosening screws located at varying positions in a real satellite-like model. Compared with empirical methods, the proposed virtual beam-like structure method has proved to be very effective and more reliable for fault localization.

Issues and Strategies in Solving Multidisciplinary Optimization Problems

NASA Technical Reports Server (NTRS)

Patnaik, Surya

2013-01-01

Optimization research at NASA Glenn Research Center has addressed the design of structures, aircraft and airbreathing propulsion engines. The accumulated multidisciplinary design activity is collected under a testbed entitled COMETBOARDS. Several issues were encountered during the solution of the problems. Four issues and the strategies adapted for their resolution are discussed. This is followed by a discussion on analytical methods that is limited to structural design application. An optimization process can lead to an inefficient local solution. This deficiency was encountered during design of an engine component. The limitation was overcome through an augmentation of animation into optimization. Optimum solutions obtained were infeasible for aircraft and airbreathing propulsion engine problems. Alleviation of this deficiency required a cascading of multiple algorithms. Profile optimization of a beam produced an irregular shape. Engineering intuition restored the regular shape for the beam. The solution obtained for a cylindrical shell by a subproblem strategy converged to a design that can be difficult to manufacture. Resolution of this issue remains a challenge. The issues and resolutions are illustrated through a set of problems: Design of an engine component, Synthesis of a subsonic aircraft, Operation optimization of a supersonic engine, Design of a wave-rotor-topping device, Profile optimization of a cantilever beam, and Design of a cylindrical shell. This chapter provides a cursory account of the issues. Cited references provide detailed discussion on the topics. Design of a structure can also be generated by traditional method and the stochastic design concept. Merits and limitations of the three methods (traditional method, optimization method and stochastic concept) are illustrated. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions can be produced by all the three methods. The variation in the weight calculated by the methods was found to be modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

Development of a chromatographic method with multi-criteria decision making design for simultaneous determination of nifedipine and atenolol in content uniformity testing.

PubMed

Ahmed, Sameh; Alqurshi, Abdulmalik; Mohamed, Abdel-Maaboud Ismail

2018-07-01

A new robust and reliable high-performance liquid chromatography (HPLC) method with multi-criteria decision making (MCDM) approach was developed to allow simultaneous quantification of atenolol (ATN) and nifedipine (NFD) in content uniformity testing. Felodipine (FLD) was used as an internal standard (I.S.) in this study. A novel marriage between a new interactive response optimizer and a HPLC method was suggested for multiple response optimizations of target responses. An interactive response optimizer was used as a decision and prediction tool for the optimal settings of target responses, according to specified criteria, based on Derringer's desirability. Four independent variables were considered in this study: Acetonitrile%, buffer pH and concentration along with column temperature. Eight responses were optimized: retention times of ATN, NFD, and FLD, resolutions between ATN/NFD and NFD/FLD, and plate numbers for ATN, NFD, and FLD. Multiple regression analysis was applied in order to scan the influences of the most significant variables for the regression models. The experimental design was set to give minimum retention times, maximum resolution and plate numbers. The interactive response optimizer allowed prediction of optimum conditions according to these criteria with a good composite desirability value of 0.98156. The developed method was validated according to the International Conference on Harmonization (ICH) guidelines with the aid of the experimental design. The developed MCDM-HPLC method showed superior robustness and resolution in short analysis time allowing successful simultaneous content uniformity testing of ATN and NFD in marketed capsules. The current work presents an interactive response optimizer as an efficient platform to optimize, predict responses, and validate HPLC methodology with tolerable design space for assay in quality control laboratories. Copyright © 2018 Elsevier B.V. All rights reserved.

Pressure-Aware Control Layer Optimization for Flow-Based Microfluidic Biochips.

PubMed

Wang, Qin; Xu, Yue; Zuo, Shiliang; Yao, Hailong; Ho, Tsung-Yi; Li, Bing; Schlichtmann, Ulf; Cai, Yici

2017-12-01

Flow-based microfluidic biochips are attracting increasing attention with successful biomedical applications. One critical issue with flow-based microfluidic biochips is the large number of microvalves that require peripheral control pins. Even using the broadcasting addressing scheme, i.e., one control pin controls multiple microvalves simultaneously, thousands of microvalves would still require hundreds of control prins, which is unrealistic. To address this critical challenge in control scalability, the control-layer multiplexer is introduced to effectively reduce the number of control pins into log scale of the number of microvalves. There are two practical design issues with the control-layer multiplexer: (1) the reliability issue caused by the frequent control-valve switching, and (2) the pressure degradation problem caused by the control-valve switching without pressure refreshing from the pressure source. This paper addresses these two design issues by the proposed Hamming-distance-based switching sequence optimization method and the XOR-based pressure refreshing method. Simulation results demonstrate the effectiveness and efficiency of the proposed methods with an average 77.2% (maximum 89.6%) improvement in total pressure refreshing cost, and an average 88.5% (maximum 90.0%) improvement in pressure deviation.

Design study and performance analysis of 12S-14P field excitation flux switching motor for hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Husin, Zhafir Aizat; Sulaiman, Erwan; Khan, Faisal; Mazlan, Mohamed Mubin Aizat; Othman, Syed Muhammad Naufal Syed

2015-05-01

This paper presents a new structure of 12slot-14pole field excitation flux switching motor (FEFSM) as an alternative candidate of non-Permanent Magnet (PM) machine for HEV drives. Design study, performance analysis and optimization of field excitation flux switching machine with non-rare-earth magnet for hybrid electric vehicle drive applications is done. The stator of projected machine consists of iron core made of electromagnetic steels, armature coils and field excitation coils as the only field mmf source. The rotor is consisted of only stack of iron and hence, it is reliable and appropriate for high speed operation. The design target is a machine with the maximum torque, power and power density, more than 210Nm, 123kW and 3.5kW/kg, respectively, which competes with interior permanent magnet synchronous machine used in existing hybrid electric vehicle. Some design feasibility studies on FEFSM based on 2D-FEA and deterministic optimization method will be applied to design the proposed machine.

Self-optimizing approach for automated laser resonator alignment

NASA Astrophysics Data System (ADS)

Brecher, C.; Schmitt, R.; Loosen, P.; Guerrero, V.; Pyschny, N.; Pavim, A.; Gatej, A.

2012-02-01

Nowadays, the assembly of laser systems is dominated by manual operations, involving elaborate alignment by means of adjustable mountings. From a competition perspective, the most challenging problem in laser source manufacturing is price pressure, a result of cost competition exerted mainly from Asia. From an economical point of view, an automated assembly of laser systems defines a better approach to produce more reliable units at lower cost. However, the step from today's manual solutions towards an automated assembly requires parallel developments regarding product design, automation equipment and assembly processes. This paper introduces briefly the idea of self-optimizing technical systems as a new approach towards highly flexible automation. Technically, the work focuses on the precision assembly of laser resonators, which is one of the final and most crucial assembly steps in terms of beam quality and laser power. The paper presents a new design approach for miniaturized laser systems and new automation concepts for a robot-based precision assembly, as well as passive and active alignment methods, which are based on a self-optimizing approach. Very promising results have already been achieved, considerably reducing the duration and complexity of the laser resonator assembly. These results as well as future development perspectives are discussed.

An intelligent remote control system for ECEI on EAST

NASA Astrophysics Data System (ADS)

Chen, Dongxu; Zhu, Yilun; Zhao, Zhenling; Qu, Chengming; Liao, Wang; Xie, Jinlin; Liu, Wandong

2017-08-01

An intelligent remote control system based on a power distribution unit (PDU) and Arduino has been designed for the electron cyclotron emission imaging (ECEI) system on Experimental Advanced Superconducting Tokamak (EAST). This intelligent system has three major functions: ECEI system reboot, measurement region adjustment and signal amplitude optimization. The observation region of ECEI can be modified for different physics proposals by remotely tuning the optical and electronics systems. Via the remote adjustment of the attenuation level, the ECEI intermediate frequency signal amplitude can be efficiently optimized. The remote control system provides a feasible and reliable solution for the improvement of signal quality and the efficiency of the ECEI diagnostic system, which is also valuable for other diagnostic systems.

Kuhn-Tucker optimization based reliability analysis for probabilistic finite elements

NASA Technical Reports Server (NTRS)

Liu, W. K.; Besterfield, G.; Lawrence, M.; Belytschko, T.

1988-01-01

The fusion of probability finite element method (PFEM) and reliability analysis for fracture mechanics is considered. Reliability analysis with specific application to fracture mechanics is presented, and computational procedures are discussed. Explicit expressions for the optimization procedure with regard to fracture mechanics are given. The results show the PFEM is a very powerful tool in determining the second-moment statistics. The method can determine the probability of failure or fracture subject to randomness in load, material properties and crack length, orientation, and location.

A Delay-Aware and Reliable Data Aggregation for Cyber-Physical Sensing

PubMed Central

Zhang, Jinhuan; Long, Jun; Zhang, Chengyuan; Zhao, Guihu

2017-01-01

Physical information sensed by various sensors in a cyber-physical system should be collected for further operation. In many applications, data aggregation should take reliability and delay into consideration. To address these problems, a novel Tiered Structure Routing-based Delay-Aware and Reliable Data Aggregation scheme named TSR-DARDA for spherical physical objects is proposed. By dividing the spherical network constructed by dispersed sensor nodes into circular tiers with specifically designed widths and cells, TSTR-DARDA tries to enable as many nodes as possible to transmit data simultaneously. In order to ensure transmission reliability, lost packets are retransmitted. Moreover, to minimize the latency while maintaining reliability for data collection, in-network aggregation and broadcast techniques are adopted to deal with the transmission between data collecting nodes in the outer layer and their parent data collecting nodes in the inner layer. Thus, the optimization problem is transformed to minimize the delay under reliability constraints by controlling the system parameters. To demonstrate the effectiveness of the proposed scheme, we have conducted extensive theoretical analysis and comparisons to evaluate the performance of TSR-DARDA. The analysis and simulations show that TSR-DARDA leads to lower delay with reliability satisfaction. PMID:28218668

LIFESPAN: A tool for the computer-aided design of longitudinal studies

PubMed Central

Brandmaier, Andreas M.; von Oertzen, Timo; Ghisletta, Paolo; Hertzog, Christopher; Lindenberger, Ulman

2015-01-01

Researchers planning a longitudinal study typically search, more or less informally, a multivariate space of possible study designs that include dimensions such as the hypothesized true variance in change, indicator reliability, the number and spacing of measurement occasions, total study time, and sample size. The main search goal is to select a research design that best addresses the guiding questions and hypotheses of the planned study while heeding applicable external conditions and constraints, including time, money, feasibility, and ethical considerations. Because longitudinal study selection ultimately requires optimization under constraints, it is amenable to the general operating principles of optimization in computer-aided design. Based on power equivalence theory (MacCallum et al., 2010; von Oertzen, 2010), we propose a computational framework to promote more systematic searches within the study design space. Starting with an initial design, the proposed framework generates a set of alternative models with equal statistical power to detect hypothesized effects, and delineates trade-off relations among relevant parameters, such as total study time and the number of measurement occasions. We present LIFESPAN (Longitudinal Interactive Front End Study Planner), which implements this framework. LIFESPAN boosts the efficiency, breadth, and precision of the search for optimal longitudinal designs. Its initial version, which is freely available at http://www.brandmaier.de/lifespan, is geared toward the power to detect variance in change as specified in a linear latent growth curve model. PMID:25852596

On the Effectiveness of Nature-Inspired Metaheuristic Algorithms for Performing Phase Equilibrium Thermodynamic Calculations

PubMed Central

Fateen, Seif-Eddeen K.; Bonilla-Petriciolet, Adrian

2014-01-01

The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design. PMID:24967430

On the effectiveness of nature-inspired metaheuristic algorithms for performing phase equilibrium thermodynamic calculations.

PubMed

Fateen, Seif-Eddeen K; Bonilla-Petriciolet, Adrian

2014-01-01

The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolution strategy (CMAES), magnetic charged system search (MCSS), and bare bones particle swarm optimization (BBPSO). The results clearly showed that CS is the most reliable of all methods as it successfully solved all thermodynamic problems tested in this study. CS proved to be a promising nature-inspired optimization method to perform applied thermodynamic calculations for process design.

Optimal Implementations for Reliable Circadian Clocks

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko; Arita, Masanori

2014-09-01

Circadian rhythms are acquired through evolution to increase the chances for survival through synchronizing with the daylight cycle. Reliable synchronization is realized through two trade-off properties: regularity to keep time precisely, and entrainability to synchronize the internal time with daylight. We find by using a phase model with multiple inputs that achieving the maximal limit of regularity and entrainability entails many inherent features of the circadian mechanism. At the molecular level, we demonstrate the role sharing of two light inputs, phase advance and delay, as is well observed in mammals. At the behavioral level, the optimal phase-response curve inevitably contains a dead zone, a time during which light pulses neither advance nor delay the clock. We reproduce the results of phase-controlling experiments entrained by two types of periodic light pulses. Our results indicate that circadian clocks are designed optimally for reliable clockwork through evolution.

Rational Design of an Ultrasensitive Quorum-Sensing Switch.

PubMed

Zeng, Weiqian; Du, Pei; Lou, Qiuli; Wu, Lili; Zhang, Haoqian M; Lou, Chunbo; Wang, Hongli; Ouyang, Qi

2017-08-18

One of the purposes of synthetic biology is to develop rational methods that accelerate the design of genetic circuits, saving time and effort spent on experiments and providing reliably predictable circuit performance. We applied a reverse engineering approach to design an ultrasensitive transcriptional quorum-sensing switch. We want to explore how systems biology can guide synthetic biology in the choice of specific DNA sequences and their regulatory relations to achieve a targeted function. The workflow comprises network enumeration that achieves the target function robustly, experimental restriction of the obtained candidate networks, global parameter optimization via mathematical analysis, selection and engineering of parts based on these calculations, and finally, circuit construction based on the principles of standardization and modularization. The performance of realized quorum-sensing switches was in good qualitative agreement with the computational predictions. This study provides practical principles for the rational design of genetic circuits with targeted functions.

System Analysis and Performance Benefits of an Optimized Rotorcraft Propulsion System

NASA Technical Reports Server (NTRS)

Bruckner, Robert J.

2007-01-01

The propulsion system of rotorcraft vehicles is the most critical system to the vehicle in terms of safety and performance. The propulsion system must provide both vertical lift and forward flight propulsion during the entire mission. Whereas propulsion is a critical element for all flight vehicles, it is particularly critical for rotorcraft due to their limited safe, un-powered landing capability. This unparalleled reliability requirement has led rotorcraft power plants down a certain evolutionary path in which the system looks and performs quite similarly to those of the 1960 s. By and large the advancements in rotorcraft propulsion have come in terms of safety and reliability and not in terms of performance. The concept of the optimized propulsion system is a means by which both reliability and performance can be improved for rotorcraft vehicles. The optimized rotorcraft propulsion system which couples an oil-free turboshaft engine to a highly loaded gearbox that provides axial load support for the power turbine can be designed with current laboratory proven technology. Such a system can provide up to 60% weight reduction of the propulsion system of rotorcraft vehicles. Several technical challenges are apparent at the conceptual design level and should be addressed with current research.

Shape optimization and CAD

NASA Technical Reports Server (NTRS)

Rasmussen, John

1990-01-01

Structural optimization has attracted the attention since the days of Galileo. Olhoff and Taylor have produced an excellent overview of the classical research within this field. However, the interest in structural optimization has increased greatly during the last decade due to the advent of reliable general numerical analysis methods and the computer power necessary to use them efficiently. This has created the possibility of developing general numerical systems for shape optimization. Several authors, eg., Esping; Braibant & Fleury; Bennet & Botkin; Botkin, Yang, and Bennet; and Stanton have published practical and successful applications of general optimization systems. Ding and Homlein have produced extensive overviews of available systems. Furthermore, a number of commercial optimization systems based on well-established finite element codes have been introduced. Systems like ANSYS, IDEAS, OASIS, and NISAOPT are widely known examples. In parallel to this development, the technology of computer aided design (CAD) has gained a large influence on the design process of mechanical engineering. The CAD technology has already lived through a rapid development driven by the drastically growing capabilities of digital computers. However, the systems of today are still considered as being only the first generation of a long row of computer integrated manufacturing (CIM) systems. These systems to come will offer an integrated environment for design, analysis, and fabrication of products of almost any character. Thus, the CAD system could be regarded as simply a database for geometrical information equipped with a number of tools with the purpose of helping the user in the design process. Among these tools are facilities for structural analysis and optimization as well as present standard CAD features like drawing, modeling, and visualization tools. The state of the art of structural optimization is that a large amount of mathematical and mechanical techniques are available for the solution of single problems. By implementing collections of the available techniques into general software systems, operational environments for structural optimization have been created. The forthcoming years must bring solutions to the problem of integrating such systems into more general design environments. The result of this work should be CAD systems for rational design in which structural optimization is one important design tool among many others.

System Reliability-Based Design Optimization Under Input and Model Uncertainties

DTIC Science & Technology

2014-02-02

Standard Form 298 (Rev 8/98) Prescribed by ANSI Std. Z39.18 W911NF-09- 1 -0250 319-335-5684 Final Report 56025-NS.40 a. REPORT 14. ABSTRACT 16...resource. In such cases the inaccuracy and uncertainty of the surrogate model needs to 1 . REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13...estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the

Micro/Nanoscale Parallel Patterning of Functional Biomolecules, Organic Fluorophores and Colloidal Nanocrystals

PubMed Central

2009-01-01

We describe the design and optimization of a reliable strategy that combines self-assembly and lithographic techniques, leading to very precise micro-/nanopositioning of biomolecules for the realization of micro- and nanoarrays of functional DNA and antibodies. Moreover, based on the covalent immobilization of stable and versatile SAMs of programmable chemical reactivity, this approach constitutes a general platform for the parallel site-specific deposition of a wide range of molecules such as organic fluorophores and water-soluble colloidal nanocrystals. PMID:20596482

Resonator design and performance estimation for a space-based laser transmitter

NASA Astrophysics Data System (ADS)

Agrawal, Lalita; Bhardwaj, Atul; Pal, Suranjan; Kamalakar, J. A.

2006-12-01

Development of a laser transmitter for space applications is a highly challenging task. The laser must be rugged, reliable, lightweight, compact and energy efficient. Most of these features are inherently achieved by diode pumping of solid state lasers. Overall system reliability can further be improved by appropriate optical design of the laser resonator besides selection of suitable electro-optical and opto-mechanical components. This paper presents the design details and the theoretically estimated performance of a crossed-porro prism based, folded Z-shaped laser resonator. A symmetrically pumped Nd: YAG laser rod of 3 mm diameter and 60 mm length is placed in the gain arm with total input peak power of 1800 W from laser diode arrays. Electro-optical Q-switching is achieved through a combination of a polarizer, a fractional waveplate and LiNbO 3 Q-switch crystal (9 x 9 x 25 mm) placed in the feedback arm. Polarization coupled output is obtained by optimizing azimuth angle of quarter wave plate placed in the gain arm. Theoretical estimation of laser output energy and pulse width has been carried out by varying input power levels and resonator length to analyse the performance tolerances. The designed system is capable of meeting the objective of generating laser pulses of 10 ns duration and 30 mJ energy @ 10 Hz.

An R package for the design, analysis and operation of reservoir systems

NASA Astrophysics Data System (ADS)

Turner, Sean; Ng, Jia Yi; Galelli, Stefano

2016-04-01

We present a new R package - named "reservoir" - which has been designed for rapid and easy routing of runoff through storage. The package comprises well-established tools for capacity design (e.g., the sequent peak algorithm), performance analysis (storage-yield-reliability and reliability-resilience-vulnerability analysis) and release policy optimization (Stochastic Dynamic Programming). Operating rules can be optimized for water supply, flood control and amenity objectives, as well as for maximum hydropower production. Storage-depth-area relationships are in-built, allowing users to incorporate evaporation from the reservoir surface. We demonstrate the capabilities of the software for global studies using thousands of reservoirs from the Global Reservoir and Dam (GRanD) database fed by historical monthly inflow time series from a 0.5 degree gridded global runoff dataset. The package is freely available through the Comprehensive R Archive Network (CRAN).

Grid sensitivity for aerodynamic optimization and flow analysis

NASA Technical Reports Server (NTRS)

Sadrehaghighi, I.; Tiwari, S. N.

1993-01-01

After reviewing relevant literature, it is apparent that one aspect of aerodynamic sensitivity analysis, namely grid sensitivity, has not been investigated extensively. The grid sensitivity algorithms in most of these studies are based on structural design models. Such models, although sufficient for preliminary or conceptional design, are not acceptable for detailed design analysis. Careless grid sensitivity evaluations, would introduce gradient errors within the sensitivity module, therefore, infecting the overall optimization process. Development of an efficient and reliable grid sensitivity module with special emphasis on aerodynamic applications appear essential. The organization of this study is as follows. The physical and geometric representations of a typical model are derived in chapter 2. The grid generation algorithm and boundary grid distribution are developed in chapter 3. Chapter 4 discusses the theoretical formulation and aerodynamic sensitivity equation. The method of solution is provided in chapter 5. The results are presented and discussed in chapter 6. Finally, some concluding remarks are provided in chapter 7.

Robust Design of Sheet Metal Forming Process Based on Kriging Metamodel

NASA Astrophysics Data System (ADS)

Xie, Yanmin

2011-08-01

Nowadays, sheet metal forming processes design is not a trivial task due to the complex issues to be taken into account (conflicting design goals, complex shapes forming and so on). Optimization methods have also been widely applied in sheet metal forming. Therefore, proper design methods to reduce time and costs have to be developed mostly based on computer aided procedures. At the same time, the existence of variations during manufacturing processes significantly may influence final product quality, rendering non-robust optimal solutions. In this paper, a small size of design of experiments is conducted to investigate how a stochastic behavior of noise factors affects drawing quality. The finite element software (LS_DYNA) is used to simulate the complex sheet metal stamping processes. The Kriging metamodel is adopted to map the relation between input process parameters and part quality. Robust design models for sheet metal forming process integrate adaptive importance sampling with Kriging model, in order to minimize impact of the variations and achieve reliable process parameters. In the adaptive sample, an improved criterion is used to provide direction in which additional training samples can be added to better the Kriging model. Nonlinear functions as test functions and a square stamping example (NUMISHEET'93) are employed to verify the proposed method. Final results indicate application feasibility of the aforesaid method proposed for multi-response robust 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.

Optimally analyzing and implementing of bolt fittings in steel structure based on ANSYS

NASA Astrophysics Data System (ADS)

Han, Na; Song, Shuangyang; Cui, Yan; Wu, Yongchun

2018-03-01

ANSYS simulation software for its excellent performance become outstanding one in Computer-aided Engineering (CAE) family, it is committed to the innovation of engineering simulation to help users to shorten the design process. First, a typical procedure to implement CAE was design. The framework of structural numerical analysis on ANSYS Technology was proposed. Then, A optimally analyzing and implementing of bolt fittings in beam-column join of steel structure was implemented by ANSYS, which was display the cloud chart of XY-shear stress, the cloud chart of YZ-shear stress and the cloud chart of Y component of stress. Finally, ANSYS software simulating results was compared with the measured results by the experiment. The result of ANSYS simulating and analyzing is reliable, efficient and optical. In above process, a structural performance's numerical simulating and analyzing model were explored for engineering enterprises' practice.

Unimodular sequence design under frequency hopping communication compatibility requirements

NASA Astrophysics Data System (ADS)

Ge, Peng; Cui, Guolong; Kong, Lingjiang; Yang, Jianyu

2016-12-01

The integrated design for both radar and anonymous communication has drawn more attention recently since wireless communication system appeals to enhance security and reliability. Given the frequency hopping (FH) communication system, an effective way to realize integrated design is to meet the spectrum compatibility between these two systems. The paper deals with a unimodular sequence design technique which considers optimizing both the spectrum compatibility and peak sidelobes levels (PSL) of auto-correlation function (ACF). The spectrum compatibility requirement realizes anonymous communication for the FH system and provides this system lower probability of intercept (LPI) since the spectrum of the FH system is hidden in that of the radar system. The proposed algorithm, named generalized fitting template (GFT) technique, converts the sequence optimization design problem to a iterative fitting process. In this process, the power spectrum density (PSD) and PSL behaviors of the generated sequences fit both PSD and PSL templates progressively. Two templates are established based on the spectrum compatibility requirement and the expected PSL. As noted, in order to ensure the communication security and reliability, spectrum compatibility requirement is given a higher priority to achieve in the GFT algorithm. This algorithm realizes this point by adjusting the weight adaptively between these two terms during the iteration process. The simulation results are analyzed in terms of bit error rate (BER), PSD, PSL, and signal-interference rate (SIR) for both the radar and FH systems. The performance of GFT is compared with SCAN, CAN, FRE, CYC, and MAT algorithms in the above aspects, which shows its good effectiveness.

Probabilistic framework for product design optimization and risk management

NASA Astrophysics Data System (ADS)

Keski-Rahkonen, J. K.

2018-05-01

Probabilistic methods have gradually gained ground within engineering practices but currently it is still the industry standard to use deterministic safety margin approaches to dimensioning components and qualitative methods to manage product risks. These methods are suitable for baseline design work but quantitative risk management and product reliability optimization require more advanced predictive approaches. Ample research has been published on how to predict failure probabilities for mechanical components and furthermore to optimize reliability through life cycle cost analysis. This paper reviews the literature for existing methods and tries to harness their best features and simplify the process to be applicable in practical engineering work. Recommended process applies Monte Carlo method on top of load-resistance models to estimate failure probabilities. Furthermore, it adds on existing literature by introducing a practical framework to use probabilistic models in quantitative risk management and product life cycle costs optimization. The main focus is on mechanical failure modes due to the well-developed methods used to predict these types of failures. However, the same framework can be applied on any type of failure mode as long as predictive models can be developed.

Defect design of insulation systems for photovoltaic modules

NASA Technical Reports Server (NTRS)

Mon, G. R.

1981-01-01

A defect-design approach to sizing electrical insulation systems for terrestrial photovoltaic modules is presented. It consists of gathering voltage-breakdown statistics on various thicknesses of candidate insulation films where, for a designated voltage, module failure probabilities for enumerated thickness and number-of-layer film combinations are calculated. Cost analysis then selects the most economical insulation system. A manufacturing yield problem is solved to exemplify the technique. Results for unaged Mylar suggest using fewer layers of thicker films. Defect design incorporates effects of flaws in optimal insulation system selection, and obviates choosing a tolerable failure rate, since the optimization process accomplishes that. Exposure to weathering and voltage stress reduces the voltage-withstanding capability of module insulation films. Defect design, applied to aged polyester films, promises to yield reliable, cost-optimal insulation systems.

Receptor-based 3D-QSAR in Drug Design: Methods and Applications in Kinase Studies.

PubMed

Fang, Cheng; Xiao, Zhiyan

2016-01-01

Receptor-based 3D-QSAR strategy represents a superior integration of structure-based drug design (SBDD) and three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis. It combines the accurate prediction of ligand poses by the SBDD approach with the good predictability and interpretability of statistical models derived from the 3D-QSAR approach. Extensive efforts have been devoted to the development of receptor-based 3D-QSAR methods and two alternative approaches have been exploited. One associates with computing the binding interactions between a receptor and a ligand to generate structure-based descriptors for QSAR analyses. The other concerns the application of various docking protocols to generate optimal ligand poses so as to provide reliable molecular alignments for the conventional 3D-QSAR operations. This review highlights new concepts and methodologies recently developed in the field of receptorbased 3D-QSAR, and in particular, covers its application in kinase studies.

The design of electron and ion guns, beams, and collectors

NASA Astrophysics Data System (ADS)

Becker, Reinard; Herrmannsfeldt, William B.

2004-01-01

The well known `SLAC Electron Trajectory Program' (EGUN) has been ported to PCs and has been developed into a family of programs for the design and the optimization of particle optics devices including electron and ion guns, beam transport sections and collectors. We will discuss the application of these tools for the design and the optimization of the essential parts of EBIS/T devices. The discussion will include conditions in which restrictions in the reliability of simulations may occur due to the mathematical modeling and how to overcome them.

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models

PubMed Central

Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra. Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra. PMID:29887907

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models.

PubMed

Yu, Li; Jin, Weifeng; Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra . Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra .

Aeroelastic Modeling of Offshore Turbines and Support Structures in Hurricane-Prone Regions (Poster)

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

Damiani, R.

US offshore wind turbines (OWTs) will likely have to contend with hurricanes and the associated loading conditions. Current industry standards do not account for these design load cases (DLCs), thus a new approach is required to guarantee that the OWTs achieve an appropriate level of reliability. In this study, a sequentially coupled aero-hydro-servo-elastic modeling technique was used to address two design approaches: 1.) The ABS (American Bureau of Shipping) approach; and 2.) The Hazard Curve or API (American Petroleum Institute) approach. The former employs IEC partial load factors (PSFs) and 100-yr return-period (RP) metocean events. The latter allows setting PSFsmore » and RP to a prescribed level of system reliability. The 500-yr RP robustness check (appearing in [2] and [3] upcoming editions) is a good indicator of the target reliability for L2 structures. CAE tools such as NREL's FAST and Bentley's' SACS (offshore analysis and design software) can be efficiently coupled to simulate system loads under hurricane DLCs. For this task, we augmented the latest FAST version (v. 8) to include tower aerodynamic drag that cannot be ignored in hurricane DLCs. In this project, a 6 MW turbine was simulated on a typical 4-legged jacket for a mid-Atlantic site. FAST-calculated tower base loads were fed to SACS at the interface level (transition piece); SACS added hydrodynamic and wind loads on the exposed substructure, and calculated mudline overturning moments, and member and joint utilization. Results show that CAE tools can be effectively used to compare design approaches for the design of OWTs in hurricane regions and to achieve a well-balanced design, where reliability levels and costs are optimized.« less

Development and optimization of a stove-powered thermoelectric generator

NASA Astrophysics Data System (ADS)

Mastbergen, Dan

Almost a third of the world's population still lacks access to electricity. Most of these people use biomass stoves for cooking which produce significant amounts of wasted thermal energy, but no electricity. Less than 1% of this energy in the form of electricity would be adequate for basic tasks such as lighting and communications. However, an affordable and reliable means of accomplishing this is currently nonexistent. The goal of this work is to develop a thermoelectric generator to convert a small amount of wasted heat into electricity. Although this concept has been around for decades, previous attempts have failed due to insufficient analysis of the system as a whole, leading to ineffective and costly designs. In this work, a complete design process is undertaken including concept generation, prototype testing, field testing, and redesign/optimization. Detailed component models are constructed and integrated to create a full system model. The model encompasses the stove operation, thermoelectric module, heat sinks, charging system and battery. A 3000 cycle endurance test was also conducted to evaluate the effects of operating temperature, module quality, and thermal interface quality on the generator's reliability, lifetime and cost effectiveness. The results from this testing are integrated into the system model to determine the lowest system cost in $/Watt over a five year period. Through this work the concept of a stove-based thermoelectric generator is shown to be technologically and economically feasible. In addition, a methodology is developed for optimizing the system for specific regional stove usage habits.

