Algorithmic Mechanism Design of Evolutionary Computation
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm. PMID:26257777
Algorithmic Mechanism Design of Evolutionary Computation.
Pei, Yan
2015-01-01
We consider algorithmic design, enhancement, and improvement of evolutionary computation as a mechanism design problem. All individuals or several groups of individuals can be considered as self-interested agents. The individuals in evolutionary computation can manipulate parameter settings and operations by satisfying their own preferences, which are defined by an evolutionary computation algorithm designer, rather than by following a fixed algorithm rule. Evolutionary computation algorithm designers or self-adaptive methods should construct proper rules and mechanisms for all agents (individuals) to conduct their evolution behaviour correctly in order to definitely achieve the desired and preset objective(s). As a case study, we propose a formal framework on parameter setting, strategy selection, and algorithmic design of evolutionary computation by considering the Nash strategy equilibrium of a mechanism design in the search process. The evaluation results present the efficiency of the framework. This primary principle can be implemented in any evolutionary computation algorithm that needs to consider strategy selection issues in its optimization process. The final objective of our work is to solve evolutionary computation design as an algorithmic mechanism design problem and establish its fundamental aspect by taking this perspective. This paper is the first step towards achieving this objective by implementing a strategy equilibrium solution (such as Nash equilibrium) in evolutionary computation algorithm.
Application of Modified Flower Pollination Algorithm on Mechanical Engineering Design Problem
NASA Astrophysics Data System (ADS)
Kok Meng, Ong; Pauline, Ong; Chee Kiong, Sia; Wahab, Hanani Abdul; Jafferi, Noormaziah
2017-01-01
The aim of the optimization is to obtain the best solution among other solutions in order to achieve the objective of the problem without evaluation on all possible solutions. In this study, an improved flower pollination algorithm, namely, the Modified Flower Pollination Algorithms (MFPA) is developed. Comprising of the elements of chaos theory, frog leaping local search and adaptive inertia weight, the performance of MFPA is evaluated in optimizing five benchmark mechanical engineering design problems - tubular column design, speed reducer, gear train, tension/compression spring design and pressure vessel. The obtained results are listed and compared with the results of the other state-of-art algorithms. Assessment shows that the MFPA gives promising result in finding the optimal design for all considered mechanical engineering problems.
Genetic Algorithm for the Design of Electro-Mechanical Sigma Delta Modulator MEMS Sensors
Wilcock, Reuben; Kraft, Michael
2011-01-01
This paper describes a novel design methodology using non-linear models for complex closed loop electro-mechanical sigma-delta modulators (EMΣΔM) that is based on genetic algorithms and statistical variation analysis. The proposed methodology is capable of quickly and efficiently designing high performance, high order, closed loop, near-optimal systems that are robust to sensor fabrication tolerances and electronic component variation. The use of full non-linear system models allows significant higher order non-ideal effects to be taken into account, improving accuracy and confidence in the results. To demonstrate the effectiveness of the approach, two design examples are presented including a 5th order low-pass EMΣΔM for a MEMS accelerometer, and a 6th order band-pass EMΣΔM for the sense mode of a MEMS gyroscope. Each example was designed using the system in less than one day, with very little manual intervention. The strength of the approach is verified by SNR performances of 109.2 dB and 92.4 dB for the low-pass and band-pass system respectively, coupled with excellent immunities to fabrication tolerances and parameter mismatch. PMID:22163691
Genetic algorithm for the design of electro-mechanical sigma delta modulator MEMS sensors.
Wilcock, Reuben; Kraft, Michael
2011-01-01
This paper describes a novel design methodology using non-linear models for complex closed loop electro-mechanical sigma-delta modulators (EMΣΔM) that is based on genetic algorithms and statistical variation analysis. The proposed methodology is capable of quickly and efficiently designing high performance, high order, closed loop, near-optimal systems that are robust to sensor fabrication tolerances and electronic component variation. The use of full non-linear system models allows significant higher order non-ideal effects to be taken into account, improving accuracy and confidence in the results. To demonstrate the effectiveness of the approach, two design examples are presented including a 5th order low-pass EMΣΔM for a MEMS accelerometer, and a 6th order band-pass EMΣΔM for the sense mode of a MEMS gyroscope. Each example was designed using the system in less than one day, with very little manual intervention. The strength of the approach is verified by SNR performances of 109.2 dB and 92.4 dB for the low-pass and band-pass system respectively, coupled with excellent immunities to fabrication tolerances and parameter mismatch.
Andrews, Jeff; Likis, Frances E
2015-10-01
To aid authors in correctly naming their study design, to assist readers and reviewers who must decide what the design was for some published studies, and to provide consistency in evaluating the design of published studies, especially for those conducting systematic reviews and evidence synthesis. An annotated algorithm method is used to prompt serial questions and analysis to identify a single study design. The algorithm begins with a research article. Primary clinical research is divided into experimental and observational studies. Key determinants include identifying the study question and the population, intervention, comparison, and outcome. Experimental therapy and prognosis studies are subdivided into 4 design types. Observational therapy and prognosis studies are subdivided into 7 design types. Experimental diagnosis and screening studies are subdivided into 2 types. Observational diagnosis and screening studies are subdivided into 5 types. An annotated algorithm may be used by authors, readers, and reviewers to consistently determine the design of clinical research studies.
Amaritsakul, Yongyut; Chao, Ching-Kong
2013-01-01
Short-segment instrumentation for spine fractures is threatened by relatively high failure rates. Failure of the spinal pedicle screws including breakage and loosening may jeopardize the fixation integrity and lead to treatment failure. Two important design objectives, bending strength and pullout strength, may conflict with each other and warrant a multiobjective optimization study. In the present study using the three-dimensional finite element (FE) analytical results based on an L25 orthogonal array, bending and pullout objective functions were developed by an artificial neural network (ANN) algorithm, and the trade-off solutions known as Pareto optima were explored by a genetic algorithm (GA). The results showed that the knee solutions of the Pareto fronts with both high bending and pullout strength ranged from 92% to 94% of their maxima, respectively. In mechanical validation, the results of mathematical analyses were closely related to those of experimental tests with a correlation coefficient of −0.91 for bending and 0.93 for pullout (P < 0.01 for both). The optimal design had significantly higher fatigue life (P < 0.01) and comparable pullout strength as compared with commercial screws. Multiobjective optimization study of spinal pedicle screws using the hybrid of ANN and GA could achieve an ideal with high bending and pullout performances simultaneously. PMID:23983810
Amaritsakul, Yongyut; Chao, Ching-Kong; Lin, Jinn
2013-01-01
Short-segment instrumentation for spine fractures is threatened by relatively high failure rates. Failure of the spinal pedicle screws including breakage and loosening may jeopardize the fixation integrity and lead to treatment failure. Two important design objectives, bending strength and pullout strength, may conflict with each other and warrant a multiobjective optimization study. In the present study using the three-dimensional finite element (FE) analytical results based on an L25 orthogonal array, bending and pullout objective functions were developed by an artificial neural network (ANN) algorithm, and the trade-off solutions known as Pareto optima were explored by a genetic algorithm (GA). The results showed that the knee solutions of the Pareto fronts with both high bending and pullout strength ranged from 92% to 94% of their maxima, respectively. In mechanical validation, the results of mathematical analyses were closely related to those of experimental tests with a correlation coefficient of -0.91 for bending and 0.93 for pullout (P < 0.01 for both). The optimal design had significantly higher fatigue life (P < 0.01) and comparable pullout strength as compared with commercial screws. Multiobjective optimization study of spinal pedicle screws using the hybrid of ANN and GA could achieve an ideal with high bending and pullout performances simultaneously.