Optimization model of conventional missile maneuvering route based on improved Floyd algorithm

NASA Astrophysics Data System (ADS)

Wu, Runping; Liu, Weidong

2018-04-01

Missile combat plays a crucial role in the victory of war under high-tech conditions. According to the characteristics of maneuver tasks of conventional missile units in combat operations, the factors influencing road maneuvering are analyzed. Based on road distance, road conflicts, launching device speed, position requirements, launch device deployment, Concealment and so on. The shortest time optimization model was built to discuss the situation of road conflict and the strategy of conflict resolution. The results suggest that in the process of solving road conflict, the effect of node waiting is better than detour to another way. In this study, we analyzed the deficiency of the traditional Floyd algorithm which may limit the optimal way of solving road conflict, and put forward the improved Floyd algorithm, meanwhile, we designed the algorithm flow which would be better than traditional Floyd algorithm. Finally, throgh a numerical example, the model and the algorithm were proved to be reliable and effective.

A simplified lumped model for the optimization of post-buckled beam architecture wideband generator

NASA Astrophysics Data System (ADS)

Liu, Weiqun; Formosa, Fabien; Badel, Adrien; Hu, Guangdi

2017-11-01

Buckled beams structures are a classical kind of bistable energy harvesters which attract more and more interests because of their capability to scavenge energy over a large frequency band in comparison with linear generator. The usual modeling approach uses the Galerkin mode discretization method with relatively high complexity, while the simplification with a single-mode solution lacks accuracy. It stems on the optimization of the energy potential features to finally define the physical and geometrical parameters. Therefore, in this paper, a simple lumped model is proposed with explicit relationship between the potential shape and parameters to allow efficient design of bistable beams based generator. The accuracy of the approximation model is studied with the effectiveness of application analyzed. Moreover, an important fact, that the bending stiffness has little influence on the potential shape with low buckling level and the sectional area determined, is found. This feature extends the applicable range of the model by utilizing the design of high moment of inertia. Numerical investigations demonstrate that the proposed model is a simple and reliable tool for design. An optimization example of using the proposed model is demonstrated with satisfactory performance.

Dual-mode ultraflow access networks: a hybrid solution for the access bottleneck

NASA Astrophysics Data System (ADS)

Kazovsky, Leonid G.; Shen, Thomas Shunrong; Dhaini, Ahmad R.; Yin, Shuang; De Leenheer, Marc; Detwiler, Benjamin A.

2013-12-01

Optical Flow Switching (OFS) is a promising solution for large Internet data transfers. In this paper, we introduce UltraFlow Access, a novel optical access network architecture that offers dual-mode service to its end-users: IP and OFS. With UltraFlow Access, we design and implement a new dual-mode control plane and a new dual-mode network stack to ensure efficient connection setup and reliable and optimal data transmission. We study the impact of the UltraFlow system's design on the network throughput. Our experimental results show that with an optimized system design, near optimal (around 10 Gb/s) OFS data throughput can be attained when the line rate is 10Gb/s.

CARES/Life Software for Designing More Reliable Ceramic Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Baker, Eric H.

1997-01-01

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion, and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CAPES/Life software eases this task by providing a tool to optimize the design and manufacture of brittle material components using probabilistic reliability analysis techniques. Probabilistic component design involves predicting the probability of failure for a thermomechanically loaded component from specimen rupture data. Typically, these experiments are performed using many simple geometry flexural or tensile test specimens. A static, dynamic, or cyclic load is applied to each specimen until fracture. Statistical strength and SCG (fatigue) parameters are then determined from these data. Using these parameters and the results obtained from a finite element analysis, the time-dependent reliability for a complex component geometry and loading is then predicted. Appropriate design changes are made until an acceptable probability of failure has been reached.

Reliability and Maintainability Engineering - A Major Driver for Safety and Affordability

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.

2011-01-01

The United States National Aeronautics and Space Administration (NASA) is in the midst of an effort to design and build a safe and affordable heavy lift vehicle to go to the moon and beyond. To achieve that, NASA is seeking more innovative and efficient approaches to reduce cost while maintaining an acceptable level of safety and mission success. One area that has the potential to contribute significantly to achieving NASA safety and affordability goals is Reliability and Maintainability (R&M) engineering. Inadequate reliability or failure of critical safety items may directly jeopardize the safety of the user(s) and result in a loss of life. Inadequate reliability of equipment may directly jeopardize mission success. Systems designed to be more reliable (fewer failures) and maintainable (fewer resources needed) can lower the total life cycle cost. The Department of Defense (DOD) and industry experience has shown that optimized and adequate levels of R&M are critical for achieving a high level of safety and mission success, and low sustainment cost. Also, lessons learned from the Space Shuttle program clearly demonstrated the importance of R&M engineering in designing and operating safe and affordable launch systems. The Challenger and Columbia accidents are examples of the severe impact of design unreliability and process induced failures on system safety and mission success. These accidents demonstrated the criticality of reliability engineering in understanding component failure mechanisms and integrated system failures across the system elements interfaces. Experience from the shuttle program also shows that insufficient Reliability, Maintainability, and Supportability (RMS) engineering analyses upfront in the design phase can significantly increase the sustainment cost and, thereby, the total life cycle cost. Emphasis on RMS during the design phase is critical for identifying the design features and characteristics needed for time efficient processing, improved operational availability, and optimized maintenance and logistic support infrastructure. This paper discusses the role of R&M in a program acquisition phase and the potential impact of R&M on safety, mission success, operational availability, and affordability. This includes discussion of the R&M elements that need to be addressed and the R&M analyses that need to be performed in order to support a safe and affordable system design. The paper also provides some lessons learned from the Space Shuttle program on the impact of R&M on safety and affordability.

Structural Reliability Analysis and Optimization: Use of Approximations

NASA Technical Reports Server (NTRS)

Grandhi, Ramana V.; Wang, Liping

1999-01-01

This report is intended for the demonstration of function approximation concepts and their applicability in reliability analysis and design. Particularly, approximations in the calculation of the safety index, failure probability and structural optimization (modification of design variables) are developed. With this scope in mind, extensive details on probability theory are avoided. Definitions relevant to the stated objectives have been taken from standard text books. The idea of function approximations is to minimize the repetitive use of computationally intensive calculations by replacing them with simpler closed-form equations, which could be nonlinear. Typically, the approximations provide good accuracy around the points where they are constructed, and they need to be periodically updated to extend their utility. There are approximations in calculating the failure probability of a limit state function. The first one, which is most commonly discussed, is how the limit state is approximated at the design point. Most of the time this could be a first-order Taylor series expansion, also known as the First Order Reliability Method (FORM), or a second-order Taylor series expansion (paraboloid), also known as the Second Order Reliability Method (SORM). From the computational procedure point of view, this step comes after the design point identification; however, the order of approximation for the probability of failure calculation is discussed first, and it is denoted by either FORM or SORM. The other approximation of interest is how the design point, or the most probable failure point (MPP), is identified. For iteratively finding this point, again the limit state is approximated. The accuracy and efficiency of the approximations make the search process quite practical for analysis intensive approaches such as the finite element methods; therefore, the crux of this research is to develop excellent approximations for MPP identification and also different approximations including the higher-order reliability methods (HORM) for representing the failure surface. This report is divided into several parts to emphasize different segments of the structural reliability analysis and design. Broadly, it consists of mathematical foundations, methods and applications. Chapter I discusses the fundamental definitions of the probability theory, which are mostly available in standard text books. Probability density function descriptions relevant to this work are addressed. In Chapter 2, the concept and utility of function approximation are discussed for a general application in engineering analysis. Various forms of function representations and the latest developments in nonlinear adaptive approximations are presented with comparison studies. Research work accomplished in reliability analysis is presented in Chapter 3. First, the definition of safety index and most probable point of failure are introduced. Efficient ways of computing the safety index with a fewer number of iterations is emphasized. In chapter 4, the probability of failure prediction is presented using first-order, second-order and higher-order methods. System reliability methods are discussed in chapter 5. Chapter 6 presents optimization techniques for the modification and redistribution of structural sizes for improving the structural reliability. The report also contains several appendices on probability parameters.

Distributed collaborative response surface method for mechanical dynamic assembly reliability design

NASA Astrophysics Data System (ADS)

Bai, Guangchen; Fei, Chengwei

2013-11-01

Because of the randomness of many impact factors influencing the dynamic assembly relationship of complex machinery, the reliability analysis of dynamic assembly relationship needs to be accomplished considering the randomness from a probabilistic perspective. To improve the accuracy and efficiency of dynamic assembly relationship reliability analysis, the mechanical dynamic assembly reliability(MDAR) theory and a distributed collaborative response surface method(DCRSM) are proposed. The mathematic model of DCRSM is established based on the quadratic response surface function, and verified by the assembly relationship reliability analysis of aeroengine high pressure turbine(HPT) blade-tip radial running clearance(BTRRC). Through the comparison of the DCRSM, traditional response surface method(RSM) and Monte Carlo Method(MCM), the results show that the DCRSM is not able to accomplish the computational task which is impossible for the other methods when the number of simulation is more than 100 000 times, but also the computational precision for the DCRSM is basically consistent with the MCM and improved by 0.40˜4.63% to the RSM, furthermore, the computational efficiency of DCRSM is up to about 188 times of the MCM and 55 times of the RSM under 10000 times simulations. The DCRSM is demonstrated to be a feasible and effective approach for markedly improving the computational efficiency and accuracy of MDAR analysis. Thus, the proposed research provides the promising theory and method for the MDAR design and optimization, and opens a novel research direction of probabilistic analysis for developing the high-performance and high-reliability of aeroengine.

Integrated control-system design via generalized LQG (GLQG) theory

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Hyland, David C.; Richter, Stephen; Haddad, Wassim M.

1989-01-01

Thirty years of control systems research has produced an enormous body of theoretical results in feedback synthesis. Yet such results see relatively little practical application, and there remains an unsettling gap between classical single-loop techniques (Nyquist, Bode, root locus, pole placement) and modern multivariable approaches (LQG and H infinity theory). Large scale, complex systems, such as high performance aircraft and flexible space structures, now demand efficient, reliable design of multivariable feedback controllers which optimally tradeoff performance against modeling accuracy, bandwidth, sensor noise, actuator power, and control law complexity. A methodology is described which encompasses numerous practical design constraints within a single unified formulation. The approach, which is based upon coupled systems or modified Riccati and Lyapunov equations, encompasses time-domain linear-quadratic-Gaussian theory and frequency-domain H theory, as well as classical objectives such as gain and phase margin via the Nyquist circle criterion. In addition, this approach encompasses the optimal projection approach to reduced-order controller design. The current status of the overall theory will be reviewed including both continuous-time and discrete-time (sampled-data) formulations.

Fabrication of Gate-Electrode Integrated Carbon-Nanotube Bundle Field Emitters

NASA Technical Reports Server (NTRS)

Toda, Risaku; Bronikowski, Michael; Luong, Edward; Manohara, Harish

2008-01-01

A continuing effort to develop carbon-nanotube-based field emitters (cold cathodes) as high-current-density electron sources has yielded an optimized device design and a fabrication scheme to implement the design. One major element of the device design is to use a planar array of bundles of carbon nanotubes as the field-emission tips and to optimize the critical dimensions of the array (principally, heights of bundles and distances between them) to obtain high area-averaged current density and high reliability over a long operational lifetime a concept that was discussed in more detail in Arrays of Bundles of Carbon Nanotubes as Field Emitters (NPO-40817), NASA Tech Briefs, Vol. 31, No. 2 (February 2007), page 58. Another major element of the design is to configure the gate electrodes (anodes used to extract, accelerate, and/or focus electrons) as a ring that overhangs a recess wherein the bundles of nanotubes are located, such that by virtue of the proximity between the ring and the bundles, a relatively low applied potential suffices to generate the large electric field needed for emission of electrons.

Comparison of Traditional Design Nonlinear Programming Optimization and Stochastic Methods for Structural Design

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2010-01-01

Structural design generated by traditional method, optimization method and the stochastic design concept are compared. In the traditional method, the constraints are manipulated to obtain the design and weight is back calculated. In design optimization, the weight of a structure becomes the merit function with constraints imposed on failure modes and an optimization algorithm is used to generate the solution. Stochastic design concept accounts for uncertainties in loads, material properties, and other parameters and solution is obtained by solving a design optimization problem for a specified reliability. Acceptable solutions were produced by all the three methods. The variation in the weight calculated by the methods was modest. Some variation was noticed in designs calculated by the methods. The variation may be attributed to structural indeterminacy. It is prudent to develop design by all three methods prior to its fabrication. The traditional design method can be improved when the simplified sensitivities of the behavior constraint is used. Such sensitivity can reduce design calculations and may have a potential to unify the traditional and optimization methods. Weight versus reliabilitytraced out an inverted-S-shaped graph. The center of the graph corresponded to mean valued design. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for a most failure-prone design. Probabilistic modeling of load and material properties remained a challenge.

Distribution System Reliability Analysis for Smart Grid Applications

NASA Astrophysics Data System (ADS)

Aljohani, Tawfiq Masad

Reliability of power systems is a key aspect in modern power system planning, design, and operation. The ascendance of the smart grid concept has provided high hopes of developing an intelligent network that is capable of being a self-healing grid, offering the ability to overcome the interruption problems that face the utility and cost it tens of millions in repair and loss. To address its reliability concerns, the power utilities and interested parties have spent extensive amount of time and effort to analyze and study the reliability of the generation and transmission sectors of the power grid. Only recently has attention shifted to be focused on improving the reliability of the distribution network, the connection joint between the power providers and the consumers where most of the electricity problems occur. In this work, we will examine the effect of the smart grid applications in improving the reliability of the power distribution networks. The test system used in conducting this thesis is the IEEE 34 node test feeder, released in 2003 by the Distribution System Analysis Subcommittee of the IEEE Power Engineering Society. The objective is to analyze the feeder for the optimal placement of the automatic switching devices and quantify their proper installation based on the performance of the distribution system. The measures will be the changes in the reliability system indices including SAIDI, SAIFI, and EUE. The goal is to design and simulate the effect of the installation of the Distributed Generators (DGs) on the utility's distribution system and measure the potential improvement of its reliability. The software used in this work is DISREL, which is intelligent power distribution software that is developed by General Reliability Co.

Structural Optimization of the Retractable Dome for Four Meter Telescope (FMT)

NASA Astrophysics Data System (ADS)

Pan, Nian; Li, Yuxi; Fan, Yue; Ma, Wenli; Huang, Jinlong; Jiang, Ping; Kong, Sijie

2017-03-01

Dome seeing degrades the image quality of ground-based telescopes. To achieve dome seeing of the Four Meter Telescope (FMT) less than 0.5 arcsec, structural optimizations based on computational fluid dynamics (CFD) simulation were proposed. The results of the simulation showed that dome seeing of FMT was 0.42 arcsec, which was mainly caused by the slope angle of the dome when the slope angle was 15° and the wind speed was 10 m/s. Furthermore, the lower the air speed was, the less dome seeing would be. Wind tunnel tests (WT) with a 1:120 scaled model of the retractable dome and FMT indicated that the calculated deviations of the CFD simulation used in this paper were less than 20% and the same variations of the refractive index derived from the WT would be a convincing argument for the validity of the simulations. Thus, the optimization of the retractable dome was reliable and the method expressed in this paper provided a reference for the design of next generation of ground-based telescope dome.

DG Planning with Amalgamation of Operational and Reliability Considerations

NASA Astrophysics Data System (ADS)

Battu, Neelakanteshwar Rao; Abhyankar, A. R.; Senroy, Nilanjan

2016-04-01

Distributed Generation has been playing a vital role in dealing issues related to distribution systems. This paper presents an approach which provides policy maker with a set of solutions for DG placement to optimize reliability and real power loss of the system. Optimal location of a Distributed Generator is evaluated based on performance indices derived for reliability index and real power loss. The proposed approach is applied on a 15-bus radial distribution system and a 18-bus radial distribution system with conventional and wind distributed generators individually.

The use of chemometrics to study multifunctional indole alkaloids from Psychotria nemorosa (Palicourea comb. nov.). Part I: Extraction and fractionation optimization based on metabolic profiling.

PubMed

Klein-Júnior, Luiz C; Viaene, Johan; Salton, Juliana; Koetz, Mariana; Gasper, André L; Henriques, Amélia T; Vander Heyden, Yvan

2016-09-09

Extraction methods evaluation to access plants metabolome is usually performed visually, lacking a truthful method of data handling. In the present study the major aim was developing reliable time- and solvent-saving extraction and fractionation methods to access alkaloid profiling of Psychotria nemorosa leaves. Ultrasound assisted extraction was selected as extraction method. Determined from a Fractional Factorial Design (FFD) approach, yield, sum of peak areas, and peak numbers were rather meaningless responses. However, Euclidean distance calculations between the UPLC-DAD metabolic profiles and the blank injection evidenced the extracts are highly diverse. Coupled with the calculation and plotting of effects per time point, it was possible to indicate thermolabile peaks. After screening, time and temperature were selected for optimization, while plant:solvent ratio was set at 1:50 (m/v), number of extractions at one and particle size at ≤180μm. From Central Composite Design (CCD) results modeling heights of important peaks, previously indicated by the FFD metabolic profile analysis, time was set at 65min and temperature at 45°C, thus avoiding degradation. For the fractionation step, a solid phase extraction method was optimized by a Box-Behnken Design (BBD) approach using the sum of peak areas as response. Sample concentration was consequently set at 150mg/mL, % acetonitrile in dichloromethane at 40% as eluting solvent, and eluting volume at 30mL. Summarized, the Euclidean distance and the metabolite profiles provided significant responses for accessing P. nemorosa alkaloids, allowing developing reliable extraction and fractionation methods, avoiding degradation and decreasing the required time and solvent volume. Copyright © 2016 Elsevier B.V. All rights reserved.

Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.).

PubMed

Rincent, R; Laloë, D; Nicolas, S; Altmann, T; Brunel, D; Revilla, P; Rodríguez, V M; Moreno-Gonzalez, J; Melchinger, A; Bauer, E; Schoen, C-C; Meyer, N; Giauffret, C; Bauland, C; Jamin, P; Laborde, J; Monod, H; Flament, P; Charcosset, A; Moreau, L

2012-10-01

Genomic selection refers to the use of genotypic information for predicting breeding values of selection candidates. A prediction formula is calibrated with the genotypes and phenotypes of reference individuals constituting the calibration set. The size and the composition of this set are essential parameters affecting the prediction reliabilities. The objective of this study was to maximize reliabilities by optimizing the calibration set. Different criteria based on the diversity or on the prediction error variance (PEV) derived from the realized additive relationship matrix-best linear unbiased predictions model (RA-BLUP) were used to select the reference individuals. For the latter, we considered the mean of the PEV of the contrasts between each selection candidate and the mean of the population (PEVmean) and the mean of the expected reliabilities of the same contrasts (CDmean). These criteria were tested with phenotypic data collected on two diversity panels of maize (Zea mays L.) genotyped with a 50k SNPs array. In the two panels, samples chosen based on CDmean gave higher reliabilities than random samples for various calibration set sizes. CDmean also appeared superior to PEVmean, which can be explained by the fact that it takes into account the reduction of variance due to the relatedness between individuals. Selected samples were close to optimality for a wide range of trait heritabilities, which suggests that the strategy presented here can efficiently sample subsets in panels of inbred lines. A script to optimize reference samples based on CDmean is available on request.

Optimal designs based on the maximum quasi-likelihood estimator

PubMed Central

Shen, Gang; Hyun, Seung Won; Wong, Weng Kee

2016-01-01

We use optimal design theory and construct locally optimal designs based on the maximum quasi-likelihood estimator (MqLE), which is derived under less stringent conditions than those required for the MLE method. We show that the proposed locally optimal designs are asymptotically as efficient as those based on the MLE when the error distribution is from an exponential family, and they perform just as well or better than optimal designs based on any other asymptotically linear unbiased estimators such as the least square estimator (LSE). In addition, we show current algorithms for finding optimal designs can be directly used to find optimal designs based on the MqLE. As an illustrative application, we construct a variety of locally optimal designs based on the MqLE for the 4-parameter logistic (4PL) model and study their robustness properties to misspecifications in the model using asymptotic relative efficiency. The results suggest that optimal designs based on the MqLE can be easily generated and they are quite robust to mis-specification in the probability distribution of the responses. PMID:28163359

Neural Network Prediction of New Aircraft Design Coefficients

NASA Technical Reports Server (NTRS)

Norgaard, Magnus; Jorgensen, Charles C.; Ross, James C.

1997-01-01

This paper discusses a neural network tool for more effective aircraft design evaluations during wind tunnel tests. Using a hybrid neural network optimization method, we have produced fast and reliable predictions of aerodynamical coefficients, found optimal flap settings, and flap schedules. For validation, the tool was tested on a 55% scale model of the USAF/NASA Subsonic High Alpha Research Concept aircraft (SHARC). Four different networks were trained to predict coefficients of lift, drag, moment of inertia, and lift drag ratio (C(sub L), C(sub D), C(sub M), and L/D) from angle of attack and flap settings. The latter network was then used to determine an overall optimal flap setting and for finding optimal flap schedules.

Image gathering and processing - Information and fidelity

NASA Technical Reports Server (NTRS)

Huck, F. O.; Fales, C. L.; Halyo, N.; Samms, R. W.; Stacy, K.

1985-01-01

In this paper we formulate and use information and fidelity criteria to assess image gathering and processing, combining optical design with image-forming and edge-detection algorithms. The optical design of the image-gathering system revolves around the relationship among sampling passband, spatial response, and signal-to-noise ratio (SNR). Our formulations of information, fidelity, and optimal (Wiener) restoration account for the insufficient sampling (i.e., aliasing) common in image gathering as well as for the blurring and noise that conventional formulations account for. Performance analyses and simulations for ordinary optical-design constraints and random scences indicate that (1) different image-forming algorithms prefer different optical designs; (2) informationally optimized designs maximize the robustness of optimal image restorations and lead to the highest-spatial-frequency channel (relative to the sampling passband) for which edge detection is reliable (if the SNR is sufficiently high); and (3) combining the informationally optimized design with a 3 by 3 lateral-inhibitory image-plane-processing algorithm leads to a spatial-response shape that approximates the optimal edge-detection response of (Marr's model of) human vision and thus reduces the data preprocessing and transmission required for machine vision.

Developing safety performance functions incorporating reliability-based risk measures.

PubMed

Ibrahim, Shewkar El-Bassiouni; Sayed, Tarek

2011-11-01

Current geometric design guides provide deterministic standards where the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from these standards. Several studies have advocated probabilistic geometric design where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a risk measure of the implication of deviation from design standards. However, there is currently no link between measures of design reliability and the quantification of safety using collision frequency. The analysis presented in this paper attempts to bridge this gap by incorporating a reliability-based quantitative risk measure such as the probability of non-compliance (P(nc)) in safety performance functions (SPFs). Establishing this link will allow admitting reliability-based design into traditional benefit-cost analysis and should lead to a wider application of the reliability technique in road design. The present application is concerned with the design of horizontal curves, where the limit state function is defined in terms of the available (supply) and stopping (demand) sight distances. A comprehensive collision and geometric design database of two-lane rural highways is used to investigate the effect of the probability of non-compliance on safety. The reliability analysis was carried out using the First Order Reliability Method (FORM). Two Negative Binomial (NB) SPFs were developed to compare models with and without the reliability-based risk measures. It was found that models incorporating the P(nc) provided a better fit to the data set than the traditional (without risk) NB SPFs for total, injury and fatality (I+F) and property damage only (PDO) collisions. Copyright © 2011 Elsevier Ltd. All rights reserved.

A hybrid Jaya algorithm for reliability-redundancy allocation problems

NASA Astrophysics Data System (ADS)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

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.

Demonstrating the Safety and Reliability of a New System or Spacecraft: Incorporating Analyses and Reviews of the Design and Processing in Determining the Number of Tests to be Conducted

NASA Technical Reports Server (NTRS)

Vesely, William E.; Colon, Alfredo E.

2010-01-01

Design Safety/Reliability is associated with the probability of no failure-causing faults existing in a design. Confidence in the non-existence of failure-causing faults is increased by performing tests with no failure. Reliability-Growth testing requirements are based on initial assurance and fault detection probability. Using binomial tables generally gives too many required tests compared to reliability-growth requirements. Reliability-Growth testing requirements are based on reliability principles and factors and should be used.

Improvement of up-converting phosphor technology-based biosensor

NASA Astrophysics Data System (ADS)

Xie, Chengke; Huang, Lihua; Zhang, Youbao; Guo, Xiaoxian; Qu, Jianfeng; Huang, Huijie

2008-12-01

A novel biosensor based on up-converting phosphor technology (UPT) was developed several years ago. It is a kind of optical biosensor using up-converting phosphor (UCP) particles as the biological marker. From then on, some improvements have been made for this UPT-based biosensor. The primary aspects of the improvement lie in the control system. On one hand, the hardware of the control system has been optimized, including replacing two single chip microcomputers (SCM) with only one, the optimal design of the keyboard interface circuit and the liquid crystal module (LCM) control circuit et al.. These result in lower power consumption and higher reliability. On the other hand, a novel signal processing algorithm is proposed in this paper, which can improve the automation and operating simplicity of the UPT-based biosensor. It has proved to have high sensitivity (~ng/ml), high stability and good repeatability (CV<5%), which is better than the former system. It can meet the need of some various applications such as rapid immunoassay, chemical and biological detection and so on.

Optimal Reservoir Operation using Stochastic Model Predictive Control

NASA Astrophysics Data System (ADS)

Sahu, R.; McLaughlin, D.

2016-12-01

Hydropower operations are typically designed to fulfill contracts negotiated with consumers who need reliable energy supplies, despite uncertainties in reservoir inflows. In addition to providing reliable power the reservoir operator needs to take into account environmental factors such as downstream flooding or compliance with minimum flow requirements. From a dynamical systems perspective, the reservoir operating strategy must cope with conflicting objectives in the presence of random disturbances. In order to achieve optimal performance, the reservoir system needs to continually adapt to disturbances in real time. Model Predictive Control (MPC) is a real-time control technique that adapts by deriving the reservoir release at each decision time from the current state of the system. Here an ensemble-based version of MPC (SMPC) is applied to a generic reservoir to determine both the optimal power contract, considering future inflow uncertainty, and a real-time operating strategy that attempts to satisfy the contract. Contract selection and real-time operation are coupled in an optimization framework that also defines a Pareto trade off between the revenue generated from energy production and the environmental damage resulting from uncontrolled reservoir spills. Further insight is provided by a sensitivity analysis of key parameters specified in the SMPC technique. The results demonstrate that SMPC is suitable for multi-objective planning and associated real-time operation of a wide range of hydropower reservoir systems.

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2000-01-01

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics, cost, mission and coupled structural/thermal, various composite property simulators and probabilistic methods to evaluate uncertainty effects (scatter ranges) in all the design parameters. The objective of the proposed paper is to briefly describe a multi-faceted design analysis and optimization capability for coupled multi-discipline engine structures optimization. Results are presented for engine and aircraft type metrics to illustrate the versatility of that capability. Results are also presented for reliability, noise and fatigue to illustrate its inclusiveness. For example, replacing metal rotors with composites reduces the engine weight by 20 percent, 15 percent noise reduction, and an order of magnitude improvement in reliability. Composite designs exist to increase fatigue life by at least two orders of magnitude compared to state-of-the-art metals.

Development of garlic bioactive compounds analytical methodology based on liquid phase microextraction using response surface design. Implications for dual analysis: Cooked and biological fluids samples.

PubMed

Ramirez, Daniela Andrea; Locatelli, Daniela Ana; Torres-Palazzolo, Carolina Andrea; Altamirano, Jorgelina Cecilia; Camargo, Alejandra Beatriz

2017-01-15

Organosulphur compounds (OSCs) present in garlic (Allium sativum L.) are responsible of several biological properties. Functional foods researches indicate the importance of quantifying these compounds in food matrices and biological fluids. For this purpose, this paper introduces a novel methodology based on dispersive liquid-liquid microextraction (DLLME) coupled to high performance liquid chromatography with ultraviolet detector (HPLC-UV) for the extraction and determination of organosulphur compounds in different matrices. The target analytes were allicin, (E)- and (Z)-ajoene, 2-vinyl-4H-1,2-dithiin (2-VD), diallyl sulphide (DAS) and diallyl disulphide (DADS). The microextraction technique was optimized using an experimental design, and the analytical performance was evaluated under optimum conditions. The desirability function presented an optimal value for 600μL of chloroform as extraction solvent using acetonitrile as dispersant. The method proved to be reliable, precise and accurate. It was successfully applied to determine OSCs in cooked garlic samples as well as blood plasma and digestive fluids. Copyright © 2016 Elsevier Ltd. All rights reserved.

Reliability-based evaluation of bridge components for consistent safety margins.

DOT National Transportation Integrated Search

2010-10-01

The Load and Resistant Factor Design (LRFD) approach is based on the concept of structural reliability. The approach is more : rational than the former design approaches such as Load Factor Design or Allowable Stress Design. The LRFD Specification fo...

antaRNA: ant colony-based RNA sequence design.

PubMed

Kleinkauf, Robert; Mann, Martin; Backofen, Rolf

2015-10-01

RNA sequence design is studied at least as long as the classical folding problem. Although for the latter the functional fold of an RNA molecule is to be found ,: inverse folding tries to identify RNA sequences that fold into a function-specific target structure. In combination with RNA-based biotechnology and synthetic biology ,: reliable RNA sequence design becomes a crucial step to generate novel biochemical components. In this article ,: the computational tool antaRNA is presented. It is capable of compiling RNA sequences for a given structure that comply in addition with an adjustable full range objective GC-content distribution ,: specific sequence constraints and additional fuzzy structure constraints. antaRNA applies ant colony optimization meta-heuristics and its superior performance is shown on a biological datasets. http://www.bioinf.uni-freiburg.de/Software/antaRNA CONTACT: backofen@informatik.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Reentry-Vehicle Shape Optimization Using a Cartesian Adjoint Method and CAD Geometry

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.

2006-01-01

A DJOINT solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (e.g., geometric parameters that control the shape). Classic aerodynamic applications of gradient-based optimization include the design of cruise configurations for transonic and supersonic flow, as well as the design of high-lift systems. are perhaps the most promising approach for addressing the issues of flow solution automation for aerodynamic design problems. In these methods, the discretization of the wetted surface is decoupled from that of the volume mesh. This not only enables fast and robust mesh generation for geometry of arbitrary complexity, but also facilitates access to geometry modeling and manipulation using parametric computer-aided design (CAD). In previous work on Cartesian adjoint solvers, Melvin et al. developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the two-dimensional Euler equations using a ghost-cell method to enforce the wall boundary conditions. In Refs. 18 and 19, we presented an accurate and efficient algorithm for the solution of the adjoint Euler equations discretized on Cartesian meshes with embedded, cut-cell boundaries. Novel aspects of the algorithm were the computation of surface shape sensitivities for triangulations based on parametric-CAD models and the linearization of the coupling between the surface triangulation and the cut-cells. The accuracy of the gradient computation was verified using several three-dimensional test cases, which included design variables such as the free stream parameters and the planform shape of an isolated wing. The objective of the present work is to extend our adjoint formulation to problems involving general shape changes. Factors under consideration include the computation of mesh sensitivities that provide a reliable approximation of the objective function gradient, as well as the computation of surface shape sensitivities based on a direct-CAD interface. We present detailed gradient verification studies and then focus on a shape optimization problem for an Apollo-like reentry vehicle. The goal of the optimization is to enhance the lift-to-drag ratio of the capsule by modifying the shape of its heat-shield in conjunction with a center-of-gravity (c.g.) offset. This multipoint and multi-objective optimization problem is used to demonstrate the overall effectiveness of the Cartesian adjoint method for addressing the issues of complex aerodynamic design.

Space tourism optimized reusable spaceplane design

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

Penn, J.P.; Lindley, C.A.

Market surveys suggest that a viable space tourism industry will require flight rates about two orders of magnitude higher than those required for conventional spacelift. Although enabling round-trip cost goals for a viable space tourism business are about {dollar_sign}240 per pound ({dollar_sign}529/kg), or {dollar_sign}72,000 per passenger round-trip, goals should be about {dollar_sign}50 per pound ({dollar_sign}110/kg) or approximately {dollar_sign}15,000 for a typical passenger and baggage. The lower price will probably open space tourism to the general population. Vehicle reliabilities must approach those of commercial aircraft as closely as possible. This paper addresses the development of spaceplanes optimized for the ultra-high flightmore » rate and high reliability demands of the space tourism mission. It addresses the fundamental operability, reliability, and cost drivers needed to satisfy this mission need. Figures of merit similar to those used to evaluate the economic viability of conventional commercial aircraft are developed, including items such as payload/vehicle dry weight, turnaround time, propellant cost per passenger, and insurance and depreciation costs, which show that infrastructure can be developed for a viable space tourism industry. A reference spaceplane design optimized for space tourism is described. Subsystem allocations for reliability, operability, and costs are made and a route to developing such a capability is discussed. The vehicle{close_quote}s ability to also satisfy the traditional spacelift market is shown. {copyright} {ital 1997 American Institute of Physics.}« less

E-Service Quality Evaluation on E-Government Website: Case Study BPJS Kesehatan Indonesia

NASA Astrophysics Data System (ADS)

Rasyid, A.; Alfina, I.

2017-01-01

This research intends to develop a model to evaluate the quality of e-services on e-government. The proposed model consists of seven dimensions: web design, reliability, responsiveness, privacy and security, personalization, information, and ease of use. The model is used to measure the quality of the e-registration of BPJS Kesehatan, an Indonesian government health insurance program. The validation and reliability testing show that of the seven dimensions proposed, only four that suitable for the case study. The result shows that the BPJS Kesehatan e-registration service is good in reliability and responsiveness dimensions, while from web design and ease of use dimensions the e-service still needs to be optimized.

Crystalline-silicon reliability lessons for thin-film modules

NASA Technical Reports Server (NTRS)

Ross, R. G., Jr.

1985-01-01

The reliability of crystalline silicon modules has been brought to a high level with lifetimes approaching 20 years, and excellent industry credibility and user satisfaction. The transition from crystalline modules to thin film modules is comparable to the transition from discrete transistors to integrated circuits. New cell materials and monolithic structures will require new device processing techniques, but the package function and design will evolve to a lesser extent. Although there will be new encapsulants optimized to take advantage of the mechanical flexibility and low temperature processing features of thin films, the reliability and life degradation stresses and mechanisms will remain mostly unchanged. Key reliability technologies in common between crystalline and thin film modules include hot spot heating, galvanic and electrochemical corrosion, hail impact stresses, glass breakage, mechanical fatigue, photothermal degradation of encapsulants, operating temperature, moisture sorption, circuit design strategies, product safety issues, and the process required to achieve a reliable product from a laboratory prototype.

Performance and Reliability Optimization for Aerospace Systems subject to Uncertainty and Degradation

NASA Technical Reports Server (NTRS)

Miller, David W.; Uebelhart, Scott A.; Blaurock, Carl

2004-01-01

This report summarizes work performed by the Space Systems Laboratory (SSL) for NASA Langley Research Center in the field of performance optimization for systems subject to uncertainty. The objective of the research is to develop design methods and tools to the aerospace vehicle design process which take into account lifecycle uncertainties. It recognizes that uncertainty between the predictions of integrated models and data collected from the system in its operational environment is unavoidable. Given the presence of uncertainty, the goal of this work is to develop means of identifying critical sources of uncertainty, and to combine these with the analytical tools used with integrated modeling. In this manner, system uncertainty analysis becomes part of the design process, and can motivate redesign. The specific program objectives were: 1. To incorporate uncertainty modeling, propagation and analysis into the integrated (controls, structures, payloads, disturbances, etc.) design process to derive the error bars associated with performance predictions. 2. To apply modern optimization tools to guide in the expenditure of funds in a way that most cost-effectively improves the lifecycle productivity of the system by enhancing the subsystem reliability and redundancy. The results from the second program objective are described. This report describes the work and results for the first objective: uncertainty modeling, propagation, and synthesis with integrated modeling.

The usefulness of systematic reviews of animal experiments for the design of preclinical and clinical studies.

PubMed

de Vries, Rob B M; Wever, Kimberley E; Avey, Marc T; Stephens, Martin L; Sena, Emily S; Leenaars, Marlies

2014-01-01

The question of how animal studies should be designed, conducted, and analyzed remains underexposed in societal debates on animal experimentation. This is not only a scientific but also a moral question. After all, if animal experiments are not appropriately designed, conducted, and analyzed, the results produced are unlikely to be reliable and the animals have in effect been wasted. In this article, we focus on one particular method to address this moral question, namely systematic reviews of previously performed animal experiments. We discuss how the design, conduct, and analysis of future (animal and human) experiments may be optimized through such systematic reviews. In particular, we illustrate how these reviews can help improve the methodological quality of animal experiments, make the choice of an animal model and the translation of animal data to the clinic more evidence-based, and implement the 3Rs. Moreover, we discuss which measures are being taken and which need to be taken in the future to ensure that systematic reviews will actually contribute to optimizing experimental design and thereby to meeting a necessary condition for making the use of animals in these experiments justified. © The Author 2014. Published by Oxford University Press.

The Usefulness of Systematic Reviews of Animal Experiments for the Design of Preclinical and Clinical Studies

PubMed Central

de Vries, Rob B. M.; Wever, Kimberley E.; Avey, Marc T.; Stephens, Martin L.; Sena, Emily S.; Leenaars, Marlies

2014-01-01

The question of how animal studies should be designed, conducted, and analyzed remains underexposed in societal debates on animal experimentation. This is not only a scientific but also a moral question. After all, if animal experiments are not appropriately designed, conducted, and analyzed, the results produced are unlikely to be reliable and the animals have in effect been wasted. In this article, we focus on one particular method to address this moral question, namely systematic reviews of previously performed animal experiments. We discuss how the design, conduct, and analysis of future (animal and human) experiments may be optimized through such systematic reviews. In particular, we illustrate how these reviews can help improve the methodological quality of animal experiments, make the choice of an animal model and the translation of animal data to the clinic more evidence-based, and implement the 3Rs. Moreover, we discuss which measures are being taken and which need to be taken in the future to ensure that systematic reviews will actually contribute to optimizing experimental design and thereby to meeting a necessary condition for making the use of animals in these experiments justified. PMID:25541545

A real time, FEM based optimal control algorithm and its implementation using parallel processing hardware (transistors) in a microprocessor environment

NASA Technical Reports Server (NTRS)

Patten, William Neff

1989-01-01

There is an evident need to discover a means of establishing reliable, implementable controls for systems that are plagued by nonlinear and, or uncertain, model dynamics. The development of a generic controller design tool for tough-to-control systems is reported. The method utilizes a moving grid, time infinite element based solution of the necessary conditions that describe an optimal controller for a system. The technique produces a discrete feedback controller. Real time laboratory experiments are now being conducted to demonstrate the viability of the method. The algorithm that results is being implemented in a microprocessor environment. Critical computational tasks are accomplished using a low cost, on-board, multiprocessor (INMOS T800 Transputers) and parallel processing. Progress to date validates the methodology presented. Applications of the technique to the control of highly flexible robotic appendages are suggested.

Safety reliability evaluation when vehicles turn right from urban major roads onto minor ones based on driver's visual perception.

PubMed

Yu, Bo; Chen, Yuren; Wang, Ruiyun; Dong, Yongjie

2016-10-01

Turning right has a significant impact on urban road traffic safety. Driving into the curve inappropriately or with improper turning speed often leads to a series of potential accidents and hidden dangers. For a long time, the design speed at intersections has been used to determine the physical radius of curbs and channelization, and drivers are expected to drive in accordance with the design speed. However, a large number of real vehicle tests show that for the road without an exclusive right-turn lane, there is not a good correlation between the physical radius of curbs and the turning right speeds. In this paper, shape parameters of the driver's visual lane model are put forward and they have relatively high correlations with right-turn speeds. Hence, an evaluation method about safety reliability of turning right from urban major roads onto minor ones based on driver's visual perception is proposed. For existing roads, the evaluation object could be real driving videos; for those under construction roads, the evaluation object could be visual scenes obtained from a driving simulation device. Findings in this research will make a contribution to the optimization of right-turn design at intersections and lead to the development of auxiliary driving technology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Structural design considerations for micromachined solid-oxide fuel cells

NASA Astrophysics Data System (ADS)

Srikar, V. T.; Turner, Kevin T.; Andrew Ie, Tze Yung; Spearing, S. Mark

Micromachined solid-oxide fuel cells (μSOFCs) are among a class of devices being investigated for portable power generation. Optimization of the performance and reliability of such devices requires robust, scale-dependent, design methodologies. In this first analysis, we consider the structural design of planar, electrolyte-supported, μSOFCs from the viewpoints of electrochemical performance, mechanical stability and reliability, and thermal behavior. The effect of electrolyte thickness on fuel cell performance is evaluated using a simple analytical model. Design diagrams that account explicitly for thermal and intrinsic residual stresses are presented to identify geometries that are resistant to fracture and buckling. Analysis of energy loss due to in-plane heat conduction highlights the importance of efficient thermal isolation in microscale fuel cell design.

Fast and Accurate Circuit Design Automation through Hierarchical Model Switching.

PubMed

Huynh, Linh; Tagkopoulos, Ilias

2015-08-21

In computer-aided biological design, the trifecta of characterized part libraries, accurate models and optimal design parameters is crucial for producing reliable designs. As the number of parts and model complexity increase, however, it becomes exponentially more difficult for any optimization method to search the solution space, hence creating a trade-off that hampers efficient design. To address this issue, we present a hierarchical computer-aided design architecture that uses a two-step approach for biological design. First, a simple model of low computational complexity is used to predict circuit behavior and assess candidate circuit branches through branch-and-bound methods. Then, a complex, nonlinear circuit model is used for a fine-grained search of the reduced solution space, thus achieving more accurate results. Evaluation with a benchmark of 11 circuits and a library of 102 experimental designs with known characterization parameters demonstrates a speed-up of 3 orders of magnitude when compared to other design methods that provide optimality guarantees.

Optimal reinforcement of training datasets in semi-supervised landmark-based segmentation

NASA Astrophysics Data System (ADS)

Ibragimov, Bulat; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

2015-03-01

During the last couple of decades, the development of computerized image segmentation shifted from unsupervised to supervised methods, which made segmentation results more accurate and robust. However, the main disadvantage of supervised segmentation is a need for manual image annotation that is time-consuming and subjected to human error. To reduce the need for manual annotation, we propose a novel learning approach for training dataset reinforcement in the area of landmark-based segmentation, where newly detected landmarks are optimally combined with reference landmarks from the training dataset and therefore enriches the training process. The approach is formulated as a nonlinear optimization problem, where the solution is a vector of weighting factors that measures how reliable are the detected landmarks. The detected landmarks that are found to be more reliable are included into the training procedure with higher weighting factors, whereas the detected landmarks that are found to be less reliable are included with lower weighting factors. The approach is integrated into the landmark-based game-theoretic segmentation framework and validated against the problem of lung field segmentation from chest radiographs.

Scheduling for energy and reliability management on multiprocessor real-time systems

NASA Astrophysics Data System (ADS)

Qi, Xuan

Scheduling algorithms for multiprocessor real-time systems have been studied for years with many well-recognized algorithms proposed. However, it is still an evolving research area and many problems remain open due to their intrinsic complexities. With the emergence of multicore processors, it is necessary to re-investigate the scheduling problems and design/develop efficient algorithms for better system utilization, low scheduling overhead, high energy efficiency, and better system reliability. Focusing cluster schedulings with optimal global schedulers, we study the utilization bound and scheduling overhead for a class of cluster-optimal schedulers. Then, taking energy/power consumption into consideration, we developed energy-efficient scheduling algorithms for real-time systems, especially for the proliferating embedded systems with limited energy budget. As the commonly deployed energy-saving technique (e.g. dynamic voltage frequency scaling (DVFS)) will significantly affect system reliability, we study schedulers that have intelligent mechanisms to recuperate system reliability to satisfy the quality assurance requirements. Extensive simulation is conducted to evaluate the performance of the proposed algorithms on reduction of scheduling overhead, energy saving, and reliability improvement. The simulation results show that the proposed reliability-aware power management schemes could preserve the system reliability while still achieving substantial energy saving.

Development of Long-Pulse Heating and Current Drive Actuators and Operational Techniques Compatible with a High-Z Divertor and First Wall

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

Wang, Guiding

Accurate measurement of the edge electron density profile is essential to optimizing antenna coupling and assessment of impurity contamination in studying long-pulse plasma heating and current drive in fusion devices. Measurement of the edge density profile has been demonstrated on the US fusion devices such as C-Mod, DIII-D, and TFTR amongst many devices, and has been used for RF loading and impurity modeling calculations for many years. University of Science and Technology of China (USTC) has recently installed a density profile reflectometer system on the EAST fusion device at the Institute of Plasma Physics, Chinese Academy of Sciences in Chinamore » based on the University of California Los Angeles (UCLA)-designed reflectometer system on the DIII-D fusion device at General Atomics Company in San Diego, California. UCLA has been working with USTC to optimize the existing microwave antenna, waveguide system, microwave electronics, and data analysis to produce reliable edge density profiles. During the past budget year, progress has been made in all three major areas: effort to achieve reliable system operations under various EAST operational conditions, effort to optimize system performance, and effort to provide quality density profiles into EAST’s database routinely.« less

A quantitative framework for the forward design of synthetic miRNA circuits.

PubMed

Bloom, Ryan J; Winkler, Sally M; Smolke, Christina D

2014-11-01

Synthetic genetic circuits incorporating regulatory components based on RNA interference (RNAi) have been used in a variety of systems. A comprehensive understanding of the parameters that determine the relationship between microRNA (miRNA) and target expression levels is lacking. We describe a quantitative framework supporting the forward engineering of gene circuits that incorporate RNAi-based regulatory components in mammalian cells. We developed a model that captures the quantitative relationship between miRNA and target gene expression levels as a function of parameters, including mRNA half-life and miRNA target-site number. We extended the model to synthetic circuits that incorporate protein-responsive miRNA switches and designed an optimized miRNA-based protein concentration detector circuit that noninvasively measures small changes in the nuclear concentration of β-catenin owing to induction of the Wnt signaling pathway. Our results highlight the importance of methods for guiding the quantitative design of genetic circuits to achieve robust, reliable and predictable behaviors in mammalian cells.

Advanced Information Technology in Simulation Based Life Cycle Design

NASA Technical Reports Server (NTRS)

Renaud, John E.

2003-01-01

In this research a Collaborative Optimization (CO) approach for multidisciplinary systems design is used to develop a decision based design framework for non-deterministic optimization. To date CO strategies have been developed for use in application to deterministic systems design problems. In this research the decision based design (DBD) framework proposed by Hazelrigg is modified for use in a collaborative optimization framework. The Hazelrigg framework as originally proposed provides a single level optimization strategy that combines engineering decisions with business decisions in a single level optimization. By transforming this framework for use in collaborative optimization one can decompose the business and engineering decision making processes. In the new multilevel framework of Decision Based Collaborative Optimization (DBCO) the business decisions are made at the system level. These business decisions result in a set of engineering performance targets that disciplinary engineering design teams seek to satisfy as part of subspace optimizations. The Decision Based Collaborative Optimization framework more accurately models the existing relationship between business and engineering in multidisciplinary systems design.

Aerodynamic Shape Optimization Using A Real-Number-Encoded Genetic Algorithm

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2001-01-01

A new method for aerodynamic shape optimization using a genetic algorithm with real number encoding is presented. The algorithm is used to optimize three different problems, a simple hill climbing problem, a quasi-one-dimensional nozzle problem using an Euler equation solver and a three-dimensional transonic wing problem using a nonlinear potential solver. Results indicate that the genetic algorithm is easy to implement and extremely reliable, being relatively insensitive to design space noise.

Thermal-Structural Optimization of Integrated Cryogenic Propellant Tank Concepts for a Reusable Launch Vehicle

NASA Technical Reports Server (NTRS)

Johnson, Theodore F.; Waters, W. Allen; Singer, Thomas N.; Haftka, Raphael T.

2004-01-01

A next generation reusable launch vehicle (RLV) will require thermally efficient and light-weight cryogenic propellant tank structures. Since these tanks will be weight-critical, analytical tools must be developed to aid in sizing the thickness of insulation layers and structural geometry for optimal performance. Finite element method (FEM) models of the tank and insulation layers were created to analyze the thermal performance of the cryogenic insulation layer and thermal protection system (TPS) of the tanks. The thermal conditions of ground-hold and re-entry/soak-through for a typical RLV mission were used in the thermal sizing study. A general-purpose nonlinear FEM analysis code, capable of using temperature and pressure dependent material properties, was used as the thermal analysis code. Mechanical loads from ground handling and proof-pressure testing were used to size the structural geometry of an aluminum cryogenic tank wall. Nonlinear deterministic optimization and reliability optimization techniques were the analytical tools used to size the geometry of the isogrid stiffeners and thickness of the skin. The results from the sizing study indicate that a commercial FEM code can be used for thermal analyses to size the insulation thicknesses where the temperature and pressure were varied. The results from the structural sizing study show that using combined deterministic and reliability optimization techniques can obtain alternate and lighter designs than the designs obtained from deterministic optimization methods alone.

Application of experimental design for the optimization of artificial neural network-based water quality model: a case study of dissolved oxygen prediction.

PubMed

Šiljić Tomić, Aleksandra; Antanasijević, Davor; Ristić, Mirjana; Perić-Grujić, Aleksandra; Pocajt, Viktor

2018-04-01

This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to obtain a more reliable ANN model that uses fewer monitoring records, by simultaneous optimization of the following model parameters: number of monitoring sites, number of historical monitoring data (expressed in years), and number of input water quality parameters used. Box-Behnken three-factor at three levels experimental design was applied for simultaneous spatial, temporal, and input variables optimization of the ANN model. The prediction of DO was performed using a feed-forward back-propagation neural network (BPNN), while the selection of most important inputs was done off-model using multi-filter approach that combines a chi-square ranking in the first step with a correlation-based elimination in the second step. The contour plots of absolute and relative error response surfaces were utilized to determine the optimal values of design factors. From the contour plots, two BPNN models that cover entire Danube flow through Serbia are proposed: an upstream model (BPNN-UP) that covers 8 monitoring sites prior to Belgrade and uses 12 inputs measured in the 7-year period and a downstream model (BPNN-DOWN) which covers 9 monitoring sites and uses 11 input parameters measured in the 6-year period. The main difference between the two models is that BPNN-UP utilizes inputs such as BOD, P, and PO 4 3- , which is in accordance with the fact that this model covers northern part of Serbia (Vojvodina Autonomous Province) which is well-known for agricultural production and extensive use of fertilizers. Both models have shown very good agreement between measured and predicted DO (with R 2  ≥ 0.86) and demonstrated that they can effectively forecast DO content in the Danube River.

A Single-Lap Joint Adhesive Bonding Optimization Method Using Gradient and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Smeltzer, Stanley S., III; Finckenor, Jeffrey L.

1999-01-01

A natural process for any engineer, scientist, educator, etc. is to seek the most efficient method for accomplishing a given task. In the case of structural design, an area that has a significant impact on the structural efficiency is joint design. Unless the structure is machined from a solid block of material, the individual components which compose the overall structure must be joined together. The method for joining a structure varies depending on the applied loads, material, assembly and disassembly requirements, service life, environment, etc. Using both metallic and fiber reinforced plastic materials limits the user to two methods or a combination of these methods for joining the components into one structure. The first is mechanical fastening and the second is adhesive bonding. Mechanical fastening is by far the most popular joining technique; however, in terms of structural efficiency, adhesive bonding provides a superior joint since the load is distributed uniformly across the joint. The purpose of this paper is to develop a method for optimizing single-lap joint adhesive bonded structures using both gradient and genetic algorithms and comparing the solution process for each method. The goal of the single-lap joint optimization is to find the most efficient structure that meets the imposed requirements while still remaining as lightweight, economical, and reliable as possible. For the single-lap joint, an optimum joint is determined by minimizing the weight of the overall joint based on constraints from adhesive strengths as well as empirically derived rules. The analytical solution of the sin-le-lap joint is determined using the classical Goland-Reissner technique for case 2 type adhesive joints. Joint weight minimization is achieved using a commercially available routine, Design Optimization Tool (DOT), for the gradient solution while an author developed method is used for the genetic algorithm solution. Results illustrate the critical design variables as a function of adhesive properties and convergences of different joints based on the two optimization methods.

Genetically Engineered Microelectronic Infrared Filters

NASA Technical Reports Server (NTRS)

Cwik, Tom; Klimeck, Gerhard

1998-01-01

A genetic algorithm is used for design of infrared filters and in the understanding of the material structure of a resonant tunneling diode. These two components are examples of microdevices and nanodevices that can be numerically simulated using fundamental mathematical and physical models. Because the number of parameters that can be used in the design of one of these devices is large, and because experimental exploration of the design space is unfeasible, reliable software models integrated with global optimization methods are examined The genetic algorithm and engineering design codes have been implemented on massively parallel computers to exploit their high performance. Design results are presented for the infrared filter showing new and optimized device design. Results for nanodevices are presented in a companion paper at this workshop.

Robust optimization of the billet for isothermal local loading transitional region of a Ti-alloy rib-web component based on dual-response surface method

NASA Astrophysics Data System (ADS)

Wei, Ke; Fan, Xiaoguang; Zhan, Mei; Meng, Miao

2018-03-01

Billet optimization can greatly improve the forming quality of the transitional region in the isothermal local loading forming (ILLF) of large-scale Ti-alloy ribweb components. However, the final quality of the transitional region may be deteriorated by uncontrollable factors, such as the manufacturing tolerance of the preforming billet, fluctuation of the stroke length, and friction factor. Thus, a dual-response surface method (RSM)-based robust optimization of the billet was proposed to address the uncontrollable factors in transitional region of the ILLF. Given that the die underfilling and folding defect are two key factors that influence the forming quality of the transitional region, minimizing the mean and standard deviation of the die underfilling rate and avoiding folding defect were defined as the objective function and constraint condition in robust optimization. Then, the cross array design was constructed, a dual-RSM model was established for the mean and standard deviation of the die underfilling rate by considering the size parameters of the billet and uncontrollable factors. Subsequently, an optimum solution was derived to achieve the robust optimization of the billet. A case study on robust optimization was conducted. Good results were attained for improving the die filling and avoiding folding defect, suggesting that the robust optimization of the billet in the transitional region of the ILLF was efficient and reliable.

Advanced rotorcraft control using parameter optimization

NASA Technical Reports Server (NTRS)

Vansteenwyk, Brett; Ly, Uy-Loi

1991-01-01

A reliable algorithm for the evaluation of a quadratic performance index and its gradients with respect to the controller design parameters is presented. The algorithm is part of a design algorithm for an optimal linear dynamic output feedback controller that minimizes a finite time quadratic performance index. The numerical scheme is particularly robust when it is applied to the control law synthesis for systems with densely packed modes and where there is a high likelihood of encountering degeneracies in the closed loop eigensystem. This approach through the use of a accurate Pade series approximation does not require the closed loop system matrix to be diagonalizable. The algorithm has been included in a control design package for optimal robust low order controllers. Usefulness of the proposed numerical algorithm has been demonstrated using numerous practical design cases where degeneracies occur frequently in the closed loop system under an arbitrary controller design initialization and during the numerical search.

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.

Recent Advances of MEMS Resonators for Lorentz Force Based Magnetic Field Sensors: Design, Applications and Challenges.

PubMed

Herrera-May, Agustín Leobardo; Soler-Balcazar, Juan Carlos; Vázquez-Leal, Héctor; Martínez-Castillo, Jaime; Vigueras-Zuñiga, Marco Osvaldo; Aguilera-Cortés, Luz Antonio

2016-08-24

Microelectromechanical systems (MEMS) resonators have allowed the development of magnetic field sensors with potential applications such as biomedicine, automotive industry, navigation systems, space satellites, telecommunications and non-destructive testing. We present a review of recent magnetic field sensors based on MEMS resonators, which operate with Lorentz force. These sensors have a compact structure, wide measurement range, low energy consumption, high sensitivity and suitable performance. The design methodology, simulation tools, damping sources, sensing techniques and future applications of magnetic field sensors are discussed. The design process is fundamental in achieving correct selection of the operation principle, sensing technique, materials, fabrication process and readout systems of the sensors. In addition, the description of the main sensing systems and challenges of the MEMS sensors are discussed. To develop the best devices, researches of their mechanical reliability, vacuum packaging, design optimization and temperature compensation circuits are needed. Future applications will require multifunctional sensors for monitoring several physical parameters (e.g., magnetic field, acceleration, angular ratio, humidity, temperature and gases).

Recent Advances of MEMS Resonators for Lorentz Force Based Magnetic Field Sensors: Design, Applications and Challenges

PubMed Central

Herrera-May, Agustín Leobardo; Soler-Balcazar, Juan Carlos; Vázquez-Leal, Héctor; Martínez-Castillo, Jaime; Vigueras-Zuñiga, Marco Osvaldo; Aguilera-Cortés, Luz Antonio

2016-01-01

Microelectromechanical systems (MEMS) resonators have allowed the development of magnetic field sensors with potential applications such as biomedicine, automotive industry, navigation systems, space satellites, telecommunications and non-destructive testing. We present a review of recent magnetic field sensors based on MEMS resonators, which operate with Lorentz force. These sensors have a compact structure, wide measurement range, low energy consumption, high sensitivity and suitable performance. The design methodology, simulation tools, damping sources, sensing techniques and future applications of magnetic field sensors are discussed. The design process is fundamental in achieving correct selection of the operation principle, sensing technique, materials, fabrication process and readout systems of the sensors. In addition, the description of the main sensing systems and challenges of the MEMS sensors are discussed. To develop the best devices, researches of their mechanical reliability, vacuum packaging, design optimization and temperature compensation circuits are needed. Future applications will require multifunctional sensors for monitoring several physical parameters (e.g., magnetic field, acceleration, angular ratio, humidity, temperature and gases). PMID:27563912

Reliable Adaptive Data Aggregation Route Strategy for a Trade-off between Energy and Lifetime in WSNs

PubMed Central

Guo, Wenzhong; Hong, Wei; Zhang, Bin; Chen, Yuzhong; Xiong, Naixue

2014-01-01

Mobile security is one of the most fundamental problems in Wireless Sensor Networks (WSNs). The data transmission path will be compromised for some disabled nodes. To construct a secure and reliable network, designing an adaptive route strategy which optimizes energy consumption and network lifetime of the aggregation cost is of great importance. In this paper, we address the reliable data aggregation route problem for WSNs. Firstly, to ensure nodes work properly, we propose a data aggregation route algorithm which improves the energy efficiency in the WSN. The construction process achieved through discrete particle swarm optimization (DPSO) saves node energy costs. Then, to balance the network load and establish a reliable network, an adaptive route algorithm with the minimal energy and the maximum lifetime is proposed. Since it is a non-linear constrained multi-objective optimization problem, in this paper we propose a DPSO with the multi-objective fitness function combined with the phenotype sharing function and penalty function to find available routes. Experimental results show that compared with other tree routing algorithms our algorithm can effectively reduce energy consumption and trade off energy consumption and network lifetime. PMID:25215944

Coupled Multi-Disciplinary Optimization for Structural Reliability and Affordability

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

A computational simulation method is presented for Non-Deterministic Multidisciplinary Optimization of engine composite materials and structures. A hypothetical engine duct made with ceramic matrix composites (CMC) is evaluated probabilistically in the presence of combined thermo-mechanical loading. The structure is tailored by quantifying the uncertainties in all relevant design variables such as fabrication, material, and loading parameters. The probabilistic sensitivities are used to select critical design variables for optimization. In this paper, two approaches for non-deterministic optimization are presented. The non-deterministic minimization of combined failure stress criterion is carried out by: (1) performing probabilistic evaluation first and then optimization and (2) performing optimization first and then probabilistic evaluation. The first approach shows that the optimization feasible region can be bounded by a set of prescribed probability limits and that the optimization follows the cumulative distribution function between those limits. The second approach shows that the optimization feasible region is bounded by 0.50 and 0.999 probabilities.

Sediment transport modeling in deposited bed sewers: unified form of May's equations using the particle swarm optimization algorithm.

PubMed

Safari, Mir Jafar Sadegh; Shirzad, Akbar; Mohammadi, Mirali

2017-08-01

May proposed two dimensionless parameters of transport (η) and mobility (F s ) for self-cleansing design of sewers with deposited bed condition. The relationships between those two parameters were introduced in conditional form for specific ranges of F s , which makes it difficult to use as a practical tool for sewer design. In this study, using the same experimental data used by May and employing the particle swarm optimization algorithm, a unified equation is recommended based on η and F s . The developed model is compared with original May relationships as well as corresponding models available in the literature. A large amount of data taken from the literature is used for the models' evaluation. The results demonstrate that the developed model in this study is superior to May and other existing models in the literature. Due to the fact that in May's dimensionless parameters more effective variables in the sediment transport process in sewers with deposited bed condition are considered, it is concluded that the revised May equation proposed in this study is a reliable model for sewer design.

Development of FAST.Farm: A New Multiphysics Engineering Tool for Wind Farm Design and Analysis: Preprint

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

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

2017-01-01

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

Development of a Robust and Cost-Effective Friction Stir Welding Process for Use in Advanced Military Vehicles

NASA Astrophysics Data System (ADS)

Grujicic, M.; Arakere, G.; Pandurangan, B.; Hariharan, A.; Yen, C.-F.; Cheeseman, B. A.