Shook, Richard; /Marquette U. /SLAC
2010-08-25
The particle beam of the SXR (soft x-ray) beam line in the LCLS (Linac Coherent Light Source) has a high intensity in order to penetrate through samples at the atomic level. However, the intensity is so high that many experiments fail because of severe damage. To correct this issue, attenuators are put into the beam line to reduce this intensity to a level suitable for experimentation. Attenuation is defined as 'the gradual loss in intensity of any flux through a medium' by [1]. It is found that Beryllium and Boron Carbide can survive the intensity of the beam. At very thin films, both of these materials work very well as filters for reducing the beam intensity. Using a total of 12 filters, the first 9 being made of Beryllium and the rest made of Boron Carbide, the beam's energy range of photons can be attenuated between 800 eV and 9000 eV. The design of the filters allows attenuation for different beam intensities so that experiments can obtain different intensities from the beam if desired. The step of attenuation varies, but is relative to the thickness of the filter as a power function of 2. A relationship for this is f(n) = x{sub 0}2{sup n} where n is the step of attenuation desired and x{sub 0} is the initial thickness of the material. To allow for this desired variation, a mechanism must be designed within the test chamber. This is visualized using a 3D computer aided design modeling tool known as Solid Edge.
NASA Technical Reports Server (NTRS)
1976-01-01
Design concepts for a 1000 mw thermal stationary power plant employing the UF6 fueled gas core breeder reactor are examined. Three design combinations-gaseous UF6 core with a solid matrix blanket, gaseous UF6 core with a liquid blanket, and gaseous UF6 core with a circulating blanket were considered. Results show the gaseous UF6 core with a circulating blanket was best suited to the power plant concept.
Molecular beacon sequence design algorithm.
Monroe, W Todd; Haselton, Frederick R
2003-01-01
A method based on Web-based tools is presented to design optimally functioning molecular beacons. Molecular beacons, fluorogenic hybridization probes, are a powerful tool for the rapid and specific detection of a particular nucleic acid sequence. However, their synthesis costs can be considerable. Since molecular beacon performance is based on its sequence, it is imperative to rationally design an optimal sequence before synthesis. The algorithm presented here uses simple Microsoft Excel formulas and macros to rank candidate sequences. This analysis is carried out using mfold structural predictions along with other free Web-based tools. For smaller laboratories where molecular beacons are not the focus of research, the public domain algorithm described here may be usefully employed to aid in molecular beacon design.
Automatic design of decision-tree algorithms with evolutionary algorithms.
Barros, Rodrigo C; Basgalupp, Márcio P; de Carvalho, André C P L F; Freitas, Alex A
2013-01-01
This study reports the empirical analysis of a hyper-heuristic evolutionary algorithm that is capable of automatically designing top-down decision-tree induction algorithms. Top-down decision-tree algorithms are of great importance, considering their ability to provide an intuitive and accurate knowledge representation for classification problems. The automatic design of these algorithms seems timely, given the large literature accumulated over more than 40 years of research in the manual design of decision-tree induction algorithms. The proposed hyper-heuristic evolutionary algorithm, HEAD-DT, is extensively tested using 20 public UCI datasets and 10 microarray gene expression datasets. The algorithms automatically designed by HEAD-DT are compared with traditional decision-tree induction algorithms, such as C4.5 and CART. Experimental results show that HEAD-DT is capable of generating algorithms which are significantly more accurate than C4.5 and CART.
Fashion sketch design by interactive genetic algorithms
NASA Astrophysics Data System (ADS)
Mok, P. Y.; Wang, X. X.; Xu, J.; Kwok, Y. L.
2012-11-01
Computer aided design is vitally important for the modern industry, particularly for the creative industry. Fashion industry faced intensive challenges to shorten the product development process. In this paper, a methodology is proposed for sketch design based on interactive genetic algorithms. The sketch design system consists of a sketch design model, a database and a multi-stage sketch design engine. First, a sketch design model is developed based on the knowledge of fashion design to describe fashion product characteristics by using parameters. Second, a database is built based on the proposed sketch design model to define general style elements. Third, a multi-stage sketch design engine is used to construct the design. Moreover, an interactive genetic algorithm (IGA) is used to accelerate the sketch design process. The experimental results have demonstrated that the proposed method is effective in helping laypersons achieve satisfied fashion design sketches.
Statistical Methods in Algorithm Design and Analysis.