2011-02-01

To respond to the advent of more lethal threats, recently designed aluminum-armor-based military-vehicle systems have resorted to an increasing use of higher strength aluminum alloys (with superior ballistic resistance against armor piercing (AP) threats and with high vehicle-light weighing potential). Unfortunately, these alloys are not very amenable to conventional fusion-based welding technologies and in-order to obtain high-quality welds, solid-state joining technologies such as Friction stir welding (FSW) have to be employed. However, since FSW is a relatively new and fairly complex joining technology, its introduction into advanced military vehicle structures is not straight forward and entails a comprehensive multi-step approach. One such (three-step) approach is developed in the present work. Within the first step, experimental and computational techniques are utilized to determine the optimal tool design and the optimal FSW process parameters which result in maximal productivity of the joining process and the highest quality of the weld. Within the second step, techniques are developed for the identification and qualification of the optimal weld joint designs in different sections of a prototypical military vehicle structure. In the third step, problems associated with the fabrication of a sub-scale military vehicle test structure and the blast survivability of the structure are assessed. The results obtained and the lessons learned are used to judge the potential of the current approach in shortening the development time and in enhancing reliability and blast survivability of military vehicle structures.

Rational risk-based decision support for drinking water well managers by optimized monitoring designs

NASA Astrophysics Data System (ADS)

Enzenhöfer, R.; Geiges, A.; Nowak, W.

2011-12-01

Advection-based well-head protection zones are commonly used to manage the contamination risk of drinking water wells. Considering the insufficient knowledge about hazards and transport properties within the catchment, current Water Safety Plans recommend that catchment managers and stakeholders know, control and monitor all possible hazards within the catchments and perform rational risk-based decisions. Our goal is to supply catchment managers with the required probabilistic risk information, and to generate tools that allow for optimal and rational allocation of resources between improved monitoring versus extended safety margins and risk mitigation measures. To support risk managers with the indispensable information, we address the epistemic uncertainty of advective-dispersive solute transport and well vulnerability (Enzenhoefer et al., 2011) within a stochastic simulation framework. Our framework can separate between uncertainty of contaminant location and actual dilution of peak concentrations by resolving heterogeneity with high-resolution Monte-Carlo simulation. To keep computational costs low, we solve the reverse temporal moment transport equation. Only in post-processing, we recover the time-dependent solute breakthrough curves and the deduced well vulnerability criteria from temporal moments by non-linear optimization. Our first step towards optimal risk management is optimal positioning of sampling locations and optimal choice of data types to reduce best the epistemic prediction uncertainty for well-head delineation, using the cross-bred Likelihood Uncertainty Estimator (CLUE, Leube et al., 2011) for optimal sampling design. Better monitoring leads to more reliable and realistic protection zones and thus helps catchment managers to better justify smaller, yet conservative safety margins. In order to allow an optimal choice in sampling strategies, we compare the trade-off in monitoring versus the delineation costs by accounting for ill-delineated fractions of protection zones. Within an illustrative simplified 2D synthetic test case, we demonstrate our concept, involving synthetic transmissivity and head measurements for conditioning. We demonstrate the worth of optimally collected data in the context of protection zone delineation by assessing the reduced areal demand of delineated area at user-specified risk acceptance level. Results indicate that, thanks to optimally collected data, risk-aware delineation can be made at low to moderate additional costs compared to conventional delineation strategies.

Experimental design for evaluating WWTP data by linear mass balances.

PubMed

Le, Quan H; Verheijen, Peter J T; van Loosdrecht, Mark C M; Volcke, Eveline I P

2018-05-15

A stepwise experimental design procedure to obtain reliable data from wastewater treatment plants (WWTPs) was developed. The proposed procedure aims at determining sets of additional measurements (besides available ones) that guarantee the identifiability of key process variables, which means that their value can be calculated from other, measured variables, based on available constraints in the form of linear mass balances. Among all solutions, i.e. all possible sets of additional measurements allowing the identifiability of all key process variables, the optimal solutions were found taking into account two objectives, namely the accuracy of the identified key variables and the cost of additional measurements. The results of this multi-objective optimization problem were represented in a Pareto-optimal front. The presented procedure was applied to a full-scale WWTP. Detailed analysis of the relation between measurements allowed the determination of groups of overlapping mass balances. Adding measured variables could only serve in identifying key variables that appear in the same group of mass balances. Besides, the application of the experimental design procedure to these individual groups significantly reduced the computational effort in evaluating available measurements and planning additional monitoring campaigns. The proposed procedure is straightforward and can be applied to other WWTPs with or without prior data collection. Copyright © 2018 Elsevier Ltd. All rights reserved.

Reliable data storage system design and implementation for acoustic logging while drilling

NASA Astrophysics Data System (ADS)

Hao, Xiaolong; Ju, Xiaodong; Wu, Xiling; Lu, Junqiang; Men, Baiyong; Yao, Yongchao; Liu, Dong

2016-12-01

Owing to the limitations of real-time transmission, reliable downhole data storage and fast ground reading have become key technologies in developing tools for acoustic logging while drilling (LWD). In order to improve the reliability of the downhole storage system in conditions of high temperature, intensive shake and periodic power supply, improvements were made in terms of hardware and software. In hardware, we integrated the storage system and data acquisition control module into one circuit board, to reduce the complexity of the storage process, by adopting the controller combination of digital signal processor and field programmable gate array. In software, we developed a systematic management strategy for reliable storage. Multiple-backup independent storage was employed to increase the data redundancy. A traditional error checking and correction (ECC) algorithm was improved and we embedded the calculated ECC code into all management data and waveform data. A real-time storage algorithm for arbitrary length data was designed to actively preserve the storage scene and ensure the independence of the stored data. The recovery procedure of management data was optimized to realize reliable self-recovery. A new bad block management idea of static block replacement and dynamic page mark was proposed to make the period of data acquisition and storage more balanced. In addition, we developed a portable ground data reading module based on a new reliable high speed bus to Ethernet interface to achieve fast reading of the logging data. Experiments have shown that this system can work stably below 155 °C with a periodic power supply. The effective ground data reading rate reaches 1.375 Mbps with 99.7% one-time success rate at room temperature. This work has high practical application significance in improving the reliability and field efficiency of acoustic LWD tools.

Assuring Electronics Reliability: What Could and Should Be Done Differently

NASA Astrophysics Data System (ADS)

Suhir, E.

The following “ ten commandments” for the predicted and quantified reliability of aerospace electronic, and photonic products are addressed and discussed: 1) The best product is the best compromise between the needs for reliability, cost effectiveness and time-to-market; 2) Reliability cannot be low, need not be higher than necessary, but has to be adequate for a particular product; 3) When reliability is imperative, ability to quantify it is a must, especially if optimization is considered; 4) One cannot design a product with quantified, optimized and assured reliability by limiting the effort to the highly accelerated life testing (HALT) that does not quantify reliability; 5) Reliability is conceived at the design stage and should be taken care of, first of all, at this stage, when a “ genetically healthy” product should be created; reliability evaluations and assurances cannot be delayed until the product is fabricated and shipped to the customer, i.e., cannot be left to the prognostics-and-health-monitoring/managing (PHM) stage; it is too late at this stage to change the design or the materials for improved reliability; that is why, when reliability is imperative, users re-qualify parts to assess their lifetime and use redundancy to build a highly reliable system out of insufficiently reliable components; 6) Design, fabrication, qualification and PHM efforts should consider and be specific for particular products and their most likely actual or at least anticipated application(s); 7) Probabilistic design for reliability (PDfR) is an effective means for improving the state-of-the-art in the field: nothing is perfect, and the difference between an unreliable product and a robust one is “ merely” the probability of failure (PoF); 8) Highly cost-effective and highly focused failure oriented accelerated testing (FOAT) geared to a particular pre-determined reliability model and aimed at understanding the physics of failure- anticipated by this model is an important constituent part of the PDfR effort; 9) Predictive modeling (PM) is another important constituent of the PDfR approach; in combination with FOAT, it is a powerful means to carry out sensitivity analyses (SA), to quantify and nearly eliminate failures (“ principle of practical confidence” ); 10) Consistent, comprehensive and physically meaningful PDfR can effectively contribute to the most feasible and the most effective qualification test (QT) methodologies, practices and specifications. The general concepts addressed in the paper are illustrated by numerical examples. It is concluded that although the suggested concept is promising and fruitful, further research, refinement, and validations are needed before this concept becomes widely accepted by the engineering community and implemented into practice. It is important that this novel approach is introduced gradually, whenever feasible and appropriate, in addition to, and in some situations even instead of, the currently employed various types and modifications of the forty year old HALT.

Vortex-assisted surfactant-enhanced emulsification microextraction combined with LC-MS/MS for the determination of glucocorticoids in water with the aid of experimental design.

PubMed

Asati, Ankita; Satyanarayana, G N V; Patel, Devendra K

2017-04-01

An efficient and inexpensive method using vortex-assisted surfactant-enhanced emulsification microextraction (VASEME) based on solidification of floating organic droplet coupled with ultraperformance liquid chromatography-tandem mass spectrometry is proposed for the analysis of glucocorticoids in water samples (river water and hospital wastewater). VASEME was optimized by the experimental validation of Plackett-Burman design and central composite design, which has been co-related to experimental design. Plackett-Burman design showed that factors such as vortex time, surfactant concentration, and pH significantly affect the extraction efficiency of the method. Method validation was characterized by an acceptable calibration range of 1-1000 ng L -1 , and the limit of detection was in the range from 2.20 to 8.12 ng L -1 for glucocorticoids. The proposed method was applied to determine glucocorticoids in river water and hospital wastewater in Lucknow, India. It is reliable and rapid and has potential application for analysis of glucocorticoids in environmental aqueous samples. Graphical Abstract Low density based extraction of gluococorticoids by using design of experiment.

Effect of Processing Parameters on Reliability of VARTM/SCRIMP Composite Panels - Phase 1

DTIC Science & Technology

2007-07-01

used in this program (Hess and Beach, 2000). The structural risks associated with new FRP composite ship structures can be mitigated by...reliability calibration of new designs. This program focuses on addressing the first and second tasks outlined above. 1.2. Phase I - Objectives The...Accomplishments: Tension Testing An optimized geometry for tension coupon testing was developed for marine grade composites. The new geometry reduces

Genetic Algorithm (GA)-Based Inclinometer Layout Optimization.

PubMed

Liang, Weijie; Zhang, Ping; Chen, Xianping; Cai, Miao; Yang, Daoguo

2015-04-17

This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors.

Genetic Algorithm (GA)-Based Inclinometer Layout Optimization

PubMed Central

Liang, Weijie; Zhang, Ping; Chen, Xianping; Cai, Miao; Yang, Daoguo

2015-01-01

This paper presents numerical simulation results of an airflow inclinometer with sensitivity studies and thermal optimization of the printed circuit board (PCB) layout for an airflow inclinometer based on a genetic algorithm (GA). Due to the working principle of the gas sensor, the changes of the ambient temperature may cause dramatic voltage drifts of sensors. Therefore, eliminating the influence of the external environment for the airflow is essential for the performance and reliability of an airflow inclinometer. In this paper, the mechanism of an airflow inclinometer and the influence of different ambient temperatures on the sensitivity of the inclinometer will be examined by the ANSYS-FLOTRAN CFD program. The results show that with changes of the ambient temperature on the sensing element, the sensitivity of the airflow inclinometer is inversely proportional to the ambient temperature and decreases when the ambient temperature increases. GA is used to optimize the PCB thermal layout of the inclinometer. The finite-element simulation method (ANSYS) is introduced to simulate and verify the results of our optimal thermal layout, and the results indicate that the optimal PCB layout greatly improves (by more than 50%) the sensitivity of the inclinometer. The study may be useful in the design of PCB layouts that are related to sensitivity improvement of gas sensors. PMID:25897500

Hot and cold body reference noise generators from 0 to 40 GHz

NASA Technical Reports Server (NTRS)

Hornbostel, D. H.

1974-01-01

This article describes the design, development, and analysis of exceptionally accurate radiometric noise generators from 0-40 GHz to serve as standard references. Size, weight, power, and reliability are optimized to meet the requirements of NASA air- and space-borne radiometers. The radiometric noise temperature of these noise generators is, unavoidably, calculated from measured values rather than measured directly. The absolute accuracy and stability are equal to or better than those of reliable standards available for comparison. A noise generator has been developed whose measurable properties (VSWR, line loss, thermometric temperatures) have been optimized in order to minimize the effects of the uncertainty in the calculated radiometric noise temperatures. Each measurable property is evaluated and analyzed to determine the effects of the uncertainty of the measured value. Unmeasurable properties (primarily temperature gradients) are analyzed, and reasonable precautions are designed into the noise generator to guarantee that the uncertainty of the value remains within tolerable limits.

The optimization on flow scheme of helium liquefier with genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, H. R.; Xiong, L. Y.; Peng, N.; Liu, L. Q.

2017-01-01

There are several ways to organize the flow scheme of the helium liquefiers, such as arranging the expanders in parallel (reverse Brayton stage) or in series (modified Brayton stages). In this paper, the inlet mass flow and temperatures of expanders in Collins cycle are optimized using genetic algorithm (GA). Results show that maximum liquefaction rate can be obtained when the system is working at the optimal parameters. However, the reliability of the system is not well due to high wheel speed of the first turbine. Study shows that the scheme in which expanders are arranged in series with heat exchangers between them has higher operation reliability but lower plant efficiency when working at the same situation. Considering both liquefaction rate and system stability, another flow scheme is put forward hoping to solve the dilemma. The three configurations are compared from different aspects, they are respectively economic cost, heat exchanger size, system reliability and exergy efficiency. In addition, the effect of heat capacity ratio on heat transfer efficiency is discussed. A conclusion of choosing liquefier configuration is given in the end, which is meaningful for the optimal design of helium liquefier.

Compressive spectral testbed imaging system based on thin-film color-patterned filter arrays.

PubMed

Rueda, Hoover; Arguello, Henry; Arce, Gonzalo R

2016-11-20

Compressive spectral imaging systems can reliably capture multispectral data using far fewer measurements than traditional scanning techniques. In this paper, a thin-film patterned filter array-based compressive spectral imager is demonstrated, including its optical design and implementation. The use of a patterned filter array entails a single-step three-dimensional spatial-spectral coding on the input data cube, which provides higher flexibility on the selection of voxels being multiplexed on the sensor. The patterned filter array is designed and fabricated with micrometer pitch size thin films, referred to as pixelated filters, with three different wavelengths. The performance of the system is evaluated in terms of references measured by a commercially available spectrometer and the visual quality of the reconstructed images. Different distributions of the pixelated filters, including random and optimized structures, are explored.

The Design of Finite State Machine for Asynchronous Replication Protocol

NASA Astrophysics Data System (ADS)

Wang, Yanlong; Li, Zhanhuai; Lin, Wei; Hei, Minglei; Hao, Jianhua

Data replication is a key way to design a disaster tolerance system and to achieve reliability and availability. It is difficult for a replication protocol to deal with the diverse and complex environment. This means that data is less well replicated than it ought to be. To reduce data loss and to optimize replication protocols, we (1) present a finite state machine, (2) run it to manage an asynchronous replication protocol and (3) report a simple evaluation of the asynchronous replication protocol based on our state machine. It's proved that our state machine is applicable to guarantee the asynchronous replication protocol running in the proper state to the largest extent in the event of various possible events. It also can helpful to build up replication-based disaster tolerance systems to ensure the business continuity.

The T/R modules for phased-array antennas

NASA Astrophysics Data System (ADS)

Peignet, Colette; Mancuso, Yves; Resneau, J. Claude

1990-09-01

The concept of phased array radar is critically dependent on the availability of compact, reliable and low power consuming Transmitter/Receiver (T/R) modules. An overview is given on two major programs actually at development stage within the Thomson group and on three major development axis (electrical concept optimization, packaging, and size reduction). The technical feasibility of the concept was proven and the three major axis were enlightened, based on reliability, power added efficiency, and RF tests optimization.

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

Jonkman, Jason; Annoni, Jennifer; Hayman, Greg

This paper presents the development of FAST.Farm, a new multiphysics tool applicable to engineering problems in research and industry involving wind farm performance and cost optimization that is needed to address the current underperformance, failures, and expenses plaguing the wind industry. Achieving wind cost-of-energy targets - which requires improvements in wind farm performance and reliability, together with reduced uncertainty and expenditures - has been eluded by the complicated nature of the wind farm design problem, especially the sophisticated interaction between atmospheric phenomena and wake dynamics and array effects. FAST.Farm aims to balance the need for accurate modeling of the relevantmore » physics for predicting power performance and loads while maintaining low computational cost to support a highly iterative and probabilistic design process and system-wide optimization. FAST.Farm makes use of FAST to model the aero-hydro-servo-elastics of distinct turbines in the wind farm, and it is based on some of the principles of the Dynamic Wake Meandering (DWM) model, but avoids many of the limitations of existing DWM implementations.« less

High-throughput design and optimization of fast lithium ion conductors by the combination of bond-valence method and density functional theory

NASA Astrophysics Data System (ADS)

Xiao, Ruijuan; Li, Hong; Chen, Liquan

2015-09-01

Looking for solid state electrolytes with fast lithium ion conduction is an important prerequisite for developing all-solid-state lithium secondary batteries. By combining the simulation techniques in different levels of accuracy, e.g. the bond-valence (BV) method and the density functional theory (DFT), a high-throughput design and optimization scheme is proposed for searching fast lithium ion conductors as candidate solid state electrolytes for lithium rechargeable batteries. The screening from more than 1000 compounds is performed through BV-based method, and the ability to predict reliable tendency of the Li+ migration energy barriers is confirmed by comparing with the results from DFT calculations. β-Li3PS4 is taken as a model system to demonstrate the application of this combination method in optimizing properties of solid electrolytes. By employing the high-throughput DFT simulations to more than 200 structures of the doping derivatives of β-Li3PS4, the effects of doping on the ionic conductivities in this material are predicted by the BV calculations. The O-doping scheme is proposed as a promising way to improve the kinetic properties of this materials, and the validity of the optimization is proved by the first-principles molecular dynamics (FPMD) simulations.

An analytic model for footprint dispersions and its application to mission design

NASA Technical Reports Server (NTRS)

Rao, J. R. Jagannatha; Chen, Yi-Chao

1992-01-01

This is the final report on our recent research activities that are complementary to those conducted by our colleagues, Professor Farrokh Mistree and students, in the context of the Taguchi method. We have studied the mathematical model that forms the basis of the Simulation and Optimization of Rocket Trajectories (SORT) program and developed an analytic method for determining mission reliability with a reduced number of flight simulations. This method can be incorporated in a design algorithm to mathematically optimize different performance measures of a mission, thus leading to a robust and easy-to-use methodology for mission planning and design.

Estimates Of The Orbiter RSI Thermal Protection System Thermal Reliability

NASA Technical Reports Server (NTRS)

Kolodziej, P.; Rasky, D. J.

2002-01-01

In support of the Space Shuttle Orbiter post-flight inspection, structure temperatures are recorded at selected positions on the windward, leeward, starboard and port surfaces. Statistical analysis of this flight data and a non-dimensional load interference (NDLI) method are used to estimate the thermal reliability at positions were reusable surface insulation (RSI) is installed. In this analysis, structure temperatures that exceed the design limit define the critical failure mode. At thirty-three positions the RSI thermal reliability is greater than 0.999999 for the missions studied. This is not the overall system level reliability of the thermal protection system installed on an Orbiter. The results from two Orbiters, OV-102 and OV-105, are in good agreement. The original RSI designs on the OV-102 Orbital Maneuvering System pods, which had low reliability, were significantly improved on OV-105. The NDLI method was also used to estimate thermal reliability from an assessment of TPS uncertainties that was completed shortly before the first Orbiter flight. Results fiom the flight data analysis and the pre-flight assessment agree at several positions near each other. The NDLI method is also effective for optimizing RSI designs to provide uniform thermal reliability on the acreage surface of reusable launch vehicles.

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

Kisner, R.; Melin, A.; Burress, T.

The objective of this project is to demonstrate improved reliability and increased performance made possible by deeply embedding instrumentation and controls (I&C) in nuclear power plant (NPP) components and systems. The project is employing a highly instrumented canned rotor, magnetic bearing, fluoride salt pump as its I&C technology demonstration platform. I&C is intimately part of the basic millisecond-by-millisecond functioning of the system; treating I&C as an integral part of the system design is innovative and will allow significant improvement in capabilities and performance. As systems become more complex and greater performance is required, traditional I&C design techniques become inadequate andmore » more advanced I&C needs to be applied. New I&C techniques enable optimal and reliable performance and tolerance of noise and uncertainties in the system rather than merely monitoring quasistable performance. Traditionally, I&C has been incorporated in NPP components after the design is nearly complete; adequate performance was obtained through over-design. By incorporating I&C at the beginning of the design phase, the control system can provide superior performance and reliability and enable designs that are otherwise impossible. This report describes the progress and status of the project and provides a conceptual design overview for the platform to demonstrate the performance and reliability improvements enabled by advanced embedded I&C.« less

Salient object detection based on discriminative boundary and multiple cues integration

NASA Astrophysics Data System (ADS)

Jiang, Qingzhu; Wu, Zemin; Tian, Chang; Liu, Tao; Zeng, Mingyong; Hu, Lei

2016-01-01

In recent years, many saliency models have achieved good performance by taking the image boundary as the background prior. However, if all boundaries of an image are equally and artificially selected as background, misjudgment may happen when the object touches the boundary. We propose an algorithm called weighted contrast optimization based on discriminative boundary (wCODB). First, a background estimation model is reliably constructed through discriminating each boundary via Hausdorff distance. Second, the background-only weighted contrast is improved by fore-background weighted contrast, which is optimized through weight-adjustable optimization framework. Then to objectively estimate the quality of a saliency map, a simple but effective metric called spatial distribution of saliency map and mean saliency in covered window ratio (MSR) is designed. Finally, in order to further promote the detection result using MSR as the weight, we propose a saliency fusion framework to integrate three other cues-uniqueness, distribution, and coherence from three representative methods into our wCODB model. Extensive experiments on six public datasets demonstrate that our wCODB performs favorably against most of the methods based on boundary, and the integrated result outperforms all state-of-the-art methods.

Reinforcement Learning Strategies for Clinical Trials in Non-small Cell Lung Cancer

PubMed Central

Zhao, Yufan; Zeng, Donglin; Socinski, Mark A.; Kosorok, Michael R.

2010-01-01

Summary Typical regimens for advanced metastatic stage IIIB/IV non-small cell lung cancer (NSCLC) consist of multiple lines of treatment. We present an adaptive reinforcement learning approach to discover optimal individualized treatment regimens from a specially designed clinical trial (a “clinical reinforcement trial”) of an experimental treatment for patients with advanced NSCLC who have not been treated previously with systemic therapy. In addition to the complexity of the problem of selecting optimal compounds for first and second-line treatments based on prognostic factors, another primary goal is to determine the optimal time to initiate second-line therapy, either immediately or delayed after induction therapy, yielding the longest overall survival time. A reinforcement learning method called Q-learning is utilized which involves learning an optimal regimen from patient data generated from the clinical reinforcement trial. Approximating the Q-function with time-indexed parameters can be achieved by using a modification of support vector regression which can utilize censored data. Within this framework, a simulation study shows that the procedure can extract optimal regimens for two lines of treatment directly from clinical data without prior knowledge of the treatment effect mechanism. In addition, we demonstrate that the design reliably selects the best initial time for second-line therapy while taking into account the heterogeneity of NSCLC across patients. PMID:21385164

The in situ aeration in an old landfill in China: Multi-wells optimization method and application.

PubMed

Liu, Lei; Ma, Jun; Xue, Qiang; Shao, Jingbang; Chen, Yijun; Zeng, Gang

2018-06-01

The optimization design of well spacing (WS) and aeration rate (AR) is crucial to the in situ aeration system operation in under long-term and high-efficiency conditions. This optimization design aims to transport additional air into landfills and to develop an improved oxygen environment for enhancing aerobic degradation. Given the specific pore structure distribution within landfills, providing sufficient oxygen in all waste bodies in field sites through gas wells is difficult. The design of well distribution also lacks adequate criteria. In this work, the multi-well optimization aeration method (MWOAM) was proposed to select the WS and AR from prediction results that consider gas transport properties by maximizing oxygen storage ratio (OSR) as the key objective threshold. This method was applied to the aeration restoration engineering in Jinkou landfill, which represents the first full-scale application of an aeration project in China, to optimize the operation scheme of the aeration system. Results of the gas concentration monitoring show that the trend of the OSR with aeration time based on the measurement agrees with the prediction. The oxygen and methane contents remain high and low within the landfill during the aeration process, respectively. Moreover, the temperature in the waste body did not exceed the upper limit value. These results suggested that the MWOAM is an effective means of supplying sufficient oxygen content across the landfill body and extend the aeration system operation for the long term. Therefore, this work provides reliable evidence to support the design and operation management of the aeration systems in full-scale landfills. Copyright © 2018 Elsevier Ltd. All rights reserved.

Blackcomb: Hardware-Software Co-design for Non-Volatile Memory in Exascale Systems

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

Schreiber, Robert

Summary of technical results of Blackcomb Memory Devices We explored various different memory technologies (STTRAM, PCRAM, FeRAM, and ReRAM). The progress can be classified into three categories, below. Modeling and Tool Releases Various modeling tools have been developed over the last decade to help in the design of SRAM or DRAM-based memory hierarchies. To explore new design opportunities that NVM technologies can bring to the designers, we have developed similar high-level models for NVM, including PCRAMsim [Dong 2009], NVSim [Dong 2012], and NVMain [Poremba 2012]. NVSim is a circuit-level model for NVM performance, energy, and area estimation, which supports variousmore » NVM technologies, including STT-RAM, PCRAM, ReRAM, and legacy NAND Flash. NVSim is successfully validated against industrial NVM prototypes, and it is expected to help boost architecture-level NVM-related studies. On the other side, NVMain is a cycle accurate main memory simulator designed to simulate emerging nonvolatile memories at the architectural level. We have released these models as open source tools and provided contiguous support to them. We also proposed PS3-RAM, which is a fast, portable and scalable statistical STT-RAM reliability analysis model [Wen 2012]. Design Space Exploration and Optimization With the support of these models, we explore different device/circuit optimization techniques. For example, in [Niu 2012a] we studied the power reduction technique for the application of ECC scheme in ReRAM designs and proposed to use ECC code to relax the BER (Bit Error Rate) requirement of a single memory to improve the write energy consumption and latency for both 1T1R and cross-point ReRAM designs. In [Xu 2011], we proposed a methodology to design STT-RAM for different optimization goals such as read performance, write performance and write energy by leveraging the trade-off between write current and write time of MTJ. We also studied the tradeoffs in building a reliable crosspoint ReRAM array [Niu 2012b]. We have conducted an in depth analysis of the circuit and system level design implications of multi-layer cross-point Resistive RAM (MLCReRAM) from performance, power and reliability perspectives [Xu 2013]. The objective of this study is to understand the design trade-offs of this technology with respect to the MLC Phase Change Memory (MLCPCM).Our MLC ReRAM design at the circuit and system levels indicates that different resistance allocation schemes, programming strategies, peripheral designs, and material selections profoundly affect the area, latency, power, and reliability of MLC ReRAM. Based on this analysis, we conduct two case studies: first we compare MLC ReRAM design against MLC phase-change memory (PCM) and multi-layer cross-point ReRAM design, and point out why multi-level ReRAM is appealing; second we further explore the design space for MLC ReRAM. Architecture and Application We explored hybrid checkpointing using phase-change memory for future exascale systems [Dong 2011] and showed that the use of nonvolatile memory for local checkpointing significantly increases the number of faults covered by local checkpoints and reduces the probability of a global failure in the middle of a global checkpoint to less than 1%. We also proposed a technique called i2WAP to mitigate the write variations in NVM-based last-level cache for the improvement of the NVM lifetime [Wang 2013]. Our wear leveling technique attempts to work around the limitations of write endurance by arranging data access so that write operations can be distributed evenly across all the storage cells. During our intensive research on fault-tolerant NVM design, we found that ECC cannot effectively tolerate hard errors from limited write endurance and process imperfection. Therefore, we devised a novel Point and Discard (PAD) architecture in in [ 2012] as a hard-error-tolerant architecture for ReRAM-based Last Level Caches. PAD improves the lifetime of ReRAM caches by 1.6X-440X under different process variations without performance overhead in the system's early life. We have investigated the applicability of NVM for persistent memory design [Zhao 2013]. New byte addressable NVM enables fast persistent memory that allows in-memory persistent data objects to be updated with much higher throughput. Despite the significant improvement, the performance of these designs is only 50% of the native system with no persistence support, due to the logging or copy-on-write mechanisms used to update the persistent memory. A challenge in this approach is therefore how to efficiently enable atomic, consistent, and durable updates to ensure data persistence that survives application and/or system failures. We have designed a persistent memory system, called Klin, that can provide performance as close as that of the native system. The Klin design adopts a non-volatile cache and a non-volatile main memory for constructing a multi-versioned durable memory system, enabling atomic updates without logging or copy-on-write. Our evaluation shows that the proposed Kiln mechanism can achieve up to 2X of performance improvement to NVRAM-based persistent memory employing write-ahead logging. In addition, our design has numerous practical advantages: a simple and intuitive abstract interface, microarchitecture-level optimizations, fast recovery from failures, and no redundant writes to slow non-volatile storage media. The work was published in MICRO 2013 and received Best Paper Honorable Mentioned Award.« less

Optimizing study design for interobserver reliability: IUGA-ICS classification of complications of prostheses and graft insertion.

PubMed

Haylen, Bernard T; Lee, Joseph; Maher, Chris; Deprest, Jan; Freeman, Robert

2014-06-01

Results of interobserver reliability studies for the International Urogynecological Association-International Continence Society (IUGA-ICS) Complication Classification coding can be greatly influenced by study design factors such as participant instruction, motivation, and test-question clarity. We attempted to optimize these factors. After a 15-min instructional lecture with eight clinical case examples (including images) and with classification/coding charts available, those clinicians attending an IUGA Surgical Complications workshop were presented with eight similar-style test cases over 10 min and asked to code them using the Category, Time and Site classification. Answers were compared to predetermined correct codes obtained by five instigators of the IUGA-ICS prostheses and grafts complications classification. Prelecture and postquiz participant confidence levels using a five-step Likert scale were assessed. Complete sets of answers to the questions (24 codings) were provided by 34 respondents, only three of whom reported prior use of the charts. Average score [n (%)] out of eight, as well as median score (range) for each coding category were: (i) Category: 7.3 (91 %); 7 (4-8); (ii) Time: 7.8 (98 %); 7 (6-8); (iii) Site: 7.2 (90 %); 7 (5-8). Overall, the equivalent calculations (out of 24) were 22.3 (93 %) and 22 (18-24). Mean prelecture confidence was 1.37 (out of 5), rising to 3.85 postquiz. Urogynecologists had the highest correlation with correct coding, followed closely by fellows and general gynecologists. Optimizing training and study design can lead to excellent results for interobserver reliability of the IUGA-ICS Complication Classification coding, with increased participant confidence in complication-coding ability.

Status of the ITER Cryodistribution

NASA Astrophysics Data System (ADS)

Chang, H.-S.; Vaghela, H.; Patel, P.; Rizzato, A.; Cursan, M.; Henry, D.; Forgeas, A.; Grillot, D.; Sarkar, B.; Muralidhara, S.; Das, J.; Shukla, V.; Adler, E.

2017-12-01

Since the conceptual design of the ITER Cryodistribution many modifications have been applied due to both system optimization and improved knowledge of the clients’ requirements. Process optimizations in the Cryoplant resulted in component simplifications whereas increased heat load in some of the superconducting magnet systems required more complicated process configuration but also the removal of a cold box was possible due to component arrangement standardization. Another cold box, planned for redundancy, has been removed due to the Tokamak in-Cryostat piping layout modification. In this proceeding we will summarize the present design status and component configuration of the ITER Cryodistribution with all changes implemented which aim at process optimization and simplification as well as operational reliability, stability and flexibility.

Taguchi Approach to Design Optimization for Quality and Cost: An Overview

NASA Technical Reports Server (NTRS)

Unal, Resit; Dean, Edwin B.

1990-01-01

Calibrations to existing cost of doing business in space indicate that to establish human presence on the Moon and Mars with the Space Exploration Initiative (SEI) will require resources, felt by many, to be more than the national budget can afford. In order for SEI to succeed, we must actually design and build space systems at lower cost this time, even with tremendous increases in quality and performance requirements, such as extremely high reliability. This implies that both government and industry must change the way they do business. Therefore, new philosophy and technology must be employed to design and produce reliable, high quality space systems at low cost. In recognizing the need to reduce cost and improve quality and productivity, Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) have initiated Total Quality Management (TQM). TQM is a revolutionary management strategy in quality assurance and cost reduction. TQM requires complete management commitment, employee involvement, and use of statistical tools. The quality engineering methods of Dr. Taguchi, employing design of experiments (DOE), is one of the most important statistical tools of TQM for designing high quality systems at reduced cost. Taguchi methods provide an efficient and systematic way to optimize designs for performance, quality, and cost. Taguchi methods have been used successfully in Japan and the United States in designing reliable, high quality products at low cost in such areas as automobiles and consumer electronics. However, these methods are just beginning to see application in the aerospace industry. The purpose of this paper is to present an overview of the Taguchi methods for improving quality and reducing cost, describe the current state of applications and its role in identifying cost sensitive design parameters.

On Some Methods in Safety Evaluation in Geotechnics

NASA Astrophysics Data System (ADS)

Puła, Wojciech; Zaskórski, Łukasz

2015-06-01

The paper demonstrates how the reliability methods can be utilised in order to evaluate safety in geotechnics. Special attention is paid to the so-called reliability based design that can play a useful and complementary role to Eurocode 7. In the first part, a brief review of first- and second-order reliability methods is given. Next, two examples of reliability-based design are demonstrated. The first one is focussed on bearing capacity calculation and is dedicated to comparison with EC7 requirements. The second one analyses a rigid pile subjected to lateral load and is oriented towards working stress design method. In the second part, applications of random field to safety evaluations in geotechnics are addressed. After a short review of the theory a Random Finite Element algorithm to reliability based design of shallow strip foundation is given. Finally, two illustrative examples for cohesive and cohesionless soils are demonstrated.

High-performance and high-reliability SOT-6 packaged diplexer based on advanced IPD fabrication techniques

NASA Astrophysics Data System (ADS)

Qiang, Tian; Wang, Cong; Kim, Nam-Young

2017-08-01

A diplexer offering the advantages of compact size, high performance, and high reliability is proposed on the basis of advanced integrated passive device (IPD) fabrication techniques. The proposed diplexer is developed by combining a third-order low-pass filter (LPF) and a third-order high-pass filter (HPF), which are designed on the basis of the elliptic function prototype low-pass filter. Primary components, such as inductors and capacitors, are designed and fabricated with high Q-factor and appropriate values, and they are subsequently used to construct a compact diplexer having a chip area of 900 μm × 1100 μm (0.009 λ0 × 0.011 λ0, where λ0 is the guided wavelength). In addition, a small-outline transistor (SOT-6) packaging method is adopted, and reliability tests (including temperature, humidity, vibration, and pressure) are conducted to guarantee long-term stability and commercial success. The packaged measurement results indicate excellent RF performance with insertion losses of 1.39 dB and 0.75 dB at operation bands of 0.9 GHz and 1.8 GHz, respectively. The return loss is lower than 10 dB from 0.5 GHz to 4.0 GHz, while the isolation is higher than 15 dB from 0.5 GHz to 3.0 GHz. Thus, it can be concluded that the proposed SOT-6 packaged diplexer is a promising candidate for GSM/CDMA applications. Synthetic solution of diplexer design, RF performance optimization, fabrication process, packaging, RF response measurement, and reliability test is particularly explained and analyzed in this work.

Shape Optimization of Supersonic Turbines Using Response Surface and Neural Network Methods

NASA Technical Reports Server (NTRS)

Papila, Nilay; Shyy, Wei; Griffin, Lisa W.; Dorney, Daniel J.

2001-01-01

Turbine performance directly affects engine specific impulse, thrust-to-weight ratio, and cost in a rocket propulsion system. A global optimization framework combining the radial basis neural network (RBNN) and the polynomial-based response surface method (RSM) is constructed for shape optimization of a supersonic turbine. Based on the optimized preliminary design, shape optimization is performed for the first vane and blade of a 2-stage supersonic turbine, involving O(10) design variables. The design of experiment approach is adopted to reduce the data size needed by the optimization task. It is demonstrated that a major merit of the global optimization approach is that it enables one to adaptively revise the design space to perform multiple optimization cycles. This benefit is realized when an optimal design approaches the boundary of a pre-defined design space. Furthermore, by inspecting the influence of each design variable, one can also gain insight into the existence of multiple design choices and select the optimum design based on other factors such as stress and materials considerations.

Comparative Evaluation of Different Optimization Algorithms for Structural Design Applications

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

1996-01-01

Non-linear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Centre, a project was initiated to assess the performance of eight different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using the eight different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems, however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with Sequential Unconstrained Minimizations Technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Performance Trend of Different Algorithms for Structural Design Optimization

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

1996-01-01

Nonlinear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Center, a project was initiated to assess performance of different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with the sequential unconstrained minimizations technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

Reliability Analysis of Main-axis Control System of the Equatorial Antarctica Astronomical Telescope Based on Fault Tree

NASA Astrophysics Data System (ADS)

LI, Y.; Yang, S. H.

2017-05-01

The Antarctica astronomical telescopes work chronically on the top of the unattended South Pole, and they have only one chance to maintain every year. Due to the complexity of the optical, mechanical, and electrical systems, the telescopes are hard to be maintained and need multi-tasker expedition teams, which means an excessive awareness is essential for the reliability of the Antarctica telescopes. Based on the fault mechanism and fault mode of the main-axis control system for the equatorial Antarctica astronomical telescope AST3-3 (Antarctic Schmidt Telescopes 3-3), the method of fault tree analysis is introduced in this article, and we obtains the importance degree of the top event from the importance degree of the bottom event structure. From the above results, the hidden problems and weak links can be effectively found out, which will indicate the direction for promoting the stability of the system and optimizing the design of the system.

A lightweight thermal heat switch for redundant cryocooling on satellites

NASA Astrophysics Data System (ADS)

Dietrich, M.; Euler, A.; Thummes, G.

2017-04-01

A previously designed cryogenic thermal heat switch for space applications has been optimized for low mass, high structural stability, and reliability. The heat switch makes use of the large linear thermal expansion coefficient (CTE) of the thermoplastic UHMW-PE for actuation. A structure model, which includes the temperature dependent properties of the actuator, is derived to be able to predict the contact pressure between the switch parts. This pressure was used in a thermal model in order to predict the switch performance under different heat loads and operating temperatures. The two models were used to optimize the mass and stability of the switch. Its reliability was proven by cyclic actuation of the switch and by shaker tests.

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization

PubMed Central

Chen, Qingkui; Zhao, Deyu; Wang, Jingjuan

2017-01-01

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes’ diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services. PMID:28777325

RGCA: A Reliable GPU Cluster Architecture for Large-Scale Internet of Things Computing Based on Effective Performance-Energy Optimization.

PubMed

Fang, Yuling; Chen, Qingkui; Xiong, Neal N; Zhao, Deyu; Wang, Jingjuan

2017-08-04

This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of IoT data processing, similar to mainstream high performance computing, we use a GPU (Graphics Processing Unit) cluster to achieve better IoT services. Firstly, we present an energy consumption calculation method (ECCM) based on WSNs. Then, using the CUDA (Compute Unified Device Architecture) Programming model, we propose a Two-level Parallel Optimization Model (TLPOM) which exploits reasonable resource planning and common compiler optimization techniques to obtain the best blocks and threads configuration considering the resource constraints of each node. The key to this part is dynamic coupling Thread-Level Parallelism (TLP) and Instruction-Level Parallelism (ILP) to improve the performance of the algorithms without additional energy consumption. Finally, combining the ECCM and the TLPOM, we use the Reliable GPU Cluster Architecture (RGCA) to obtain a high-reliability computing system considering the nodes' diversity, algorithm characteristics, etc. The results show that the performance of the algorithms significantly increased by 34.1%, 33.96% and 24.07% for Fermi, Kepler and Maxwell on average with TLPOM and the RGCA ensures that our IoT computing system provides low-cost and high-reliability services.

Designing optimal universal pulses using second-order, large-scale, non-linear optimization

NASA Astrophysics Data System (ADS)

Anand, Christopher Kumar; Bain, Alex D.; Curtis, Andrew Thomas; Nie, Zhenghua

2012-06-01

Recently, RF pulse design using first-order and quasi-second-order pulses has been actively investigated. We present a full second-order design method capable of incorporating relaxation, inhomogeneity in B0 and B1. Our model is formulated as a generic optimization problem making it easy to incorporate diverse pulse sequence features. To tame the computational cost, we present a method of calculating second derivatives in at most a constant multiple of the first derivative calculation time, this is further accelerated by using symbolic solutions of the Bloch equations. We illustrate the relative merits and performance of quasi-Newton and full second-order optimization with a series of examples, showing that even a pulse already optimized using other methods can be visibly improved. To be useful in CPMG experiments, a universal refocusing pulse should be independent of the delay time and insensitive of the relaxation time and RF inhomogeneity. We design such a pulse and show that, using it, we can obtain reliable R2 measurements for offsets within ±γB1. Finally, we compare our optimal refocusing pulse with other published refocusing pulses by doing CPMG experiments.

[Optimization of one-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology].

PubMed

Zhang, Yan-jun; Liu, Li-li; Hu, Jun-hua; Wu, Yun; Chao, En-xiang; Xiao, Wei

2015-11-01

First with the qualified rate of granules as the evaluation index, significant influencing factors were firstly screened by Plackett-Burman design. Then, with the qualified rate and moisture content as the evaluation indexes, significant factors that affect one-step pelletization technology were further optimized by Box-Behnken design; experimental data were imitated by multiple regression and second-order polynomial equation; and response surface method was used for predictive analysis of optimal technology. The best conditions were as follows: inlet air temperature of 85 degrees C, sample introduction speed of 33 r x min(-1), density of concrete 1. 10. One-step pelletization technology of Biqiu granules by Plackett-Burman design and Box-Behnken response surface methodology was stable and feasible with good predictability, which provided reliable basis for the industrialized production of Biqiu granules.

Reducing maintenance costs in agreement with CNC machine tools reliability

NASA Astrophysics Data System (ADS)

Ungureanu, A. L.; Stan, G.; Butunoi, P. A.

2016-08-01

Aligning maintenance strategy with reliability is a challenge due to the need to find an optimal balance between them. Because the various methods described in the relevant literature involve laborious calculations or use of software that can be costly, this paper proposes a method that is easier to implement on CNC machine tools. The new method, called the Consequence of Failure Analysis (CFA) is based on technical and economic optimization, aimed at obtaining a level of required performance with minimum investment and maintenance costs.

Optimization of an asymmetric thin-walled tube in rotary draw bending process

NASA Astrophysics Data System (ADS)

Xue, Xin; Liao, Juan; Vincze, Gabriela; Gracio, Jose J.

2013-12-01

The rotary draw bending is one of the advanced thin-walled tube forming processes with high efficiency, low consumption and good flexibility in several industries such as automotive, aerospace and shipping. However it may cause undesirable deformations such as over-thinning and ovalization, which bring the weakening of the strength and difficulties in the assembly process respectively. Accurate modeling and effective optimization design to eliminate or reduce undesirable deformations in tube bending process have been a challenging topic. In this paper, in order to study the deformation behaviors of an asymmetric thin-walled tube in rotary draw bending process, a 3D elastic-plastic finite element model has been built under the ABAQUS environment, and the reliability of the model is validated by comparison with experiment. Then, the deformation mechanism of thin-walled tube in bending process was briefly analysis and the effects of wall thickness ratio, section height width ratio and mandrel extension on wall thinning and ovalization in bending process were investigated by using Response Surface Methodology. Finally, multi-objective optimization method was used to obtain an optimum solution of design variables based on simulation results.

Integrated performance and reliability specification for digital avionics systems

NASA Technical Reports Server (NTRS)

Brehm, Eric W.; Goettge, Robert T.

1995-01-01

This paper describes an automated tool for performance and reliability assessment of digital avionics systems, called the Automated Design Tool Set (ADTS). ADTS is based on an integrated approach to design assessment that unifies traditional performance and reliability views of system designs, and that addresses interdependencies between performance and reliability behavior via exchange of parameters and result between mathematical models of each type. A multi-layer tool set architecture has been developed for ADTS that separates the concerns of system specification, model generation, and model solution. Performance and reliability models are generated automatically as a function of candidate system designs, and model results are expressed within the system specification. The layered approach helps deal with the inherent complexity of the design assessment process, and preserves long-term flexibility to accommodate a wide range of models and solution techniques within the tool set structure. ADTS research and development to date has focused on development of a language for specification of system designs as a basis for performance and reliability evaluation. A model generation and solution framework has also been developed for ADTS, that will ultimately encompass an integrated set of analytic and simulated based techniques for performance, reliability, and combined design assessment.

Efficient computation of photonic crystal waveguide modes with dispersive material.

PubMed

Schmidt, Kersten; Kappeler, Roman

2010-03-29

The optimization of PhC waveguides is a key issue for successfully designing PhC devices. Since this design task is computationally expensive, efficient methods are demanded. The available codes for computing photonic bands are also applied to PhC waveguides. They are reliable but not very efficient, which is even more pronounced for dispersive material. We present a method based on higher order finite elements with curved cells, which allows to solve for the band structure taking directly into account the dispersiveness of the materials. This is accomplished by reformulating the wave equations as a linear eigenproblem in the complex wave-vectors k. For this method, we demonstrate the high efficiency for the computation of guided PhC waveguide modes by a convergence analysis.

Optimized Generator Designs for the DTU 10-MW Offshore Wind Turbine using GeneratorSE

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

Sethuraman, Latha; Maness, Michael; Dykes, Katherine

Compared to land-based applications, offshore wind imposes challenges for the development of next generation wind turbine generator technology. Direct-drive generators are believed to offer high availability, efficiency, and reduced operation and maintenance requirements; however, previous research suggests difficulties in scaling to several megawatts or more in size. The resulting designs are excessively large and/or massive, which are major impediments to transportation logistics, especially for offshore applications. At the same time, geared wind turbines continue to sustain offshore market growth through relatively cheaper and lightweight generators. However, reliability issues associated with mechanical components in a geared system create significant operation andmore » maintenance costs, and these costs make up a large portion of overall system costs offshore. Thus, direct-drive turbines are likely to outnumber their gear-driven counterparts for this market, and there is a need to review the costs or opportunities of building machines with different types of generators and examining their competitiveness at the sizes necessary for the next generation of offshore wind turbines. In this paper, we use GeneratorSE, the National Renewable Energy Laboratory's newly developed systems engineering generator sizing tool to estimate mass, efficiency, and the costs of different generator technologies satisfying the electromagnetic, structural, and basic thermal design requirements for application in a very large-scale offshore wind turbine such as the Technical University of Denmark's (DTU) 10-MW reference wind turbine. For the DTU reference wind turbine, we use the previously mentioned criteria to optimize a direct-drive, radial flux, permanent-magnet synchronous generator; a direct-drive electrically excited synchronous generator; a medium-speed permanent-magnet generator; and a high-speed, doubly-fed induction generator. Preliminary analysis of leveled costs of energy indicate that for large turbines, the cost of permanent magnets and reliability issues associated with brushes in electrically excited machines are the biggest deterrents for building direct-drive systems. The advantage of medium-speed permanent-magnet machines over doubly-fed induction generators is evident, yet, variability in magnet prices and solutions to address reliability issues associated with gearing and brushes can change this outlook. This suggests the need to potentially pursue fundamentally new innovations in generator designs that help avoid high capital costs but still have significant reliability related to performance.« less

Optimized Generator Designs for the DTU 10-MW Offshore Wind Turbine using GeneratorSE: Preprint

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

Sethuraman, Latha; Maness, Michael; Dykes, Katherine

Compared to land-based applications, offshore wind imposes challenges for the development of next generation wind turbine generator technology. Direct-drive generators are believed to offer high availability, efficiency, and reduced operation and maintenance requirements; however, previous research suggests difficulties in scaling to several megawatts or more in size. The resulting designs are excessively large and/or massive, which are major impediments to transportation logistics, especially for offshore applications. At the same time, geared wind turbines continue to sustain offshore market growth through relatively cheaper and lightweight generators. However, reliability issues associated with mechanical components in a geared system create significant operation andmore » maintenance costs, and these costs make up a large portion of overall system costs offshore. Thus, direct-drive turbines are likely to outnumber their gear-driven counterparts for this market, and there is a need to review the costs or opportunities of building machines with different types of generators and examining their competitiveness at the sizes necessary for the next generation of offshore wind turbines. In this paper, we use GeneratorSE, the National Renewable Energy Laboratory's newly developed systems engineering generator sizing tool to estimate mass, efficiency, and the costs of different generator technologies satisfying the electromagnetic, structural, and basic thermal design requirements for application in a very large-scale offshore wind turbine such as the Technical University of Denmark's (DTU) 10-MW reference wind turbine. For the DTU reference wind turbine, we use the previously mentioned criteria to optimize a direct-drive, radial flux, permanent-magnet synchronous generator; a direct-drive electrically excited synchronous generator; a medium-speed permanent-magnet generator; and a high-speed, doubly-fed induction generator. Preliminary analysis of leveled costs of energy indicate that for large turbines, the cost of permanent magnets and reliability issues associated with brushes in electrically excited machines are the biggest deterrents for building direct-drive systems. The advantage of medium-speed permanent-magnet machines over doubly-fed induction generators is evident, yet, variability in magnet prices and solutions to address reliability issues associated with gearing and brushes can change this outlook. This suggests the need to potentially pursue fundamentally new innovations in generator designs that help avoid high capital costs but still have significant reliability related to performance.« less

Modeling of plasma in a hybrid electric propulsion for small satellites

NASA Astrophysics Data System (ADS)

Jugroot, Manish; Christou, Alex

2016-09-01

As space flight becomes more available and reliable, space-based technology is allowing for smaller and more cost-effective satellites to be produced. Working in large swarms, many small satellites can provide additional capabilities while reducing risk. These satellites require efficient, long term propulsion for manoeuvres, orbit maintenance and de-orbiting. The high exhaust velocity and propellant efficiency of electric propulsion makes it ideally suited for low thrust missions. The two dominant types of electric propulsion, namely ion thrusters and Hall thrusters, excel in different mission types. In this work, a novel electric hybrid propulsion design is modelled to enhance understanding of key phenomena and evaluate performance. Specifically, the modelled hybrid thruster seeks to overcome issues with existing Ion and Hall thruster designs. Scaling issues and optimization of the design will be discussed and will investigate a conceptual design of a hybrid spacecraft plasma engine.

Design and experimental validation for direct-drive fault-tolerant permanent-magnet vernier machines.

PubMed

Liu, Guohai; Yang, Junqin; Chen, Ming; Chen, Qian

2014-01-01

A fault-tolerant permanent-magnet vernier (FT-PMV) machine is designed for direct-drive applications, incorporating the merits of high torque density and high reliability. Based on the so-called magnetic gearing effect, PMV machines have the ability of high torque density by introducing the flux-modulation poles (FMPs). This paper investigates the fault-tolerant characteristic of PMV machines and provides a design method, which is able to not only meet the fault-tolerant requirements but also keep the ability of high torque density. The operation principle of the proposed machine has been analyzed. The design process and optimization are presented specifically, such as the combination of slots and poles, the winding distribution, and the dimensions of PMs and teeth. By using the time-stepping finite element method (TS-FEM), the machine performances are evaluated. Finally, the FT-PMV machine is manufactured, and the experimental results are presented to validate the theoretical analysis.

Information fusion based techniques for HEVC

NASA Astrophysics Data System (ADS)

Fernández, D. G.; Del Barrio, A. A.; Botella, Guillermo; Meyer-Baese, Uwe; Meyer-Baese, Anke; Grecos, Christos

2017-05-01

Aiming at the conflict circumstances of multi-parameter H.265/HEVC encoder system, the present paper introduces the analysis of many optimizations' set in order to improve the trade-off between quality, performance and power consumption for different reliable and accurate applications. This method is based on the Pareto optimization and has been tested with different resolutions on real-time encoders.

System of systems design: Evaluating aircraft in a fleet context using reliability and non-deterministic approaches

NASA Astrophysics Data System (ADS)

Frommer, Joshua B.

This work develops and implements a solution framework that allows for an integrated solution to a resource allocation system-of-systems problem associated with designing vehicles for integration into an existing fleet to extend that fleet's capability while improving efficiency. Typically, aircraft design focuses on using a specific design mission while a fleet perspective would provide a broader capability. Aspects of design for both the vehicles and missions may be, for simplicity, deterministic in nature or, in a model that reflects actual conditions, uncertain. Toward this end, the set of tasks or goals for the to-be-planned system-of-systems will be modeled more accurately with non-deterministic values, and the designed platforms will be evaluated using reliability analysis. The reliability, defined as the probability of a platform or set of platforms to complete possible missions, will contribute to the fitness of the overall system. The framework includes building surrogate models for metrics such as capability and cost, and includes the ideas of reliability in the overall system-level design space. The concurrent design and allocation system-of-systems problem is a multi-objective mixed integer nonlinear programming (MINLP) problem. This study considered two system-of-systems problems that seek to simultaneously design new aircraft and allocate these aircraft into a fleet to provide a desired capability. The Coast Guard's Integrated Deepwater System program inspired the first problem, which consists of a suite of search-and-find missions for aircraft based on descriptions from the National Search and Rescue Manual. The second represents suppression of enemy air defense operations similar to those carried out by the U.S. Air Force, proposed as part of the Department of Defense Network Centric Warfare structure, and depicted in MILSTD-3013. The two problems seem similar, with long surveillance segments, but because of the complex nature of aircraft design, the analysis of the vehicle for high-speed attack combined with a long loiter period is considerably different from that for quick cruise to an area combined with a low speed search. However, the framework developed to solve this class of system-of-systems problem handles both scenarios and leads to a solution type for this kind of problem. On the vehicle-level of the problem, different technology can have an impact on the fleet-level. One such technology is Morphing, the ability to change shape, which is an ideal candidate technology for missions with dissimilar segments, such as the aforementioned two. A framework, using surrogate models based on optimally-sized aircraft, and using probabilistic parameters to define a concept of operations, is investigated; this has provided insight into the setup of the optimization problem, the use of the reliability metric, and the measurement of fleet level impacts of morphing aircraft. The research consisted of four phases. The two initial phases built and defined the framework to solve system-of-systems problem; these investigations used the search-and-find scenario as the example application. The first phase included the design of fixed-geometry and morphing aircraft for a range of missions and evaluated the aircraft capability using non-deterministic mission parameters. The second phase introduced the idea of multiple aircraft in a fleet, but only considered a fleet consisting of one aircraft type. The third phase incorporated the simultaneous design of a new vehicle and allocation into a fleet for the search-and-find scenario; in this phase, multiple types of aircraft are considered. The fourth phase repeated the simultaneous new aircraft design and fleet allocation for the SEAD scenario to show that the approach is not specific to the search-and-find scenario. The framework presented in this work appears to be a viable approach for concurrently designing and allocating constituents in a system, specifically aircraft in a fleet. The research also shows that new technology impact can be assessed at the fleet level using conceptual design principles.

Verification techniques for x-ray and mammography applications

NASA Astrophysics Data System (ADS)

Kotsopoulos, Stavros A.; Lymberopoulos, Dimitris C.

1993-07-01

The integration of Medical Information Environment demands the study and development of high speed data communication systems with special designed 'endsystems' (MWS, etc.) for flexible and reliable data transmission/reception, handling and manipulation. An important parameter which affects the overall system's performance is the 'quality factor' of the communicated medical data produced by a wide range of modern modalities. The present paper describes a set of tests, done in a medical communication network based on a teleworking platform, in order to optimize the sensitivity parameters of the modalities by remote fine re-adjustments guided by experts.

Ejectors of power plants turbine units efficiency and reliability increasing

NASA Astrophysics Data System (ADS)

Aronson, K. E.; Ryabchikov, A. Yu.; Kuptsov, V. K.; Murmanskii, I. B.; Brodov, Yu. M.; Zhelonkin, N. V.; Khaet, S. I.

2017-11-01

The functioning of steam turbines condensation systems influence on the efficiency and reliability of a power plant a lot. At the same time, the condensation system operating is provided by basic ejectors, which maintain the vacuum level in the condenser. Development of methods of efficiency and reliability increasing for ejector functioning is an actual problem of up-to-date power engineering. In the paper there is presented statistical analysis of ejector breakdowns, revealed during repairing processes, the influence of such damages on the steam turbine operating reliability. It is determined, that 3% of steam turbine equipment breakdowns are the ejector breakdowns. At the same time, about 7% of turbine breakdowns are caused by different ejector malfunctions. Developed and approved design solutions, which can increase the ejector functioning indexes, are presented. Intercoolers are designed in separated cases, so the air-steam mixture can’t move from the high-pressure zones to the low-pressure zones and the maintainability of the apparatuses is increased. By U-type tubes application, the thermal expansion effect of intercooler tubes is compensated and the heat-transfer area is increased. By the applied nozzle fixing construction, it is possible to change the distance between a nozzle and a mixing chamber (nozzle exit position) for operating performance optimization. In operating conditions there are provided experimental researches of more than 30 serial ejectors and also high-efficient 3-staged ejector EPO-3-80, designed by authors. The measurement scheme of the designed ejector includes 21 indicator. The results of experimental tests with different nozzle exit positions of the ejector EPO-3-80 stream devices are presented. The pressure of primary stream (water steam) is optimized. Experimental data are well-approved by the calculation results.

Integrated optical design for highly dynamic laser beam shaping with membrane deformable mirrors

NASA Astrophysics Data System (ADS)

Pütsch, Oliver; Stollenwerk, Jochen; Loosen, Peter

2017-02-01

The utilization of membrane deformable mirrors has raised its importance in laser materials processing since they enable the generation of highly spatial and temporal dynamic intensity distributions for a wide field of applications. To take full advantage of these devices for beam shaping, the huge amount of degrees of freedom has to be considered and optimized already within the early stage of the optical design. Since the functionality of commercial available ray-tracing software has been mainly specialized on geometric dependencies and their optimization within constraints, the complex system characteristics of deformable mirrors cannot be sufficiently taken into account yet. The main reasons are the electromechanical interdependencies of electrostatic membrane deformable mirrors, namely saturation and mechanical clamping, that result in non-linear deformation. This motivates the development of an integrative design methodology. The functionality of the ray-tracing program ZEMAX is extended with a model of an electrostatic membrane mirror. This model is based on experimentally determined influence functions. Furthermore, software routines are derived and integrated that allow for the compilation of optimization criteria for the most relevant analytically describable beam shaping problems. In this way, internal optimization routines can be applied for computing the appropriate membrane deflection of the deformable mirror as well as for the parametrization of static optical components. The experimental verification of simulated intensity distributions demonstrates that the beam shaping properties can be predicted with a high degree of reliability and precision.

Optimizing the static-dynamic performance of the body-in-white using a modified non-dominated sorting genetic algorithm coupled with grey relational analysis

NASA Astrophysics Data System (ADS)

Wang, Dengfeng; Cai, Kefang

2018-04-01

This article presents a hybrid method combining a modified non-dominated sorting genetic algorithm (MNSGA-II) with grey relational analysis (GRA) to improve the static-dynamic performance of a body-in-white (BIW). First, an implicit parametric model of the BIW was built using SFE-CONCEPT software, and then the validity of the implicit parametric model was verified by physical testing. Eight shape design variables were defined for BIW beam structures based on the implicit parametric technology. Subsequently, MNSGA-II was used to determine the optimal combination of the design parameters that can improve the bending stiffness, torsion stiffness and low-order natural frequencies of the BIW without considerable increase in the mass. A set of non-dominated solutions was then obtained in the multi-objective optimization design. Finally, the grey entropy theory and GRA were applied to rank all non-dominated solutions from best to worst to determine the best trade-off solution. The comparison between the GRA and the technique for order of preference by similarity to ideal solution (TOPSIS) illustrated the reliability and rationality of GRA. Moreover, the effectiveness of the hybrid method was verified by the optimal results such that the bending stiffness, torsion stiffness, first order bending and first order torsion natural frequency were improved by 5.46%, 9.30%, 7.32% and 5.73%, respectively, with the mass of the BIW increasing by 1.30%.

Research on the optimal structure configuration of dither RLG used in skewed redundant INS

NASA Astrophysics Data System (ADS)

Gao, Chunfeng; Wang, Qi; Wei, Guo; Long, Xingwu

2016-05-01

The actual combat effectiveness of weapon equipment is restricted by the performance of Inertial Navigation System (INS), especially in high reliability required situations such as fighter, satellite and submarine. Through the use of skewed sensor geometries, redundant technique has been applied to reduce the cost and improve the reliability of the INS. In this paper, the structure configuration and the inertial sensor characteristics of Skewed Redundant Strapdown Inertial Navigation System (SRSINS) using dithered Ring Laser Gyroscope (RLG) are analyzed. For the dither coupling effects of the dither gyro, the system measurement errors can be amplified either the individual gyro dither frequency is near one another or the structure of the SRSINS is unreasonable. Based on the characteristics of RLG, the research on coupled vibration of dithered RLG in SRSINS is carried out. On the principle of optimal navigation performance, optimal reliability and optimal cost-effectiveness, the comprehensive evaluation scheme of the inertial sensor configuration of SRINS is given.