ERIC Educational Resources Information Center
Weide, Bruce W.
The use of statistical methods in the design and analysis of discrete algorithms is explored. The introductory chapter contains a literature survey and background material on probability theory. In Chapter 2, probabilistic approximation algorithms are discussed with the goal of exposing and correcting some oversights in previous work. Chapter 3…
Public traffic transfer algorithm design
NASA Astrophysics Data System (ADS)
Yin, Kui-Ying; Jin, Lin; Qian, Bo; Fang, Kai
The route relationship matrix M is employed in this paper to indicate relationship between routes. The travel solutions for bus stations are obtained by matrix operation. Through the data mining to the history record of transportation information, the road transportation status at specific time interval can be predicted. Based on the predication, the best travel solutions can be found. The algorithm fully uses history transportation information, optimizes the travel solutions according to the time consumed. It can satisfy the time requirement of traveler and is very useful.
NASA Astrophysics Data System (ADS)
Beets, Timothy A.; Beno, Joseph H.; Chun, Moo-Young; Lee, Sungho; Park, Chan; Rafal, Marc; Worthington, Michael S.; Yuk, In-Soo
2012-09-01
A near-infrared spectrograph (NIRS) has been designed and proposed for utilization as a first-light instrument on the Giant Magellan Telescope (GMT). GMTNIRS includes modular JHK, LM spectrograph units mounted to two sides of a cryogenic optical bench. The optical bench and surrounding, protective radiation (thermal) shield are containerized within a rigid cryostat vessel, which mounts to the GMT instrument platform. A support structure on the secondary side of the optical bench provides multi-dimensional stiffness to the optical bench, to prevent excessive displacements of the optical components during tracking of the telescope. Extensive mechanical simulation and optimization was utilized to arrive at synergistic designs of the optical bench, support structure, cryostat, and thermal isolation system. Additionally, detailed steady-state and transient thermal analyses were conducted to optimize and verify the mechanical designs to maximize thermal efficiency and to size cryogenic coolers and conductors. This paper explains the mechanical and thermal design points stemming from optical component placement and mounting and structural and thermal characteristics needed to achieve instrument science requirements. The thermal and mechanical simulations will be described and the data will be summarized. Sufficient details of the analyses and data will be provided to validate the design decisions.
Mechanical Drawing and Design.
ERIC Educational Resources Information Center
Mikulsky, Marilyn; McEnaney, Walter K.
A syllabus is provided for a comprehensive foundation course in mechanical drawing and design for grades 9, 10, 11, or 12 that is prerequisite to advanced elective courses. Introductory materials include course objectives, an overview of basic concepts, and guidelines for implementation. Brief discussions of and suggestions for the areas of design…
Mechanical Drawing and Design.
ERIC Educational Resources Information Center
Mikulsky, Marilyn; McEnaney, Walter K.
A syllabus is provided for a comprehensive foundation course in mechanical drawing and design for grades 9, 10, 11, or 12 that is prerequisite to advanced elective courses. Introductory materials include course objectives, an overview of basic concepts, and guidelines for implementation. Brief discussions of and suggestions for the areas of design…
Mechanical Design of Spacecraft
NASA Technical Reports Server (NTRS)
1962-01-01
In the spring of 1962, engineers from the Engineering Mechanics Division of the Jet Propulsion Laboratory gave a series of lectures on spacecraft design at the Engineering Design seminars conducted at the California Institute of Technology. Several of these lectures were subsequently given at Stanford University as part of the Space Technology seminar series sponsored by the Department of Aeronautics and Astronautics. Presented here are notes taken from these lectures. The lectures were conceived with the intent of providing the audience with a glimpse of the activities of a few mechanical engineers who are involved in designing, building, and testing spacecraft. Engineering courses generally consist of heavily idealized problems in order to allow the more efficient teaching of mathematical technique. Students, therefore, receive a somewhat limited exposure to actual engineering problems, which are typified by more unknowns than equations. For this reason it was considered valuable to demonstrate some of the problems faced by spacecraft designers, the processes used to arrive at solutions, and the interactions between the engineer and the remainder of the organization in which he is constrained to operate. These lecture notes are not so much a compilation of sophisticated techniques of analysis as they are a collection of examples of spacecraft hardware and associated problems. They will be of interest not so much to the experienced spacecraft designer as to those who wonder what part the mechanical engineer plays in an effort such as the exploration of space.