Health Monitoring and Evaluation of Long-Span Bridges Based on Sensing and Data Analysis: A Survey

PubMed Central

Zhou, Jianting; Li, Xiaogang; Xia, Runchuan; Yang, Jun; Zhang, Hong

2017-01-01

Aimed at the health monitoring and evaluation of bridges based on sensing technology, the monitoring contents of different structural types of long-span bridges were defined. Then, the definition, classification, selection principle, and installation requirements of the sensors were summarized. The concept was proposed that new adaptable long-life sensors could be developed by new theories and new effects. The principle and methods to select controlled sections and optimize the layout design of measuring points were illustrated. The functional requirements were elaborated on about the acquisition, transmission, processing, and management of sensing information. Some advanced concepts about the method of bridge safety evaluation were demonstrated and technology bottlenecks in the current safety evaluation were also put forward. Ultimately, combined with engineering practices, an application was carried out. The results showed that new, intelligent, and reliable sensor technology would be one of the main future development directions in the long-span bridge health monitoring and evaluation field. Also, it was imperative to optimize the design of the health monitoring system and realize its standardization. Moreover, it is a heavy responsibility to explore new thoughts and new concepts regarding practical bridge safety and evaluation technology. PMID:28300785

Design of an integrated airframe/propulsion control system architecture

NASA Technical Reports Server (NTRS)

Cohen, Gerald C.; Lee, C. William; Strickland, Michael J.

1990-01-01

The design of an integrated airframe/propulsion control system architecture is described. The design is based on a prevalidation methodology that used both reliability and performance tools. An account is given of the motivation for the final design and problems associated with both reliability and performance modeling. The appendices contain a listing of the code for both the reliability and performance model used in the design.

Design and experimentation of an empirical multistructure framework for accurate, sharp and reliable hydrological ensembles

NASA Astrophysics Data System (ADS)

Seiller, G.; Anctil, F.; Roy, R.

2017-09-01

This paper outlines the design and experimentation of an Empirical Multistructure Framework (EMF) for lumped conceptual hydrological modeling. This concept is inspired from modular frameworks, empirical model development, and multimodel applications, and encompasses the overproduce and select paradigm. The EMF concept aims to reduce subjectivity in conceptual hydrological modeling practice and includes model selection in the optimisation steps, reducing initial assumptions on the prior perception of the dominant rainfall-runoff transformation processes. EMF generates thousands of new modeling options from, for now, twelve parent models that share their functional components and parameters. Optimisation resorts to ensemble calibration, ranking and selection of individual child time series based on optimal bias and reliability trade-offs, as well as accuracy and sharpness improvement of the ensemble. Results on 37 snow-dominated Canadian catchments and 20 climatically-diversified American catchments reveal the excellent potential of the EMF in generating new individual model alternatives, with high respective performance values, that may be pooled efficiently into ensembles of seven to sixty constitutive members, with low bias and high accuracy, sharpness, and reliability. A group of 1446 new models is highlighted to offer good potential on other catchments or applications, based on their individual and collective interests. An analysis of the preferred functional components reveals the importance of the production and total flow elements. Overall, results from this research confirm the added value of ensemble and flexible approaches for hydrological applications, especially in uncertain contexts, and open up new modeling possibilities.

A Probabilistic Approach to Predict Thermal Fatigue Life for Ball Grid Array Solder Joints

NASA Astrophysics Data System (ADS)

Wei, Helin; Wang, Kuisheng

2011-11-01

Numerous studies of the reliability of solder joints have been performed. Most life prediction models are limited to a deterministic approach. However, manufacturing induces uncertainty in the geometry parameters of solder joints, and the environmental temperature varies widely due to end-user diversity, creating uncertainties in the reliability of solder joints. In this study, a methodology for accounting for variation in the lifetime prediction for lead-free solder joints of ball grid array packages (PBGA) is demonstrated. The key aspects of the solder joint parameters and the cyclic temperature range related to reliability are involved. Probabilistic solutions of the inelastic strain range and thermal fatigue life based on the Engelmaier model are developed to determine the probability of solder joint failure. The results indicate that the standard deviation increases significantly when more random variations are involved. Using the probabilistic method, the influence of each variable on the thermal fatigue life is quantified. This information can be used to optimize product design and process validation acceptance criteria. The probabilistic approach creates the opportunity to identify the root causes of failed samples from product fatigue tests and field returns. The method can be applied to better understand how variation affects parameters of interest in an electronic package design with area array interconnections.

Teaching Quality in Math Class: The Development of a Scale and the Analysis of Its Relationship with Engagement and Achievement

PubMed Central

Leon, Jaime; Medina-Garrido, Elena; Núñez, Juan L.

2017-01-01

Math achievement and engagement declines in secondary education; therefore, educators are faced with the challenge of engaging students to avoid school failure. Within self-determination theory, we address the need to assess comprehensively student perceptions of teaching quality that predict engagement and achievement. In study one we tested, in a sample of 548 high school students, a preliminary version of a scale to assess nine factors: teaching for relevance, acknowledge negative feelings, participation encouragement, controlling language, optimal challenge, focus on the process, class structure, positive feedback, and caring. In the second study, we analyzed the scale’s reliability and validity in a sample of 1555 high school students. The scale showed evidence of reliability, and with regard to criterion validity, at the classroom level, teaching quality was a predictor of behavioral engagement, and higher grades were observed in classes where students, as a whole, displayed more behavioral engagement. At the within level, behavioral engagement was associated with achievement. We not only provide a reliable and valid method to assess teaching quality, but also a method to design interventions, these could be designed based on the scale items to encourage students to persist and display more engagement on school duties, which in turn bolsters student achievement. PMID:28701964

Teaching Quality in Math Class: The Development of a Scale and the Analysis of Its Relationship with Engagement and Achievement.

PubMed

Leon, Jaime; Medina-Garrido, Elena; Núñez, Juan L

2017-01-01

Math achievement and engagement declines in secondary education; therefore, educators are faced with the challenge of engaging students to avoid school failure. Within self-determination theory, we address the need to assess comprehensively student perceptions of teaching quality that predict engagement and achievement. In study one we tested, in a sample of 548 high school students, a preliminary version of a scale to assess nine factors: teaching for relevance, acknowledge negative feelings, participation encouragement, controlling language, optimal challenge, focus on the process, class structure, positive feedback, and caring. In the second study, we analyzed the scale's reliability and validity in a sample of 1555 high school students. The scale showed evidence of reliability, and with regard to criterion validity, at the classroom level, teaching quality was a predictor of behavioral engagement, and higher grades were observed in classes where students, as a whole, displayed more behavioral engagement. At the within level, behavioral engagement was associated with achievement. We not only provide a reliable and valid method to assess teaching quality, but also a method to design interventions, these could be designed based on the scale items to encourage students to persist and display more engagement on school duties, which in turn bolsters student achievement.

Energy management and cooperation in microgrids

NASA Astrophysics Data System (ADS)

Rahbar, Katayoun

Microgrids are key components of future smart power grids, which integrate distributed renewable energy generators to efficiently serve the load demand locally. However, random and intermittent characteristics of renewable energy generations may hinder the reliable operation of microgrids. This thesis is thus devoted to investigating new strategies for microgrids to optimally manage their energy consumption, energy storage system (ESS) and cooperation in real time to achieve the reliable and cost-effective operation. This thesis starts with a single microgrid system. The optimal energy scheduling and ESS management policy is derived to minimize the energy cost of the microgrid resulting from drawing conventional energy from the main grid under both the off-line and online setups, where the renewable energy generation/load demand are assumed to be non-causally known and causally known at the microgrid, respectively. The proposed online algorithm is designed based on the optimal off-line solution and works under arbitrary (even unknown) realizations of future renewable energy generation/load demand. Therefore, it is more practically applicable as compared to solutions based on conventional techniques such as dynamic programming and stochastic programming that require the prior knowledge of renewable energy generation and load demand realizations/distributions. Next, for a group of microgrids that cooperate in energy management, we study efficient methods for sharing energy among them for both fully and partially cooperative scenarios, where microgrids are of common interests and self-interested, respectively. For the fully cooperative energy management, the off-line optimization problem is first formulated and optimally solved, where a distributed algorithm is proposed to minimize the total (sum) energy cost of microgrids. Inspired by the results obtained from the off-line optimization, efficient online algorithms are proposed for the real-time energy management, which are of low complexity and work given arbitrary realizations of renewable energy generation/load demand. On the other hand, for self-interested microgrids, the partially cooperative energy management is formulated and a distributed algorithm is proposed to optimize the energy cooperation such that energy costs of individual microgrids reduce simultaneously over the case without energy cooperation while limited information is shared among the microgrids and the central controller.

Error Propagation Analysis in the SAE Architecture Analysis and Design Language (AADL) and the EDICT Tool Framework

NASA Technical Reports Server (NTRS)

LaValley, Brian W.; Little, Phillip D.; Walter, Chris J.

2011-01-01

This report documents the capabilities of the EDICT tools for error modeling and error propagation analysis when operating with models defined in the Architecture Analysis & Design Language (AADL). We discuss our experience using the EDICT error analysis capabilities on a model of the Scalable Processor-Independent Design for Enhanced Reliability (SPIDER) architecture that uses the Reliable Optical Bus (ROBUS). Based on these experiences we draw some initial conclusions about model based design techniques for error modeling and analysis of highly reliable computing architectures.

Analysis of the Seismic Performance of Isolated Buildings according to Life-Cycle Cost

PubMed Central

Dang, Yu; Han, Jian-ping; Li, Yong-tao

2015-01-01

This paper proposes an indicator of seismic performance based on life-cycle cost of a building. It is expressed as a ratio of lifetime damage loss to life-cycle cost and determines the seismic performance of isolated buildings. Major factors are considered, including uncertainty in hazard demand and structural capacity, initial costs, and expected loss during earthquakes. Thus, a high indicator value indicates poor building seismic performance. Moreover, random vibration analysis is conducted to measure structural reliability and evaluate the expected loss and life-cycle cost of isolated buildings. The expected loss of an actual, seven-story isolated hospital building is only 37% of that of a fixed-base building. Furthermore, the indicator of the structural seismic performance of the isolated building is much lower in value than that of the structural seismic performance of the fixed-base building. Therefore, isolated buildings are safer and less risky than fixed-base buildings. The indicator based on life-cycle cost assists owners and engineers in making investment decisions in consideration of structural design, construction, and expected loss. It also helps optimize the balance between building reliability and building investment. PMID:25653677

Analysis of the seismic performance of isolated buildings according to life-cycle cost.

PubMed

Dang, Yu; Han, Jian-Ping; Li, Yong-Tao

2015-01-01

This paper proposes an indicator of seismic performance based on life-cycle cost of a building. It is expressed as a ratio of lifetime damage loss to life-cycle cost and determines the seismic performance of isolated buildings. Major factors are considered, including uncertainty in hazard demand and structural capacity, initial costs, and expected loss during earthquakes. Thus, a high indicator value indicates poor building seismic performance. Moreover, random vibration analysis is conducted to measure structural reliability and evaluate the expected loss and life-cycle cost of isolated buildings. The expected loss of an actual, seven-story isolated hospital building is only 37% of that of a fixed-base building. Furthermore, the indicator of the structural seismic performance of the isolated building is much lower in value than that of the structural seismic performance of the fixed-base building. Therefore, isolated buildings are safer and less risky than fixed-base buildings. The indicator based on life-cycle cost assists owners and engineers in making investment decisions in consideration of structural design, construction, and expected loss. It also helps optimize the balance between building reliability and building investment.

An assessment of alternative fuel cell designs for residential and commercial cogeneration

NASA Technical Reports Server (NTRS)

Wakefield, R. A.

1980-01-01

A comparative assessment of three fuel cell systems for application in different buildings and geographic locations is presented. The study was performed at the NASA Lewis Center and comprised the fuel cell design, performance in different conditions, and the economic parameters. Applications in multifamily housing, stores and hospitals were considered, with a load of 10kW-1 MW. Designs were traced through system sizing, simulation/evaluation, and reliability analysis, and a computer simulation based on a fourth-order representation of a generalized system was performed. The cells were all phosphoric acid type cells, and were found to be incompatible with gas/electric systems and more favorable economically than the gas/electric systems in hospital uses. The methodology used provided an optimized energy-use pattern and minimized back-up system turn-on.

Integrated Logistics Support approach: concept for the new big projects: E-ELT, SKA, CTA

NASA Astrophysics Data System (ADS)

Marchiori, G.; Rampini, F.; Formentin, F.

2014-08-01

The Integrated Logistic Support is a process supporting strategies and optimizing activities for a correct project management and system engineering development. From the design & engineering of complex technical systems, to the erection on site, acceptance and after-sales service, EIE GROUP covers all aspects of the Integrated Logistics Support (ILS) process that includes: costing process centered around the life cycle cost and Level of Repair Analyses; engineering process which influences the design via means of reliability, modularization, etc.; technical publishing process based on international specifications; ordering administration process for supply support. Through the ILS, EIE GROUP plans and directs the identification and development of logistics support and system requirements for its products, with the goal of creating systems that last longer and require less support, thereby reducing costs and increasing return on investments. ILS therefore, addresses these aspects of supportability not only during acquisition, but also throughout the operational life cycle of the system. The impact of the ILS is often measured in terms of metrics such as reliability, availability, maintainability and testability (RAMT), and System Safety (RAMS). Example of the criteria and approach adopted by EIE GROUP during the design, manufacturing and test of the ALMA European Antennas and during the design phase of the E-ELT telescope and Dome are presented.

Multi-time scale Climate Informed Stochastic Hybrid Simulation-Optimization Model (McISH model) for Multi-Purpose Reservoir System

NASA Astrophysics Data System (ADS)

Lu, M.; Lall, U.

2013-12-01

In order to mitigate the impacts of climate change, proactive management strategies to operate reservoirs and dams are needed. A multi-time scale climate informed stochastic model is developed to optimize the operations for a multi-purpose single reservoir by simulating decadal, interannual, seasonal and sub-seasonal variability. We apply the model to a setting motivated by the largest multi-purpose dam in N. India, the Bhakhra reservoir on the Sutlej River, a tributary of the Indus. This leads to a focus on timing and amplitude of the flows for the monsoon and snowmelt periods. The flow simulations are constrained by multiple sources of historical data and GCM future projections, that are being developed through a NSF funded project titled 'Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoon Asia'. The model presented is a multilevel, nonlinear programming model that aims to optimize the reservoir operating policy on a decadal horizon and the operation strategy on an updated annual basis. The model is hierarchical, in terms of having a structure that two optimization models designated for different time scales are nested as a matryoshka doll. The two optimization models have similar mathematical formulations with some modifications to meet the constraints within that time frame. The first level of the model is designated to provide optimization solution for policy makers to determine contracted annual releases to different uses with a prescribed reliability; the second level is a within-the-period (e.g., year) operation optimization scheme that allocates the contracted annual releases on a subperiod (e.g. monthly) basis, with additional benefit for extra release and penalty for failure. The model maximizes the net benefit of irrigation, hydropower generation and flood control in each of the periods. The model design thus facilitates the consistent application of weather and climate forecasts to improve operations of reservoir systems. The decadal flow simulations are re-initialized every year with updated climate projections to improve the reliability of the operation rules for the next year, within which the seasonal operation strategies are nested. The multi-level structure can be repeated for monthly operation with weekly subperiods to take advantage of evolving weather forecasts and seasonal climate forecasts. As a result of the hierarchical structure, sub-seasonal even weather time scale updates and adjustment can be achieved. Given an ensemble of these scenarios, the McISH reservoir simulation-optimization model is able to derive the desired reservoir storage levels, including minimum and maximum, as a function of calendar date, and the associated release patterns. The multi-time scale approach allows adaptive management of water supplies acknowledging the changing risks, meeting both the objectives over the decade in expected value and controlling the near term and planning period risk through probabilistic reliability constraints. For the applications presented, the target season is the monsoon season from June to September. The model also includes a monthly flood volume forecast model, based on a Copula density fit to the monthly flow and the flood volume flow. This is used to guide dynamic allocation of the flood control volume given the forecasts.

How does network design constrain optimal operation of intermittent water supply?

NASA Astrophysics Data System (ADS)

Lieb, Anna; Wilkening, Jon; Rycroft, Chris

2015-11-01

Urban water distribution systems do not always supply water continuously or reliably. As pipes fill and empty, pressure transients may contribute to degraded infrastructure and poor water quality. To help understand and manage this undesirable side effect of intermittent water supply--a phenomenon affecting hundreds of millions of people in cities around the world--we study the relative contributions of fixed versus dynamic properties of the network. Using a dynamical model of unsteady transition pipe flow, we study how different elements of network design, such as network geometry, pipe material, and pipe slope, contribute to undesirable pressure transients. Using an optimization framework, we then investigate to what extent network operation decisions such as supply timing and inflow rate may mitigate these effects. We characterize some aspects of network design that make them more or less amenable to operational optimization.

System Statement of Tasks of Calculating and Providing the Reliability of Heating Cogeneration Plants in Power Systems

NASA Astrophysics Data System (ADS)

Biryuk, V. V.; Tsapkova, A. B.; Larin, E. A.; Livshiz, M. Y.; Sheludko, L. P.

2018-01-01

A set of mathematical models for calculating the reliability indexes of structurally complex multifunctional combined installations in heat and power supply systems was developed. Reliability of energy supply is considered as required condition for the creation and operation of heat and power supply systems. The optimal value of the power supply system coefficient F is based on an economic assessment of the consumers’ loss caused by the under-supply of electric power and additional system expences for the creation and operation of an emergency capacity reserve. Rationing of RI of the industrial heat supply is based on the use of concept of technological margin of safety of technological processes. The definition of rationed RI values of heat supply of communal consumers is based on the air temperature level iside the heated premises. The complex allows solving a number of practical tasks for providing reliability of heat supply for consumers. A probabilistic model is developed for calculating the reliability indexes of combined multipurpose heat and power plants in heat-and-power supply systems. The complex of models and calculation programs can be used to solve a wide range of specific tasks of optimization of schemes and parameters of combined heat and power plants and systems, as well as determining the efficiency of various redundance methods to ensure specified reliability of power supply.

RICIN-inhibitor design. Final report, 15 April 1993-14 April 1996

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

Schramm, V.L.

1996-05-01

The purpose of this proposal was to provide information which will permit the design of transition state inhibitors for ricin A-chain. The original goals were to solve the transition state structure based on kinetic isotope effects. Substrates were synthesized and the conditions for assays optimized to provide catalytic rates at least 1000 fold greater than those published prior to this work. Reliable assay methods have been established to permit routine assays for ricin A-chain. Substrate analogues for N-ribohydrolase reactions have been designed to establish whether the reaction involves leaving-group activation or oxycarbonium ion formation. Based on these results, leaving groupmore » activation is a major contributor and oxycarbonium-ion formation is a secondary contribution in the mechanism of catalysis by ricin A-chain. Using this information, the first submicromolar inhibitor of ricin A-chain has been synthesized, tested and kinetically characterized. The development of powerful inhibitors will be a direct extrapolation of these results.« less

A unified, multifidelity quasi-newton optimization method with application to aero-structural designa

NASA Astrophysics Data System (ADS)

Bryson, Dean Edward

A model's level of fidelity may be defined as its accuracy in faithfully reproducing a quantity or behavior of interest of a real system. Increasing the fidelity of a model often goes hand in hand with increasing its cost in terms of time, money, or computing resources. The traditional aircraft design process relies upon low-fidelity models for expedience and resource savings. However, the reduced accuracy and reliability of low-fidelity tools often lead to the discovery of design defects or inadequacies late in the design process. These deficiencies result either in costly changes or the acceptance of a configuration that does not meet expectations. The unknown opportunity cost is the discovery of superior vehicles that leverage phenomena unknown to the designer and not illuminated by low-fidelity tools. Multifidelity methods attempt to blend the increased accuracy and reliability of high-fidelity models with the reduced cost of low-fidelity models. In building surrogate models, where mathematical expressions are used to cheaply approximate the behavior of costly data, low-fidelity models may be sampled extensively to resolve the underlying trend, while high-fidelity data are reserved to correct inaccuracies at key locations. Similarly, in design optimization a low-fidelity model may be queried many times in the search for new, better designs, with a high-fidelity model being exercised only once per iteration to evaluate the candidate design. In this dissertation, a new multifidelity, gradient-based optimization algorithm is proposed. It differs from the standard trust region approach in several ways, stemming from the new method maintaining an approximation of the inverse Hessian, that is the underlying curvature of the design problem. Whereas the typical trust region approach performs a full sub-optimization using the low-fidelity model at every iteration, the new technique finds a suitable descent direction and focuses the search along it, reducing the number of low-fidelity evaluations required. This narrowing of the search domain also alleviates the burden on the surrogate model corrections between the low- and high-fidelity data. Rather than requiring the surrogate to be accurate in a hyper-volume bounded by the trust region, the model needs only to be accurate along the forward-looking search direction. Maintaining the approximate inverse Hessian also allows the multifidelity algorithm to revert to high-fidelity optimization at any time. In contrast, the standard approach has no memory of the previously-computed high-fidelity data. The primary disadvantage of the proposed algorithm is that it may require modifications to the optimization software, whereas standard optimizers may be used as black-box drivers in the typical trust region method. A multifidelity, multidisciplinary simulation of aeroelastic vehicle performance is developed to demonstrate the optimization method. The numerical physics models include body-fitted Euler computational fluid dynamics; linear, panel aerodynamics; linear, finite-element computational structural mechanics; and reduced, modal structural bases. A central element of the multifidelity, multidisciplinary framework is a shared parametric, attributed geometric representation that ensures the analysis inputs are consistent between disciplines and fidelities. The attributed geometry also enables the transfer of data between disciplines. The new optimization algorithm, a standard trust region approach, and a single-fidelity quasi-Newton method are compared for a series of analytic test functions, using both polynomial chaos expansions and kriging to correct discrepancies between fidelity levels of data. In the aggregate, the new method requires fewer high-fidelity evaluations than the trust region approach in 51% of cases, and the same number of evaluations in 18%. The new approach also requires fewer low-fidelity evaluations, by up to an order of magnitude, in almost all cases. The efficacy of both multifidelity methods compared to single-fidelity optimization depends significantly on the behavior of the high-fidelity model and the quality of the low-fidelity approximation, though savings are realized in a large number of cases. The multifidelity algorithm is also compared to the single-fidelity quasi-Newton method for complex aeroelastic simulations. The vehicle design problem includes variables for planform shape, structural sizing, and cruise condition with constraints on trim and structural stresses. Considering the objective function reduction versus computational expenditure, the multifidelity process performs better in three of four cases in early iterations. However, the enforcement of a contracting trust region slows the multifidelity progress. Even so, leveraging the approximate inverse Hessian, the optimization can be seamlessly continued using high-fidelity data alone. Ultimately, the proposed new algorithm produced better designs in all four cases. Investigating the return on investment in terms of design improvement per computational hour confirms that the multifidelity advantage is greatest in early iterations, and managing the transition to high-fidelity optimization is critical.

Preliminary design of the cavity-end deformable mirror of the megajoule laser

NASA Astrophysics Data System (ADS)

Bozec, Xavier; Mercier-Ythier, Renaud; Carel, Jean-Louis; Coustal, Pierre; Michelin, Jean L.

1999-07-01

This paper describes a preliminary design to realize a 400 X 400 mm2 active deformable mirror in the framework of the LaserMegajoule French program. The proposed design is based on a force control strategy. Forces are generated by specific designed electromechanical actuators and transmitted to a Zerodur mirror through an annular soft pad. This pad is optimized to filter high frequency ripple generated by the spatial sampling of the efforts at the back of the mirror in order to decrease the needed number of actuators, and thus the cost of the deformable mirror, a specific optimization method has been developed and is applied to determine the best actuator pattern fitted on the wavefront aberrations to be corrected. Analysis, calculations, finite elements models, preliminary test and validations on breadboard models have shown that the proposed design in compliant with the functional and operation requirements. A design description and the main justifications, as the guidelines of mirror integration are given in this paper. Due to the simplicity of the concept and the use of validate and mastered technologies at SFIM Industries and REOSC, the design present a good reliability. Furthermore, a complete and very easy to work maintainability is favored by this deformable mirror definition. Each parts of the system is easily removable and replaceable on the laser line without carrying out a heavy procedure and complex tools.

Structural reliability analysis under evidence theory using the active learning kriging model

NASA Astrophysics Data System (ADS)

Yang, Xufeng; Liu, Yongshou; Ma, Panke

2017-11-01

Structural reliability analysis under evidence theory is investigated. It is rigorously proved that a surrogate model providing only correct sign prediction of the performance function can meet the accuracy requirement of evidence-theory-based reliability analysis. Accordingly, a method based on the active learning kriging model which only correctly predicts the sign of the performance function is proposed. Interval Monte Carlo simulation and a modified optimization method based on Karush-Kuhn-Tucker conditions are introduced to make the method more efficient in estimating the bounds of failure probability based on the kriging model. Four examples are investigated to demonstrate the efficiency and accuracy of the proposed method.

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

NASA Astrophysics Data System (ADS)

Luo, Yabo; Waden, Yongo P.

2017-06-01

Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

Thermal control systems for low-temperature heat rejection on a lunar base

NASA Technical Reports Server (NTRS)

Sridhar, K. R.; Gottmann, Matthias; Nanjundan, Ashok

1993-01-01

One of the important issues in the design of a lunar base is the thermal control system (TCS) used to reject low-temperature heat from the base. The TCS ensures that the base and the components inside are maintained within an acceptable temperature range. The temperature of the lunar surface peaks at 400 K during the 336-hour lunar day. Under these circumstances, direct dissipation of waste heat from the lunar base using passive radiators would be impractical. Thermal control systems based on thermal storage, shaded radiators, and heat pumps have been proposed. Based on proven technology, innovation, realistic complexity, reliability, and near-term applicability, a heat pump-based TCS was selected as a candidate for early missions. In this report, Rankine-cycle heat pumps and absorption heat pumps (ammonia water and lithium bromide-water) have been analyzed and optimized for a lunar base cooling load of 100 kW.

Theory, simulation and experiments for precise deflection control of radiotherapy electron beams.

PubMed

Figueroa, R; Leiva, J; Moncada, R; Rojas, L; Santibáñez, M; Valente, M; Velásquez, J; Young, H; Zelada, G; Yáñez, R; Guillen, Y

2018-03-08

Conventional radiotherapy is mainly applied by linear accelerators. Although linear accelerators provide dual (electron/photon) radiation beam modalities, both of them are intrinsically produced by a megavoltage electron current. Modern radiotherapy treatment techniques are based on suitable devices inserted or attached to conventional linear accelerators. Thus, precise control of delivered beam becomes a main key issue. This work presents an integral description of electron beam deflection control as required for novel radiotherapy technique based on convergent photon beam production. Theoretical and Monte Carlo approaches were initially used for designing and optimizing device´s components. Then, dedicated instrumentation was developed for experimental verification of electron beam deflection due to the designed magnets. Both Monte Carlo simulations and experimental results support the reliability of electrodynamics models used to predict megavoltage electron beam control. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimal maintenance of a multi-unit system under dependencies

NASA Astrophysics Data System (ADS)

Sung, Ho-Joon

The availability, or reliability, of an engineering component greatly influences the operational cost and safety characteristics of a modern system over its life-cycle. Until recently, the reliance on past empirical data has been the industry-standard practice to develop maintenance policies that provide the minimum level of system reliability. Because such empirically-derived policies are vulnerable to unforeseen or fast-changing external factors, recent advancements in the study of topic on maintenance, which is known as optimal maintenance problem, has gained considerable interest as a legitimate area of research. An extensive body of applicable work is available, ranging from those concerned with identifying maintenance policies aimed at providing required system availability at minimum possible cost, to topics on imperfect maintenance of multi-unit system under dependencies. Nonetheless, these existing mathematical approaches to solve for optimal maintenance policies must be treated with caution when considered for broader applications, as they are accompanied by specialized treatments to ease the mathematical derivation of unknown functions in both objective function and constraint for a given optimal maintenance problem. These unknown functions are defined as reliability measures in this thesis, and theses measures (e.g., expected number of failures, system renewal cycle, expected system up time, etc.) do not often lend themselves to possess closed-form formulas. It is thus quite common to impose simplifying assumptions on input probability distributions of components' lifetime or repair policies. Simplifying the complex structure of a multi-unit system to a k-out-of-n system by neglecting any sources of dependencies is another commonly practiced technique intended to increase the mathematical tractability of a particular model. This dissertation presents a proposal for an alternative methodology to solve optimal maintenance problems by aiming to achieve the same end-goals as Reliability Centered Maintenance (RCM). RCM was first introduced to the aircraft industry in an attempt to bridge the gap between the empirically-driven and theory-driven approaches to establishing optimal maintenance policies. Under RCM, qualitative processes that enable the prioritizing of functions based on the criticality and influence would be combined with mathematical modeling to obtain the optimal maintenance policies. Where this thesis work deviates from RCM is its proposal to directly apply quantitative processes to model the reliability measures in optimal maintenance problem. First, Monte Carlo (MC) simulation, in conjunction with a pre-determined Design of Experiments (DOE) table, can be used as a numerical means of obtaining the corresponding discrete simulated outcomes of the reliability measures based on the combination of decision variables (e.g., periodic preventive maintenance interval, trigger age for opportunistic maintenance, etc.). These discrete simulation results can then be regressed as Response Surface Equations (RSEs) with respect to the decision variables. Such an approach to represent the reliability measures with continuous surrogate functions (i.e., the RSEs) not only enables the application of the numerical optimization technique to solve for optimal maintenance policies, but also obviates the need to make mathematical assumptions or impose over-simplifications on the structure of a multi-unit system for the sake of mathematical tractability. The applicability of the proposed methodology to a real-world optimal maintenance problem is showcased through its application to a Time Limited Dispatch (TLD) of Full Authority Digital Engine Control (FADEC) system. In broader terms, this proof-of-concept exercise can be described as a constrained optimization problem, whose objective is to identify the optimal system inspection interval that guarantees a certain level of availability for a multi-unit system. A variety of reputable numerical techniques were used to model the problem as accurately as possible, including algorithms for the MC simulation, imperfect maintenance model from quasi renewal processes, repair time simulation, and state transition rules. Variance Reduction Techniques (VRTs) were also used in an effort to enhance MC simulation efficiency. After accurate MC simulation results are obtained, the RSEs are generated based on the goodness-of-fit measure to yield as parsimonious model as possible to construct the optimization problem. Under the assumption of constant failure rate for lifetime distributions, the inspection interval from the proposed methodology was found to be consistent with the one from the common approach used in industry that leverages Continuous Time Markov Chain (CTMC). While the latter does not consider maintenance cost settings, the proposed methodology enables an operator to consider different types of maintenance cost settings, e.g., inspection cost, system corrective maintenance cost, etc., to result in more flexible maintenance policies. When the proposed methodology was applied to the same TLD of FADEC example, but under the more generalized assumption of strictly Increasing Failure Rate (IFR) for lifetime distribution, it was shown to successfully capture component wear-out, as well as the economic dependencies among the system components.

Topology Optimization using the Level Set and eXtended Finite Element Methods: Theory and Applications

NASA Astrophysics Data System (ADS)

Villanueva Perez, Carlos Hernan

Computational design optimization provides designers with automated techniques to develop novel and non-intuitive optimal designs. Topology optimization is a design optimization technique that allows for the evolution of a broad variety of geometries in the optimization process. Traditional density-based topology optimization methods often lack a sufficient resolution of the geometry and physical response, which prevents direct use of the optimized design in manufacturing and the accurate modeling of the physical response of boundary conditions. The goal of this thesis is to introduce a unified topology optimization framework that uses the Level Set Method (LSM) to describe the design geometry and the eXtended Finite Element Method (XFEM) to solve the governing equations and measure the performance of the design. The methodology is presented as an alternative to density-based optimization approaches, and is able to accommodate a broad range of engineering design problems. The framework presents state-of-the-art methods for immersed boundary techniques to stabilize the systems of equations and enforce the boundary conditions, and is studied with applications in 2D and 3D linear elastic structures, incompressible flow, and energy and species transport problems to test the robustness and the characteristics of the method. A comparison of the framework against density-based topology optimization approaches is studied with regards to convergence, performance, and the capability to manufacture the designs. Furthermore, the ability to control the shape of the design to operate within manufacturing constraints is developed and studied. The analysis capability of the framework is validated quantitatively through comparison against previous benchmark studies, and qualitatively through its application to topology optimization problems. The design optimization problems converge to intuitive designs and resembled well the results from previous 2D or density-based studies.

Reliability model for ductile hybrid FRP rebar using randomly dispersed chopped fibers

NASA Astrophysics Data System (ADS)

Behnam, Bashar Ramzi

Fiber reinforced polymer composites or simply FRP composites have become more attractive to civil engineers in the last two decades due to their unique mechanical properties. However, there are many obstacles such as low elasticity modulus, non-ductile behavior, high cost of the fibers, high manufacturing costs, and absence of rigorous characterization of the uncertainties of the mechanical properties that restrict the use of these composites. However, when FRP composites are used to develop reinforcing rebars in concrete structural members to replace the conventional steel, a huge benefit can be achieved since FRP materials don't corrode. Two FRP rebar models are proposed that make use of multiple types of fibers to achieve ductility, and chopped fibers are used to reduce the manufacturing costs. In order to reach the most optimum fractional volume of each type of fiber, to minimize the cost of the proposed rebars, and to achieve a safe design by considering uncertainties in the materials and geometry of sections, appropriate material resistance factors have been developed, and a Reliability Based Design Optimization (RBDO), has been conducted for the proposed schemes.

A multiobjective optimization model and an orthogonal design-based hybrid heuristic algorithm for regional urban mining management problems.

PubMed

Wu, Hao; Wan, Zhong

2018-02-01

In this paper, a multiobjective mixed-integer piecewise nonlinear programming model (MOMIPNLP) is built to formulate the management problem of urban mining system, where the decision variables are associated with buy-back pricing, choices of sites, transportation planning, and adjustment of production capacity. Different from the existing approaches, the social negative effect, generated from structural optimization of the recycling system, is minimized in our model, as well as the total recycling profit and utility from environmental improvement are jointly maximized. For solving the problem, the MOMIPNLP model is first transformed into an ordinary mixed-integer nonlinear programming model by variable substitution such that the piecewise feature of the model is removed. Then, based on technique of orthogonal design, a hybrid heuristic algorithm is developed to find an approximate Pareto-optimal solution, where genetic algorithm is used to optimize the structure of search neighborhood, and both local branching algorithm and relaxation-induced neighborhood search algorithm are employed to cut the searching branches and reduce the number of variables in each branch. Numerical experiments indicate that this algorithm spends less CPU (central processing unit) time in solving large-scale regional urban mining management problems, especially in comparison with the similar ones available in literature. By case study and sensitivity analysis, a number of practical managerial implications are revealed from the model. Since the metal stocks in society are reliable overground mineral sources, urban mining has been paid great attention as emerging strategic resources in an era of resource shortage. By mathematical modeling and development of efficient algorithms, this paper provides decision makers with useful suggestions on the optimal design of recycling system in urban mining. For example, this paper can answer how to encourage enterprises to join the recycling activities by government's support and subsidies, whether the existing recycling system can meet the developmental requirements or not, and what is a reasonable adjustment of production capacity.

Cryogenic instrumentation for ITER magnets

NASA Astrophysics Data System (ADS)

Poncet, J.-M.; Manzagol, J.; Attard, A.; André, J.; Bizel-Bizellot, L.; Bonnay, P.; Ercolani, E.; Luchier, N.; Girard, A.; Clayton, N.; Devred, A.; Huygen, S.; Journeaux, J.-Y.

2017-02-01

Accurate measurements of the helium flowrate and of the temperature of the ITER magnets is of fundamental importance to make sure that the magnets operate under well controlled and reliable conditions, and to allow suitable helium flow distribution in the magnets through the helium piping. Therefore, the temperature and flow rate measurements shall be reliable and accurate. In this paper, we present the thermometric chains as well as the venturi flow meters installed in the ITER magnets and their helium piping. The presented thermometric block design is based on the design developed by CERN for the LHC, which has been further optimized via thermal simulations carried out by CEA. The electronic part of the thermometric chain was entirely developed by the CEA and will be presented in detail: it is based on a lock-in measurement and small signal amplification, and also provides a web interface and software to an industrial PLC. This measuring device provides a reliable, accurate, electromagnetically immune, and fast (up to 100 Hz bandwidth) system for resistive temperature sensors between a few ohms to 100 kΩ. The flowmeters (venturi type) which make up part of the helium mass flow measurement chain have been completely designed, and manufacturing is on-going. The behaviour of the helium gas has been studied in detailed thanks to ANSYS CFX software in order to obtain the same differential pressure for all types of flowmeters. Measurement uncertainties have been estimated and the influence of input parameters has been studied. Mechanical calculations have been performed to guarantee the mechanical strength of the venturis required for pressure equipment operating in nuclear environment. In order to complete the helium mass flow measurement chain, different technologies of absolute and differential pressure sensors have been tested in an applied magnetic field to identify equipment compatible with the ITER environment.

Functional Design of Highly Robust and Flexible Thin-Film Encapsulation Composed of Quasi-Perfect Sublayers for Transparent, Flexible Displays.

PubMed

Kwon, Jeong Hyun; Jeon, Yongmin; Choi, Seungyeop; Park, Jeong Woo; Kim, Hyuncheol; Choi, Kyung Cheol

2017-12-20

In this study, a structurally and materially designed thin-film encapsulation is proposed to guarantee the reliability of transparent, flexible displays by significantly improving their barrier properties, mechanical stability, and environmental reliability, all of which are essential for organic light-emitting diode (OLED) encapsulation. We fabricated a bioinspired, nacre-like ZnO/Al 2 O 3 /MgO laminate structure (ZAM) using atomic layer deposition for the microcrack toughening effect. The ZAM film was formed with intentional voids and defects through the formation of a quasi-perfect sublayer, rather than the simple fabrication of nanolaminate structures. The 240 nm thick ZAM-based multibarrier (ZAM-TFE) with a compressively strained organic layer demonstrated an optical transmittance of 91.35% in the visible range, an extremely low water vapor transmission rate of 2.06 × 10 -6 g/m 2 /day, a mechanical stability enduring a strain close to 1%, and a residual stress close to 0, showing significant improvement of key TFE properties in comparison to an Al 2 O 3 -based multibarrier. In addition, ZAM-TFE demonstrated superior environmental resistance without degradation of barrier properties in a severe environment of 85 °C and 90% relative humidity (RH). Thus, our structurally and materially designed ZAM film has been well optimized in terms of its applicability as a gas diffusion barrier as well as in terms of its mechanical and environmental reliability. Finally, we confirmed the feasibility of the ZAM-TFE through application in OLEDs. The low-temperature ZAM-TFE technology showed great potential to provide a highly robust and flexible TFE of TFOLEDs.

Design and evaluation of online arithmetic for signal processing applications on FPGAs

NASA Astrophysics Data System (ADS)

Galli, Reto; Tenca, Alexandre F.

2001-11-01

This paper shows the design and the evaluation of on-line arithmetic modules for the most common operators used in DSP applications, using FPGAs as the target technology. The designs are highly optimized for the target technology and the common range of precision in DSP. The results are based on experimental data collected using CAD tools. All designs are synthesized for the same type of devices (Xilinx XC4000) for comparison, avoiding rough estimates of the system performance, and generating a more reliable and detailed comparison of on-line signal processing solutions with other state of the art approaches, such as distributed arithmetic. We show that on-line designs have a hard stand for basic DSP applications that use only addition and multiplication. However, we also show that on-line designs are able to overtake other approaches as the applications become more sophisticated, e.g. when data dependencies exist, or when non constant multiplicands restrict the use of other approaches.

Benchmarking Heavy Ion Transport Codes FLUKA, HETC-HEDS MARS15, MCNPX, and PHITS

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

Ronningen, Reginald Martin; Remec, Igor; Heilbronn, Lawrence H.

Powerful accelerators such as spallation neutron sources, muon-collider/neutrino facilities, and rare isotope beam facilities must be designed with the consideration that they handle the beam power reliably and safely, and they must be optimized to yield maximum performance relative to their design requirements. The simulation codes used for design purposes must produce reliable results. If not, component and facility designs can become costly, have limited lifetime and usefulness, and could even be unsafe. The objective of this proposal is to assess the performance of the currently available codes PHITS, FLUKA, MARS15, MCNPX, and HETC-HEDS that could be used for designmore » simulations involving heavy ion transport. We plan to access their performance by performing simulations and comparing results against experimental data of benchmark quality. Quantitative knowledge of the biases and the uncertainties of the simulations is essential as this potentially impacts the safe, reliable and cost effective design of any future radioactive ion beam facility. Further benchmarking of heavy-ion transport codes was one of the actions recommended in the Report of the 2003 RIA R&D Workshop".« less

A Method to Predict the Reliability of Military Ground Vehicles Using High Performance Computing

DTIC Science & Technology

2006-11-01

Krayterman U.S. Army RDECOM-TARDEC Warren, MI 48397 K.K. Choi, Ed Hardee University of Iowa Coralville , IA 52242 Byeng D. Youn Michigan...University of Iowa , performed an optimization of the design for an A-arm on a military ground vehicle (a Stryker), using no sources of uncertainty...LSF for the queueing system. 3.3 Reliability/Fatigue Analysis software We used several pieces of propriety code from the University of Iowa

A Designed Experiments Approach to Optimizing MALDI-TOF MS Spectrum Processing Parameters Enhances Detection of Antibiotic Resistance in Campylobacter jejuni

PubMed Central

Penny, Christian; Grothendick, Beau; Zhang, Lin; Borror, Connie M.; Barbano, Duane; Cornelius, Angela J.; Gilpin, Brent J.; Fagerquist, Clifton K.; Zaragoza, William J.; Jay-Russell, Michele T.; Lastovica, Albert J.; Ragimbeau, Catherine; Cauchie, Henry-Michel; Sandrin, Todd R.

2016-01-01

MALDI-TOF MS has been utilized as a reliable and rapid tool for microbial fingerprinting at the genus and species levels. Recently, there has been keen interest in using MALDI-TOF MS beyond the genus and species levels to rapidly identify antibiotic resistant strains of bacteria. The purpose of this study was to enhance strain level resolution for Campylobacter jejuni through the optimization of spectrum processing parameters using a series of designed experiments. A collection of 172 strains of C. jejuni were collected from Luxembourg, New Zealand, North America, and South Africa, consisting of four groups of antibiotic resistant isolates. The groups included: (1) 65 strains resistant to cefoperazone (2) 26 resistant to cefoperazone and beta-lactams (3) 5 strains resistant to cefoperazone, beta-lactams, and tetracycline, and (4) 76 strains resistant to cefoperazone, teicoplanin, amphotericin, B and cephalothin. Initially, a model set of 16 strains (three biological replicates and three technical replicates per isolate, yielding a total of 144 spectra) of C. jejuni was subjected to each designed experiment to enhance detection of antibiotic resistance. The most optimal parameters were applied to the larger collection of 172 isolates (two biological replicates and three technical replicates per isolate, yielding a total of 1,031 spectra). We observed an increase in antibiotic resistance detection whenever either a curve based similarity coefficient (Pearson or ranked Pearson) was applied rather than a peak based (Dice) and/or the optimized preprocessing parameters were applied. Increases in antimicrobial resistance detection were scored using the jackknife maximum similarity technique following cluster analysis. From the first four groups of antibiotic resistant isolates, the optimized preprocessing parameters increased detection respective to the aforementioned groups by: (1) 5% (2) 9% (3) 10%, and (4) 2%. An additional second categorization was created from the collection consisting of 31 strains resistant to beta-lactams and 141 strains sensitive to beta-lactams. Applying optimal preprocessing parameters, beta-lactam resistance detection was increased by 34%. These results suggest that spectrum processing parameters, which are rarely optimized or adjusted, affect the performance of MALDI-TOF MS-based detection of antibiotic resistance and can be fine-tuned to enhance screening performance. PMID:27303397

Deformation mechanism of the Cryostat in the CADS Injector II

NASA Astrophysics Data System (ADS)

Yuan, Jiandong; Zhang, Bin; Wan, Yuqin; Sun, Guozhen; Bai, Feng; Zhang, Juihui; He, Yuan

2018-01-01

Thermal contraction and expansion of the Cryostat will affect its reliability and stability. To optimize and upgrade the Cryostat, we analyzed the heat transfer in a cryo-vacuum environment from the theoretical point first. The simulation of cryo-vacuum deformation based on a finite element method was implemented respectively. The completed measurement based on a Laser Tracker and a Micro Alignment Telescope was conducted to verify its correctness. The monitored deformations were consistent with the simulated ones. After the predictable deformations in vertical direction have been compensated, the superconducting solenoids and Half Wave Resonator cavities approached the ideal "zero" position under liquid helium conditions. These guaranteed the success of 25 MeV@170 uA continuous wave protons of Chinese accelerator driven subcritical system Injector II. By correlating the vacuum and cryo-deformation, we have demonstrated that the complete deformation was the superposition effect of the atmospheric pressure, gravity and thermal stress during both the process of cooling down and warming up. The results will benefit to an optimization for future Cryostat's design.

Many-objective optimization and visual analytics reveal key trade-offs for London's water supply

NASA Astrophysics Data System (ADS)

Matrosov, Evgenii S.; Huskova, Ivana; Kasprzyk, Joseph R.; Harou, Julien J.; Lambert, Chris; Reed, Patrick M.

2015-12-01

In this study, we link a water resource management simulator to multi-objective search to reveal the key trade-offs inherent in planning a real-world water resource system. We consider new supplies and demand management (conservation) options while seeking to elucidate the trade-offs between the best portfolios of schemes to satisfy projected water demands. Alternative system designs are evaluated using performance measures that minimize capital and operating costs and energy use while maximizing resilience, engineering and environmental metrics, subject to supply reliability constraints. Our analysis shows many-objective evolutionary optimization coupled with state-of-the art visual analytics can help planners discover more diverse water supply system designs and better understand their inherent trade-offs. The approach is used to explore future water supply options for the Thames water resource system (including London's water supply). New supply options include a new reservoir, water transfers, artificial recharge, wastewater reuse and brackish groundwater desalination. Demand management options include leakage reduction, compulsory metering and seasonal tariffs. The Thames system's Pareto approximate portfolios cluster into distinct groups of water supply options; for example implementing a pipe refurbishment program leads to higher capital costs but greater reliability. This study highlights that traditional least-cost reliability constrained design of water supply systems masks asset combinations whose benefits only become apparent when more planning objectives are considered.

Design and modeling of an efficiency horizontal thermal micro-actuator with integrated piezoresistors for precise control.

PubMed

Zhang, Yan; Lee, Dong-Weon

2010-05-01

An integrated system made up of a double-hot arm electro-thermal microactuator and a piezoresistor embedded at the base of the 'cold arm' is proposed. The electro-thermo-mechanical modeling and optimization is developed to elaborate the operation mechanism of the hybrid system through numerical simulations. For given materials, the geometry design mostly influences the performance of the sensor and actuator, which can be considered separately. That is because thermal expansion induced heating energy has less influence on the base area of the 'cold arm,' where is the maximum stress. The piezoresistor is positioned here for large sensitivity to monitor the in-plane movement of the system and characterize the actuator response precisely in real time. Force method is used to analyze the thermal induced mechanical expansion in the redundant structure. On the other hand, the integrated actuating mechanism is designed for high speed imaging. Based on the simulation results, the actuator operates at levels below 5 mA appearing to be very reliable, and the stress sensitivity is about 40 MPa per micron.

On the interaction structure of linear multi-input feedback control systems. M.S. Thesis; [problem solving, lattices (mathematics)

NASA Technical Reports Server (NTRS)

Wong, P. K.

1975-01-01

The closely-related problems of designing reliable feedback stabilization strategy and coordinating decentralized feedbacks are considered. Two approaches are taken. A geometric characterization of the structure of control interaction (and its dual) was first attempted and a concept of structural homomorphism developed based on the idea of 'similarity' of interaction pattern. The idea of finding classes of individual feedback maps that do not 'interfere' with the stabilizing action of each other was developed by identifying the structural properties of nondestabilizing and LQ-optimal feedback maps. Some known stability properties of LQ-feedback were generalized and some partial solutions were provided to the reliable stabilization and decentralized feedback coordination problems. A concept of coordination parametrization was introduced, and a scheme for classifying different modes of decentralization (information, control law computation, on-line control implementation) in control systems was developed.

Researches of fruit quality prediction model based on near infrared spectrum

NASA Astrophysics Data System (ADS)

Shen, Yulin; Li, Lian

2018-04-01

With the improvement in standards for food quality and safety, people pay more attention to the internal quality of fruits, therefore the measurement of fruit internal quality is increasingly imperative. In general, nondestructive soluble solid content (SSC) and total acid content (TAC) analysis of fruits is vital and effective for quality measurement in global fresh produce markets, so in this paper, we aim at establishing a novel fruit internal quality prediction model based on SSC and TAC for Near Infrared Spectrum. Firstly, the model of fruit quality prediction based on PCA + BP neural network, PCA + GRNN network, PCA + BP adaboost strong classifier, PCA + ELM and PCA + LS_SVM classifier are designed and implemented respectively; then, in the NSCT domain, the median filter and the SavitzkyGolay filter are used to preprocess the spectral signal, Kennard-Stone algorithm is used to automatically select the training samples and test samples; thirdly, we achieve the optimal models by comparing 15 kinds of prediction model based on the theory of multi-classifier competition mechanism, specifically, the non-parametric estimation is introduced to measure the effectiveness of proposed model, the reliability and variance of nonparametric estimation evaluation of each prediction model to evaluate the prediction result, while the estimated value and confidence interval regard as a reference, the experimental results demonstrate that this model can better achieve the optimal evaluation of the internal quality of fruit; finally, we employ cat swarm optimization to optimize two optimal models above obtained from nonparametric estimation, empirical testing indicates that the proposed method can provide more accurate and effective results than other forecasting methods.

Aerodynamic design applying automatic differentiation and using robust variable fidelity optimization

NASA Astrophysics Data System (ADS)

Takemiya, Tetsushi

In modern aerospace engineering, the physics-based computational design method is becoming more important, as it is more efficient than experiments and because it is more suitable in designing new types of aircraft (e.g., unmanned aerial vehicles or supersonic business jets) than the conventional design method, which heavily relies on historical data. To enhance the reliability of the physics-based computational design method, researchers have made tremendous efforts to improve the fidelity of models. However, high-fidelity models require longer computational time, so the advantage of efficiency is partially lost. This problem has been overcome with the development of variable fidelity optimization (VFO). In VFO, different fidelity models are simultaneously employed in order to improve the speed and the accuracy of convergence in an optimization process. Among the various types of VFO methods, one of the most promising methods is the approximation management framework (AMF). In the AMF, objective and constraint functions of a low-fidelity model are scaled at a design point so that the scaled functions, which are referred to as "surrogate functions," match those of a high-fidelity model. Since scaling functions and the low-fidelity model constitutes surrogate functions, evaluating the surrogate functions is faster than evaluating the high-fidelity model. Therefore, in the optimization process, in which gradient-based optimization is implemented and thus many function calls are required, the surrogate functions are used instead of the high-fidelity model to obtain a new design point. The best feature of the AMF is that it may converge to a local optimum of the high-fidelity model in much less computational time than the high-fidelity model. However, through literature surveys and implementations of the AMF, the author xx found that (1) the AMF is very vulnerable when the computational analysis models have numerical noise, which is very common in high-fidelity models, and that (2) the AMF terminates optimization erroneously when the optimization problems have constraints. The first problem is due to inaccuracy in computing derivatives in the AMF, and the second problem is due to erroneous treatment of the trust region ratio, which sets the size of the domain for an optimization in the AMF. In order to solve the first problem of the AMF, automatic differentiation (AD) technique, which reads the codes of analysis models and automatically generates new derivative codes based on some mathematical rules, is applied. If derivatives are computed with the generated derivative code, they are analytical, and the required computational time is independent of the number of design variables, which is very advantageous for realistic aerospace engineering problems. However, if analysis models implement iterative computations such as computational fluid dynamics (CFD), which solves system partial differential equations iteratively, computing derivatives through the AD requires a massive memory size. The author solved this deficiency by modifying the AD approach and developing a more efficient implementation with CFD, and successfully applied the AD to general CFD software. In order to solve the second problem of the AMF, the governing equation of the trust region ratio, which is very strict against the violation of constraints, is modified so that it can accept the violation of constraints within some tolerance. By accepting violations of constraints during the optimization process, the AMF can continue optimization without terminating immaturely and eventually find the true optimum design point. With these modifications, the AMF is referred to as "Robust AMF," and it is applied to airfoil and wing aerodynamic design problems using Euler CFD software. The former problem has 21 design variables, and the latter 64. In both problems, derivatives computed with the proposed AD method are first compared with those computed with the finite differentiation (FD) method, and then, the Robust AMF is implemented along with the sequential quadratic programming (SQP) optimization method with only high-fidelity models. The proposed AD method computes derivatives more accurately and faster than the FD method, and the Robust AMF successfully optimizes shapes of the airfoil and the wing in a much shorter time than SQP with only high-fidelity models. These results clearly show the effectiveness of the Robust AMF. Finally, the feasibility of reducing computational time for calculating derivatives and the necessity of AMF with an optimum design point always in the feasible region are discussed as future work.

Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain

DOE PAGES

Chavez, Hernan; Castillo-Villar, Krystel; Webb, Erin

2017-08-01

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meetmore » conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.« less

Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain

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

Chavez, Hernan; Castillo-Villar, Krystel; Webb, Erin

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meetmore » conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.« less

Piezoresistive Composite Silicon Dioxide Nanocantilever Surface Stress Sensor: Design and Optimization.

PubMed

Mathew, Ribu; Sankar, A Ravi

2018-05-01

In this paper, we present the design and optimization of a rectangular piezoresistive composite silicon dioxide nanocantilever sensor. Unlike the conventional design approach, we perform the sensor optimization by not only considering its electro-mechanical response but also incorporating the impact of self-heating induced thermal drift in its terminal characteristics. Through extensive simulations first we comprehend and quantify the inaccuracies due to self-heating effect induced by the geometrical and intrinsic parameters of the piezoresistor. Then, by optimizing the ratio of electrical sensitivity to thermal sensitivity defined as the sensitivity ratio (υ) we improve the sensor performance and measurement reliability. Results show that to ensure υ ≥ 1, shorter and wider piezoresistors are better. In addition, it is observed that unlike the general belief that high doping concentration of piezoresistor reduces thermal sensitivity in piezoresistive sensors, to ensure υ ≥ 1 doping concentration (p) should be in the range: 1E18 cm-3 ≤ p ≤ 1E19 cm-3. Finally, we provide a set of design guidelines that will help NEMS engineers to optimize the performance of such sensors for chemical and biological sensing applications.

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm.

PubMed

Pickett, Stephen D; Green, Darren V S; Hunt, David L; Pardoe, David A; Hughes, Ian

2011-01-13

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure-activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods.

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm

PubMed Central

2010-01-01

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure−activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods. PMID:24900251

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

NASA Astrophysics Data System (ADS)

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm.

PubMed

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

On the Improvement of Convergence Performance for Integrated Design of Wind Turbine Blade Using a Vector Dominating Multi-objective Evolution Algorithm

NASA Astrophysics Data System (ADS)

Wang, L.; Wang, T. G.; Wu, J. H.; Cheng, G. P.

2016-09-01

A novel multi-objective optimization algorithm incorporating evolution strategies and vector mechanisms, referred as VD-MOEA, is proposed and applied in aerodynamic- structural integrated design of wind turbine blade. In the algorithm, a set of uniformly distributed vectors is constructed to guide population in moving forward to the Pareto front rapidly and maintain population diversity with high efficiency. For example, two- and three- objective designs of 1.5MW wind turbine blade are subsequently carried out for the optimization objectives of maximum annual energy production, minimum blade mass, and minimum extreme root thrust. The results show that the Pareto optimal solutions can be obtained in one single simulation run and uniformly distributed in the objective space, maximally maintaining the population diversity. In comparison to conventional evolution algorithms, VD-MOEA displays dramatic improvement of algorithm performance in both convergence and diversity preservation for handling complex problems of multi-variables, multi-objectives and multi-constraints. This provides a reliable high-performance optimization approach for the aerodynamic-structural integrated design of wind turbine blade.

General purpose optimization software for engineering design

NASA Technical Reports Server (NTRS)

Vanderplaats, G. N.

1990-01-01

The author has developed several general purpose optimization programs over the past twenty years. The earlier programs were developed as research codes and served that purpose reasonably well. However, in taking the formal step from research to industrial application programs, several important lessons have been learned. Among these are the importance of clear documentation, immediate user support, and consistent maintenance. Most important has been the issue of providing software that gives a good, or at least acceptable, design at minimum computational cost. Here, the basic issues developing optimization software for industrial applications are outlined and issues of convergence rate, reliability, and relative minima are discussed. Considerable feedback has been received from users, and new software is being developed to respond to identified needs. The basic capabilities of this software are outlined. A major motivation for the development of commercial grade software is ease of use and flexibility, and these issues are discussed with reference to general multidisciplinary applications. It is concluded that design productivity can be significantly enhanced by the more widespread use of optimization as an everyday design tool.

Novel method to construct large-scale design space in lubrication process utilizing Bayesian estimation based on a small-scale design-of-experiment and small sets of large-scale manufacturing data.

PubMed

Maeda, Jin; Suzuki, Tatsuya; Takayama, Kozo

2012-12-01

A large-scale design space was constructed using a Bayesian estimation method with a small-scale design of experiments (DoE) and small sets of large-scale manufacturing data without enforcing a large-scale DoE. The small-scale DoE was conducted using various Froude numbers (X(1)) and blending times (X(2)) in the lubricant blending process for theophylline tablets. The response surfaces, design space, and their reliability of the compression rate of the powder mixture (Y(1)), tablet hardness (Y(2)), and dissolution rate (Y(3)) on a small scale were calculated using multivariate spline interpolation, a bootstrap resampling technique, and self-organizing map clustering. The constant Froude number was applied as a scale-up rule. Three experiments under an optimal condition and two experiments under other conditions were performed on a large scale. The response surfaces on the small scale were corrected to those on a large scale by Bayesian estimation using the large-scale results. Large-scale experiments under three additional sets of conditions showed that the corrected design space was more reliable than that on the small scale, even if there was some discrepancy in the pharmaceutical quality between the manufacturing scales. This approach is useful for setting up a design space in pharmaceutical development when a DoE cannot be performed at a commercial large manufacturing scale.

A Novel Cross-Layer Routing Protocol Based on Network Coding for Underwater Sensor Networks.

PubMed

Wang, Hao; Wang, Shilian; Bu, Renfei; Zhang, Eryang

2017-08-08

Underwater wireless sensor networks (UWSNs) have attracted increasing attention in recent years because of their numerous applications in ocean monitoring, resource discovery and tactical surveillance. However, the design of reliable and efficient transmission and routing protocols is a challenge due to the low acoustic propagation speed and complex channel environment in UWSNs. In this paper, we propose a novel cross-layer routing protocol based on network coding (NCRP) for UWSNs, which utilizes network coding and cross-layer design to greedily forward data packets to sink nodes efficiently. The proposed NCRP takes full advantages of multicast transmission and decode packets jointly with encoded packets received from multiple potential nodes in the entire network. The transmission power is optimized in our design to extend the life cycle of the network. Moreover, we design a real-time routing maintenance protocol to update the route when detecting inefficient relay nodes. Substantial simulations in underwater environment by Network Simulator 3 (NS-3) show that NCRP significantly improves the network performance in terms of energy consumption, end-to-end delay and packet delivery ratio compared with other routing protocols for UWSNs.

Ternary isocratic mobile phase optimization utilizing resolution Design Space based on retention time and peak width modeling.

PubMed

Kawabe, Takefumi; Tomitsuka, Toshiaki; Kajiro, Toshi; Kishi, Naoyuki; Toyo'oka, Toshimasa

2013-01-18

An optimization procedure of ternary isocratic mobile phase composition in the HPLC method using a statistical prediction model and visualization technique is described. In this report, two prediction models were first evaluated to obtain reliable prediction results. The retention time prediction model was constructed by modification from past respectable knowledge of retention modeling against ternary solvent strength changes. An excellent correlation between observed and predicted retention time was given in various kinds of pharmaceutical compounds by the multiple regression modeling of solvent strength parameters. The peak width of half height prediction model employed polynomial fitting of the retention time, because a linear relationship between the peak width of half height and the retention time was not obtained even after taking into account the contribution of the extra-column effect based on a moment method. Accurate prediction results were able to be obtained by such model, showing mostly over 0.99 value of correlation coefficient between observed and predicted peak width of half height. Then, a procedure to visualize a resolution Design Space was tried as the secondary challenge. An artificial neural network method was performed to link directly between ternary solvent strength parameters and predicted resolution, which were determined by accurate prediction results of retention time and a peak width of half height, and to visualize appropriate ternary mobile phase compositions as a range of resolution over 1.5 on the contour profile. By using mixtures of similar pharmaceutical compounds in case studies, we verified a possibility of prediction to find the optimal range of condition. Observed chromatographic results on the optimal condition mostly matched with the prediction and the average of difference between observed and predicted resolution were approximately 0.3. This means that enough accuracy for prediction could be achieved by the proposed procedure. Consequently, the procedure to search the optimal range of ternary solvent strength achieving an appropriate separation is provided by using the resolution Design Space based on accurate prediction. Copyright © 2012 Elsevier B.V. All rights reserved.

Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio-Inspired Optimization Techniques

DTIC Science & Technology

2017-11-01

ARL-TR-8225 ● NOV 2017 US Army Research Laboratory Methodology for Designing and Developing a New Ultra-Wideband Antenna Based...Research Laboratory Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio-Inspired Optimization Techniques by...SUBTITLE Methodology for Designing and Developing a New Ultra-Wideband Antenna Based on Bio-Inspired Optimization Techniques 5a. CONTRACT NUMBER

Predicting performance of axial pump inducer of LOX booster turbo-pump of staged combustion cycle based rocket engine using CFD

NASA Astrophysics Data System (ADS)

Mishra, Arpit; Ghosh, Parthasarathi

2015-12-01

For low cost, high thrust, space missions with high specific impulse and high reliability, inert weight needs to be minimized and thereby increasing the delivered payload. Turbopump feed system for a liquid propellant rocket engine (LPRE) has the highest power to weight ratio. Turbopumps are primarily equipped with an axial flow inducer to achieve the high angular velocity and low suction pressure in combination with increased system reliability. Performance of the turbopump strongly depends on the performance of the inducer. Thus, for designing a LPRE turbopump, demands optimization of the inducer geometry based on the performance of different off-design operating regimes. In this paper, steady-state CFD analysis of the inducer of a liquid oxygen (LOX) axial pump used as a booster pump for an oxygen rich staged combustion cycle rocket engine has been presented using ANSYS® CFX. Attempts have been made to obtain the performance characteristic curves for the LOX pump inducer. The formalism has been used to predict the performance of the inducer for the throttling range varying from 80% to 113% of nominal thrust and for the different rotational velocities from 4500 to 7500 rpm. The results have been analysed to determine the region of cavitation inception for different inlet pressure.

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

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

Man, Jun; Zhang, Jiangjiang; Li, Weixuan

2016-10-01

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

Hybrid Propulsion Technology Program, phase 1. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

1989-01-01

The study program was contracted to evaluate concepts of hybrid propulsion, select the most optimum, and prepare a conceptual design package. Further, this study required preparation of a technology definition package to identify hybrid propulsion enabling technologies and planning to acquire that technology in Phase 2 and demonstrate that technology in Phase 3. Researchers evaluated two design philosophies for Hybrid Rocket Booster (HRB) selection. The first is an ASRM modified hybrid wherein as many components/designs as possible were used from the present Advanced Solid Rocket Motor (ASRM) design. The second was an entirely new hybrid optimized booster using ASRM criteria as a point of departure, i.e., diameter, thrust time curve, launch facilities, and external tank attach points. Researchers selected the new design based on the logic of optimizing a hybrid booster to provide NASA with a next generation vehicle in lieu of an interim advancement over the ASRM. The enabling technologies for hybrid propulsion are applicable to either and vehicle design may be selected at a downstream point (Phase 3) at NASA's discretion. The completion of these studies resulted in ranking the various concepts of boosters from the RSRM to a turbopump fed (TF) hybrid. The scoring resulting from the Figure of Merit (FOM) scoring system clearly shows a natural growth path where the turbopump fed solid liquid staged combustion hybrid provides maximized payload and the highest safety, reliability, and low life cycle costing.

A general framework for optimization of probes for gene expression microarray and its application to the fungus Podospora anserina.

PubMed

Bidard, Frédérique; Imbeaud, Sandrine; Reymond, Nancie; Lespinet, Olivier; Silar, Philippe; Clavé, Corinne; Delacroix, Hervé; Berteaux-Lecellier, Véronique; Debuchy, Robert

2010-06-18

The development of new microarray technologies makes custom long oligonucleotide arrays affordable for many experimental applications, notably gene expression analyses. Reliable results depend on probe design quality and selection. Probe design strategy should cope with the limited accuracy of de novo gene prediction programs, and annotation up-dating. We present a novel in silico procedure which addresses these issues and includes experimental screening, as an empirical approach is the best strategy to identify optimal probes in the in silico outcome. We used four criteria for in silico probe selection: cross-hybridization, hairpin stability, probe location relative to coding sequence end and intron position. This latter criterion is critical when exon-intron gene structure predictions for intron-rich genes are inaccurate. For each coding sequence (CDS), we selected a sub-set of four probes. These probes were included in a test microarray, which was used to evaluate the hybridization behavior of each probe. The best probe for each CDS was selected according to three experimental criteria: signal-to-noise ratio, signal reproducibility, and representative signal intensities. This procedure was applied for the development of a gene expression Agilent platform for the filamentous fungus Podospora anserina and the selection of a single 60-mer probe for each of the 10,556 P. anserina CDS. A reliable gene expression microarray version based on the Agilent 44K platform was developed with four spot replicates of each probe to increase statistical significance of analysis.

Prospective regularization design in prior-image-based reconstruction

NASA Astrophysics Data System (ADS)

Dang, Hao; Siewerdsen, Jeffrey H.; Webster Stayman, J.

2015-12-01

Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in phantoms where the optimal parameters vary spatially by an order of magnitude or more. In a series of studies designed to explore potential unknowns associated with accurate PIBR, optimal prior image strength was found to vary with attenuation differences associated with anatomical change but exhibited only small variations as a function of the shape and size of the change. The results suggest that, given a target change attenuation, prospective patient-, change-, and data-specific customization of the prior image strength can be performed to ensure reliable reconstruction of specific anatomical changes.

Multiple sensitive estimation and optimal sample size allocation in the item sum technique.

PubMed

Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz

2018-01-01

For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimizing the early phase development of new analgesics by human pain biomarkers.

PubMed

Arendt-Nielsen, Lars; Hoeck, Hans Christian

2011-11-01

Human pain biomarkers are based on standardized acute activation of pain pathways/mechanisms and quantitative assessment of the evoked responses. This approach can be applied to healthy volunteers, to pain patients, and before and after pharmacological interventions to help understanding and profile the mode of action (proof-of-concept) of new and existing analgesic compounds. Standardized stimuli of different modalities can be applied to different tissues (multimodal and multi-tissue) for profiling analgesic compounds with respect to modulation of pain transduction, transmission, specific mechanisms and processing. This approach substantiates which specific compounds may work in particular clinical pain conditions. Human pain biomarkers can be translational and may bridge animal findings in clinical pain conditions, which in turn can provide new possibilities for designing more successful clinical trials. Biomarker based proof-of-concept drug studies in either volunteers or selected patient populations provide inexpensive, fast and reliable mechanism-based information about dose-efficacy relationships. This is important information in the early drug development phase and for designing large expensive clinical trials.

Real-time simulation of large-scale neural architectures for visual features computation based on GPU.

PubMed

Chessa, Manuela; Bianchi, Valentina; Zampetti, Massimo; Sabatini, Silvio P; Solari, Fabio

2012-01-01

The intrinsic parallelism of visual neural architectures based on distributed hierarchical layers is well suited to be implemented on the multi-core architectures of modern graphics cards. The design strategies that allow us to optimally take advantage of such parallelism, in order to efficiently map on GPU the hierarchy of layers and the canonical neural computations, are proposed. Specifically, the advantages of a cortical map-like representation of the data are exploited. Moreover, a GPU implementation of a novel neural architecture for the computation of binocular disparity from stereo image pairs, based on populations of binocular energy neurons, is presented. The implemented neural model achieves good performances in terms of reliability of the disparity estimates and a near real-time execution speed, thus demonstrating the effectiveness of the devised design strategies. The proposed approach is valid in general, since the neural building blocks we implemented are a common basis for the modeling of visual neural functionalities.

Inspection planning development: An evolutionary approach using reliability engineering as a tool

NASA Technical Reports Server (NTRS)

Graf, David A.; Huang, Zhaofeng

1994-01-01

This paper proposes an evolutionary approach for inspection planning which introduces various reliability engineering tools into the process and assess system trade-offs among reliability, engineering requirement, manufacturing capability and inspection cost to establish an optimal inspection plan. The examples presented in the paper illustrate some advantages and benefits of the new approach. Through the analysis, reliability and engineering impacts due to manufacturing process capability and inspection uncertainty are clearly understood; the most cost effective and efficient inspection plan can be established and associated risks are well controlled; some inspection reductions and relaxations are well justified; and design feedbacks and changes may be initiated from the analysis conclusion to further enhance reliability and reduce cost. The approach is particularly promising as global competitions and customer quality improvement expectations are rapidly increasing.

R software package based statistical optimization of process components to simultaneously enhance the bacterial growth, laccase production and textile dye decolorization with cytotoxicity study

PubMed Central

Dudhagara, Pravin; Tank, Shantilal

2018-01-01

The thermophilic bacterium, Bacillus licheniformis U1 is used for the optimization of bacterial growth (R1), laccase production (R2) and synthetic disperse blue DBR textile dye decolorization (R3) in the present study. Preliminary optimization has been performed by one variable at time (OVAT) approach using four media components viz., dye concentration, copper sulphate concentration, pH, and inoculum size. Based on OVAT result further statistical optimization of R1, R2 and R3 performed by Box–Behnken design (BBD) using response surface methodology (RSM) in R software with R Commander package. The total 29 experimental runs conducted in the experimental design study towards the construction of a quadratic model. The model indicated that dye concentration 110 ppm, copper sulphate 0.2 mM, pH 7.5 and inoculum size 6% v/v were found to be optimum to maximize the laccase production and bacterial growth. Whereas, maximum dye decolorization achieved in media containing dye concentration 110 ppm, copper sulphate 0.6 mM, pH 6 and inoculum size 6% v/v. R package predicted R2 of R1, R2 and R3 were 0.9917, 0.9831 and 0.9703 respectively; likened to Design-Expert (Stat-Ease) (DOE) predicted R2 of R1, R2, and R3 were 0.9893, 0.9822 and 0.8442 respectively. The values obtained by R software were more precise, reliable and reproducible, compared to the DOE model. The laccase production was 1.80 fold increased, and 2.24 fold enhancement in dye decolorization was achieved using optimized medium than initial experiments. Moreover, the laccase-treated sample demonstrated the less cytotoxic effect on L132 and MCF-7 cell lines compared to untreated sample using MTT assay. Higher cell viability and lower cytotoxicity observed in a laccase-treated sample suggest the impending application of bacterial laccase in the reduction of toxicity of dye to design rapid biodegradation process. PMID:29718934

Efficient Network Coding-Based Loss Recovery for Reliable Multicast in Wireless Networks

NASA Astrophysics Data System (ADS)

Chi, Kaikai; Jiang, Xiaohong; Ye, Baoliu; Horiguchi, Susumu

Recently, network coding has been applied to the loss recovery of reliable multicast in wireless networks [19], where multiple lost packets are XOR-ed together as one packet and forwarded via single retransmission, resulting in a significant reduction of bandwidth consumption. In this paper, we first prove that maximizing the number of lost packets for XOR-ing, which is the key part of the available network coding-based reliable multicast schemes, is actually a complex NP-complete problem. To address this limitation, we then propose an efficient heuristic algorithm for finding an approximately optimal solution of this optimization problem. Furthermore, we show that the packet coding principle of maximizing the number of lost packets for XOR-ing sometimes cannot fully exploit the potential coding opportunities, and we then further propose new heuristic-based schemes with a new coding principle. Simulation results demonstrate that the heuristic-based schemes have very low computational complexity and can achieve almost the same transmission efficiency as the current coding-based high-complexity schemes. Furthermore, the heuristic-based schemes with the new coding principle not only have very low complexity, but also slightly outperform the current high-complexity ones.

Optimal sensor placement for spatial lattice structure based on genetic algorithms

NASA Astrophysics Data System (ADS)

Liu, Wei; Gao, Wei-cheng; Sun, Yi; Xu, Min-jian

2008-10-01

Optimal sensor placement technique plays a key role in structural health monitoring of spatial lattice structures. This paper considers the problem of locating sensors on a spatial lattice structure with the aim of maximizing the data information so that structural dynamic behavior can be fully characterized. Based on the criterion of optimal sensor placement for modal test, an improved genetic algorithm is introduced to find the optimal placement of sensors. The modal strain energy (MSE) and the modal assurance criterion (MAC) have been taken as the fitness function, respectively, so that three placement designs were produced. The decimal two-dimension array coding method instead of binary coding method is proposed to code the solution. Forced mutation operator is introduced when the identical genes appear via the crossover procedure. A computational simulation of a 12-bay plain truss model has been implemented to demonstrate the feasibility of the three optimal algorithms above. The obtained optimal sensor placements using the improved genetic algorithm are compared with those gained by exiting genetic algorithm using the binary coding method. Further the comparison criterion based on the mean square error between the finite element method (FEM) mode shapes and the Guyan expansion mode shapes identified by data-driven stochastic subspace identification (SSI-DATA) method are employed to demonstrate the advantage of the different fitness function. The results showed that some innovations in genetic algorithm proposed in this paper can enlarge the genes storage and improve the convergence of the algorithm. More importantly, the three optimal sensor placement methods can all provide the reliable results and identify the vibration characteristics of the 12-bay plain truss model accurately.

Optimization of turning process through the analytic flank wear modelling

NASA Astrophysics Data System (ADS)

Del Prete, A.; Franchi, R.; De Lorenzis, D.

2018-05-01

In the present work, the approach used for the optimization of the process capabilities for Oil&Gas components machining will be described. These components are machined by turning of stainless steel castings workpieces. For this purpose, a proper Design Of Experiments (DOE) plan has been designed and executed: as output of the experimentation, data about tool wear have been collected. The DOE has been designed starting from the cutting speed and feed values recommended by the tools manufacturer; the depth of cut parameter has been maintained as a constant. Wear data has been obtained by means the observation of the tool flank wear under an optical microscope: the data acquisition has been carried out at regular intervals of working times. Through a statistical data and regression analysis, analytical models of the flank wear and the tool life have been obtained. The optimization approach used is a multi-objective optimization, which minimizes the production time and the number of cutting tools used, under the constraint on a defined flank wear level. The technique used to solve the optimization problem is a Multi Objective Particle Swarm Optimization (MOPS). The optimization results, validated by the execution of a further experimental campaign, highlighted the reliability of the work and confirmed the usability of the optimized process parameters and the potential benefit for the company.

Optimal design of groundwater remediation system using a probabilistic multi-objective fast harmony search algorithm under uncertainty

NASA Astrophysics Data System (ADS)

Luo, Qiankun; Wu, Jianfeng; Yang, Yun; Qian, Jiazhong; Wu, Jichun

2014-11-01

This study develops a new probabilistic multi-objective fast harmony search algorithm (PMOFHS) for optimal design of groundwater remediation systems under uncertainty associated with the hydraulic conductivity (K) of aquifers. The PMOFHS integrates the previously developed deterministic multi-objective optimization method, namely multi-objective fast harmony search algorithm (MOFHS) with a probabilistic sorting technique to search for Pareto-optimal solutions to multi-objective optimization problems in a noisy hydrogeological environment arising from insufficient K data. The PMOFHS is then coupled with the commonly used flow and transport codes, MODFLOW and MT3DMS, to identify the optimal design of groundwater remediation systems for a two-dimensional hypothetical test problem and a three-dimensional Indiana field application involving two objectives: (i) minimization of the total remediation cost through the engineering planning horizon, and (ii) minimization of the mass remaining in the aquifer at the end of the operational period, whereby the pump-and-treat (PAT) technology is used to clean up contaminated groundwater. Also, Monte Carlo (MC) analysis is employed to evaluate the effectiveness of the proposed methodology. Comprehensive analysis indicates that the proposed PMOFHS can find Pareto-optimal solutions with low variability and high reliability and is a potentially effective tool for optimizing multi-objective groundwater remediation problems under uncertainty.

Dual-Use Aspects of System Health Management

NASA Technical Reports Server (NTRS)

Owens, P. R.; Jambor, B. J.; Eger, G. W.; Clark, W. A.

1994-01-01

System Health Management functionality is an essential part of any space launch system. Health management functionality is an integral part of mission reliability, since it is needed to verify the reliability before the mission starts. Health Management is also a key factor in life cycle cost reduction and in increasing system availability. The degree of coverage needed by the system and the degree of coverage made available at a reasonable cost are critical parameters of a successful design. These problems are not unique to the launch vehicle world. In particular, the Intelligent Vehicle Highway System, commercial aircraft systems, train systems, and many types of industrial production facilities require various degrees of system health management. In all of these applications, too, the designers must balance the benefits and costs of health management in order to optimize costs. The importance of an integrated system is emphasized. That is, we present the case for considering health management as an integral part of system design, rather than functionality to be added on at the end of the design process. The importance of maintaining the system viewpoint is discussed in making hardware and software tradeoffs and in arriving at design decisions. We describe an approach to determine the parameters to be monitored in any system health management application. This approach is based on Design of Experiments (DOE), prototyping, failure modes and effects analyses, cost modeling and discrete event simulation. The various computer-based tools that facilitate the approach are discussed. The approach described originally was used to develop a fault tolerant avionics architecture for launch vehicles that incorporated health management as an integral part of the system. Finally, we discuss generalizing the technique to apply it to other domains. Several illustrations are presented.

Microwave-assisted of dispersive liquid-liquid microextraction and spectrophotometric determination of uranium after optimization based on Box-Behnken design and chemometrics methods.

PubMed

Niazi, Ali; Khorshidi, Neda; Ghaemmaghami, Pegah

2015-01-25

In this study an analytical procedure based on microwave-assisted dispersive liquid-liquid microextraction (MA-DLLME) and spectrophotometric coupled with chemometrics methods is proposed to determine uranium. In the proposed method, 4-(2-pyridylazo) resorcinol (PAR) is used as a chelating agent, and chloroform and ethanol are selected as extraction and dispersive solvent. The optimization strategy is carried out by using two level full factorial designs. Results of the two level full factorial design (2(4)) based on an analysis of variance demonstrated that the pH, concentration of PAR, amount of dispersive and extraction solvents are statistically significant. Optimal condition for three variables: pH, concentration of PAR, amount of dispersive and extraction solvents are obtained by using Box-Behnken design. Under the optimum conditions, the calibration graphs are linear in the range of 20.0-350.0 ng mL(-1) with detection limit of 6.7 ng mL(-1) (3δB/slope) and the enrichment factor of this method for uranium reached at 135. The relative standard deviation (R.S.D.) is 1.64% (n=7, c=50 ng mL(-1)). The partial least squares (PLS) modeling was used for multivariate calibration of the spectrophotometric data. The orthogonal signal correction (OSC) was used for preprocessing of data matrices and the prediction results of model, with and without using OSC, were statistically compared. MA-DLLME-OSC-PLS method was presented for the first time in this study. The root mean squares error of prediction (RMSEP) for uranium determination using PLS and OSC-PLS models were 4.63 and 0.98, respectively. This procedure allows the determination of uranium synthesis and real samples such as waste water with good reliability of the determination. Copyright © 2014. Published by Elsevier B.V.

Scenario-based fitted Q-iteration for adaptive control of water reservoir systems under uncertainty

NASA Astrophysics Data System (ADS)

Bertoni, Federica; Giuliani, Matteo; Castelletti, Andrea

2017-04-01

Over recent years, mathematical models have largely been used to support planning and management of water resources systems. Yet, the increasing uncertainties in their inputs - due to increased variability in the hydrological regimes - are a major challenge to the optimal operations of these systems. Such uncertainty, boosted by projected changing climate, violates the stationarity principle generally used for describing hydro-meteorological processes, which assumes time persisting statistical characteristics of a given variable as inferred by historical data. As this principle is unlikely to be valid in the future, the probability density function used for modeling stochastic disturbances (e.g., inflows) becomes an additional uncertain parameter of the problem, which can be described in a deterministic and set-membership based fashion. This study contributes a novel method for designing optimal, adaptive policies for controlling water reservoir systems under climate-related uncertainty. The proposed method, called scenario-based Fitted Q-Iteration (sFQI), extends the original Fitted Q-Iteration algorithm by enlarging the state space to include the space of the uncertain system's parameters (i.e., the uncertain climate scenarios). As a result, sFQI embeds the set-membership uncertainty of the future inflow scenarios in the action-value function and is able to approximate, with a single learning process, the optimal control policy associated to any scenario included in the uncertainty set. The method is demonstrated on a synthetic water system, consisting of a regulated lake operated for ensuring reliable water supply to downstream users. Numerical results show that the sFQI algorithm successfully identifies adaptive solutions to operate the system under different inflow scenarios, which outperform the control policy designed under historical conditions. Moreover, the sFQI policy generalizes over inflow scenarios not directly experienced during the policy design, thus alleviating the risk of mis-adaptation, namely the design of a solution fully adapted to a scenario that is different from the one that will actually realize.

Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG) Monitoring

PubMed Central

Ankhili, Amale; Tao, Xuyuan; Cochrane, Cédric; Coulon, David; Koncar, Vladan

2018-01-01

A medical quality electrocardiogram (ECG) signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) in order to develop and manufacture reliable and washable textile electrodes assembled to female underwear (bras), by sewing using commercially available conductive yarns. Washability tests of connected underwear containing textile electrodes and conductive threads were carried out up to 50 washing cycles. The influence of standardized washing cycles on the quality of ECG signals and the electrical properties of the textile electrodes were investigated and characterized. PMID:29414849

Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG) Monitoring.

PubMed

Ankhili, Amale; Tao, Xuyuan; Cochrane, Cédric; Coulon, David; Koncar, Vladan

2018-02-07

A medical quality electrocardiogram (ECG) signal is necessary for permanent monitoring, and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) in order to develop and manufacture reliable and washable textile electrodes assembled to female underwear (bras), by sewing using commercially available conductive yarns. Washability tests of connected underwear containing textile electrodes and conductive threads were carried out up to 50 washing cycles. The influence of standardized washing cycles on the quality of ECG signals and the electrical properties of the textile electrodes were investigated and characterized.

Combine Flash-Based FPGA TID and Long-Term Retention Reliabilities Through VT Shift

NASA Astrophysics Data System (ADS)

Wang, Jih-Jong; Rezzak, Nadia; Dsilva, Durwyn; Xue, Fengliang; Samiee, Salim; Singaraju, Pavan; Jia, James; Nguyen, Victor; Hawley, Frank; Hamdy, Esmat

2016-08-01

Reliability test results of data retention and total ionizing dose (TID) in 65 nm Flash-based field programmable gate array (FPGA) are presented. Long-chain inverter design is recommended for reliability evaluation because it is the worst case design for both effects. Based on preliminary test data, both issues are unified and modeled by one natural decay equation. The relative contributions of TID induced threshold-voltage shift and retention mechanisms are evaluated by analyzing test data.

Improving the FLORIS wind plant model for compatibility with gradient-based optimization

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

Thomas, Jared J.; Gebraad, Pieter MO; Ning, Andrew

The FLORIS (FLOw Redirection and Induction in Steady-state) model, a parametric wind turbine wake model that predicts steady-state wake characteristics based on wind turbine position and yaw angle, was developed for optimization of control settings and turbine locations. This article provides details on changes made to the FLORIS model to make the model more suitable for gradient-based optimization. Changes to the FLORIS model were made to remove discontinuities and add curvature to regions of non-physical zero gradient. Exact gradients for the FLORIS model were obtained using algorithmic differentiation. A set of three case studies demonstrate that using exact gradients withmore » gradient-based optimization reduces the number of function calls by several orders of magnitude. The case studies also show that adding curvature improves convergence behavior, allowing gradient-based optimization algorithms used with the FLORIS model to more reliably find better solutions to wind farm optimization problems.« less

A quantitative thermal and thermomechanical analysis for design optimization and robustness assessment of microassembled high power Yb:CaF2 thin-disk Laser

NASA Astrophysics Data System (ADS)

Joly, S.; Lemesre, M.-A.; Levrier, B.; Lyszyk, C.; Plano, B.; Courjaud, A.; Taira, T.; Bechou, L.

2018-09-01

While considerable effort in the field of high power laser research has been dedicated to evolving thin-disk Lasers into the kilowatt range, thermal and residual stress management remain a critical issue and need to be addressed. In this paper, a quantitative thermal and thermomechanical analysis is presented for design optimization and robustness of high power diode pumped thin-disk ytterbium Lasers based on thermal and thermomechanical Finite Element Method (FEM) simulations. In particular, Yb:CaF2 Lasers are examined with respect to the design and selection of the bonding interface material. Results propose the use of a metallic Au80Sn20 hard solder of greater than 20 μm thickness as a superior solution to adhesive bonding for the prevention of Laser crystal failure under high optical pumping power while maintaining sufficient resistance to mechanical strain. Thermal IR characterizations under "safe" CW pumping power validate our predicted FEM Multiphysics models. Finally, an essentially void-free Au80Sn20 soldering process has been demonstrated for the mounting of Yb:CaF2 crystals onto a CuW heat sink. He currently acts as a Full Professor in electronics and physics at the University of Bordeaux. His research field addresses characterization, physical and failure mechanisms modeling and methods for reliability prediction of optoelectronic/photonic micro and nano-assemblied devices (LEDs, laser diodes, fiber laser, optical amplifier, photodetectors, fibered optical module…) for different applications (telecommunications, medical, space...). Research interests focus on Design for Reliability at the early stage of the development of the device including design, fabrication, characterization and aging effects on packaged optoelectronic materials and functions which involves the exploration of the physics of the light-matter interactions as well as the understanding degradation processes. Since 2010 is currently the manager of the "Reliability Assessment of Micro and Nano-assemblied Devices" Research Group (EDMiNA) at IMS Laboratory. He is the author or co-author of more than 180 regular papers and international conferences. He has also chaired different sessions in international conferences and acts as a reviewer of peer-reviewed journals from Elsevier (Microelectronics Reliab., Optics and Laser Technology…), IOP (Optics Letters), IEEE (Photonics Technology Letters, Devices and Materials Reliability, Electron Devices…). He has managed over 20 PhDs grants and post-docs addressing projects focusing both on fundamental aspects as well as applied research with national and European industrial partnerships with over 5M€ of funding. He is involved in several French and European committees acting as reviewer expert for National Research Agency (ANR) and CATRENE/EURIPIDES programs. Since March 2016, he is appointed Visiting Professor at the French-Canadian Joint Lab LN2 - University of Sherbrooke (Qc, Canada) working on packaging and design for reliability of devices and systems for photonic applications.

A Multi-Attribute Pheromone Ant Secure Routing Algorithm Based on Reputation Value for Sensor Networks

PubMed Central

Zhang, Lin; Yin, Na; Fu, Xiong; Lin, Qiaomin; Wang, Ruchuan

2017-01-01

With the development of wireless sensor networks, certain network problems have become more prominent, such as limited node resources, low data transmission security, and short network life cycles. To solve these problems effectively, it is important to design an efficient and trusted secure routing algorithm for wireless sensor networks. Traditional ant-colony optimization algorithms exhibit only local convergence, without considering the residual energy of the nodes and many other problems. This paper introduces a multi-attribute pheromone ant secure routing algorithm based on reputation value (MPASR). This algorithm can reduce the energy consumption of a network and improve the reliability of the nodes’ reputations by filtering nodes with higher coincidence rates and improving the method used to update the nodes’ communication behaviors. At the same time, the node reputation value, the residual node energy and the transmission delay are combined to formulate a synthetic pheromone that is used in the formula for calculating the random proportion rule in traditional ant-colony optimization to select the optimal data transmission path. Simulation results show that the improved algorithm can increase both the security of data transmission and the quality of routing service. PMID:28282894

Application and optimization of microwave-assisted extraction and dispersive liquid-liquid microextraction followed by high-performance liquid chromatography for sensitive determination of polyamines in turkey breast meat samples.

PubMed

Bashiry, Moein; Mohammadi, Abdorreza; Hosseini, Hedayat; Kamankesh, Marzieh; Aeenehvand, Saeed; Mohammadi, Zaniar

2016-01-01

A novel method based on microwave-assisted extraction and dispersive liquid-liquid microextraction (MAE-DLLME) followed by high-performance liquid chromatography (HPLC) was developed for the determination of three polyamines from turkey breast meat samples. Response surface methodology (RSM) based on central composite design (CCD) was used to optimize the effective factors in DLLME process. The optimum microextraction efficiency was obtained under optimized conditions. The calibration graphs of the proposed method were linear in the range of 20-200 ng g(-1), with the coefficient determination (R(2)) higher than 0.9914. The relative standard deviations were 6.72-7.30% (n = 7). The limits of detection were in the range of 0.8-1.4 ng g(-1). The recoveries of these compounds in spiked turkey breast meat samples were from 95% to 105%. The increased sensitivity in using the MAE-DLLME-HPLC-UV has been demonstrated. Compared with previous methods, the proposed method is an accurate, rapid and reliable sample-pretreatment method. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Multiuser Manufacturing Resource Service Composition Method Based on the Bees Algorithm

PubMed Central

Xie, Yongquan; Zhou, Zude; Pham, Duc Truong; Xu, Wenjun; Ji, Chunqian

2015-01-01

In order to realize an optimal resource service allocation in current open and service-oriented manufacturing model, multiuser resource service composition (RSC) is modeled as a combinational and constrained multiobjective problem. The model takes into account both subjective and objective quality of service (QoS) properties as representatives to evaluate a solution. The QoS properties aggregation and evaluation techniques are based on existing researches. The basic Bees Algorithm is tailored for finding a near optimal solution to the model, since the basic version is only proposed to find a desired solution in continuous domain and thus not suitable for solving the problem modeled in our study. Particular rules are designed for handling the constraints and finding Pareto optimality. In addition, the established model introduces a trusted service set to each user so that the algorithm could start by searching in the neighbor of more reliable service chains (known as seeds) than those randomly generated. The advantages of these techniques are validated by experiments in terms of success rate, searching speed, ability of avoiding ingenuity, and so forth. The results demonstrate the effectiveness of the proposed method in handling multiuser RSC problems. PMID:26339232

Identifying strategic sites for Green-Infrastructures (GI) to manage stormwater in a miscellaneous use urban African watershed

NASA Astrophysics Data System (ADS)

Selker, J. S.; Kahsai, S. K.

2017-12-01

Green Infrastructure (GI) or Low impact development (LID), is a land use planning and design approach with the objective of mitigating land development impacts to the environment, and is ever more looked to as a way to lessen runoff and pollutant loading to receiving water bodies. Broad-scale approaches for siting GI/LID have been developed for agricultural watersheds, but are rare for urban watersheds, largely due to greater land use complexity. And it is even more challenging when it comes to Urban Africa due to the combination of poor data quality, rapid and unplanned development, and civic institutions unable to reliably carry out regular maintenance. We present a spacio-temporal simulation-based approach to identify an optimal prioritization of sites for GI/LID based on DEM, land use and land cover. Optimization used is a multi-objective optimization tool along with an urban storm water management model (SWMM) to identify the most cost-effective combination of LID/GI. This was applied to an urban watershed in NW Kampala, Lubigi Catchment (notorious for being heavily flooded every year), with a miscellaneous use watershed in Uganda, as a case-study to demonstrate the approach.

Space Shuttle 2 Advanced Space Transportation System. Volume 1: Executive Summary

NASA Technical Reports Server (NTRS)

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

1989-01-01

An investigation into the feasibility of establishing a second generation space transportation system is summarized. Incorporating successful systems from the Space Shuttle and technological advances made since its conception, the second generation shuttle was designed to be a lower-cost, reliable system which would guarantee access to space well into the next century. A fully reusable, all-liquid propellant booster/orbiter combination using parallel burn was selected as the base configuration. Vehicle characteristics were determined from NASA ground rules and optimization evaluations. The launch profile was constructed from particulars of the vehicle design and known orbital requirements. A stability and control analysis was performed for the landing phase of the orbiter's flight. Finally, a preliminary safety analysis was performed to indicate possible failure modes and consequences.