NASA Technical Reports Server (NTRS)
Wolpert, David H.; Turner, Kagan
2004-01-01
The field of mechanism design is concerned with setting (incentives superimposed on) the utility functions of a group of players so as to induce desirable joint behavior of those players. It arose in the context of traditional equilibrium game theory applied to games involving human players. This has led it to have many implicit restrictions, which strongly limits its scope. In particular, it ignores many issues that are crucial for systems that are large (and therefore far off-equilibrium in general) and/or composed of non-human players (e.g., computer-based agents). This also means it has concentrated on issues that are often irrelevant in those broader domains (e.g., incentive compatibility). This paper illustrates these shortcomings by reviewing some of the recent theoretical work on the design of collectives, a body of work that constitutes a substantial broadening of mechanism design. It then presents computer experiments based on a recently suggested nanotechnology testbed that demonstrates the power of that extended version of mechanism design.
Fast Fourier Transform algorithm design and tradeoffs
NASA Technical Reports Server (NTRS)
Kamin, Ray A., III; Adams, George B., III
1988-01-01
The Fast Fourier Transform (FFT) is a mainstay of certain numerical techniques for solving fluid dynamics problems. The Connection Machine CM-2 is the target for an investigation into the design of multidimensional Single Instruction Stream/Multiple Data (SIMD) parallel FFT algorithms for high performance. Critical algorithm design issues are discussed, necessary machine performance measurements are identified and made, and the performance of the developed FFT programs are measured. Fast Fourier Transform programs are compared to the currently best Cray-2 FFT program.
Algorithm for backrub motions in protein design
Georgiev, Ivelin; Keedy, Daniel; Richardson, Jane S.; Richardson, David C.; Donald, Bruce R.
2008-01-01
Motivation: The Backrub is a small but kinematically efficient side-chain-coupled local backbone motion frequently observed in atomic-resolution crystal structures of proteins. A backrub shifts the Cα–Cβ orientation of a given side-chain by rigid-body dipeptide rotation plus smaller individual rotations of the two peptides, with virtually no change in the rest of the protein. Backrubs can therefore provide a biophysically realistic model of local backbone flexibility for structure-based protein design. Previously, however, backrub motions were applied via manual interactive model-building, so their incorporation into a protein design algorithm (a simultaneous search over mutation and backbone/side-chain conformation space) was infeasible. Results: We present a combinatorial search algorithm for protein design that incorporates an automated procedure for local backbone flexibility via backrub motions. We further derive a dead-end elimination (DEE)-based criterion for pruning candidate rotamers that, in contrast to previous DEE algorithms, is provably accurate with backrub motions. Our backrub-based algorithm successfully predicts alternate side-chain conformations from ≤0.9 Å resolution structures, confirming the suitability of the automated backrub procedure. Finally, the application of our algorithm to redesign two different proteins is shown to identify a large number of lower-energy conformations and mutation sequences that would have been ignored by a rigid-backbone model. Availability: Contact authors for source code. Contact: brd+ismb08@cs.duke.edu PMID:18586714
Instrument design and optimization using genetic algorithms
Hoelzel, Robert; Bentley, Phillip M.; Fouquet, Peter
2006-10-15
This article describes the design of highly complex physical instruments by using a canonical genetic algorithm (GA). The procedure can be applied to all instrument designs where performance goals can be quantified. It is particularly suited to the optimization of instrument design where local optima in the performance figure of merit are prevalent. Here, a GA is used to evolve the design of the neutron spin-echo spectrometer WASP which is presently being constructed at the Institut Laue-Langevin, Grenoble, France. A comparison is made between this artificial intelligence approach and the traditional manual design methods. We demonstrate that the search of parameter space is more efficient when applying the genetic algorithm, and the GA produces a significantly better instrument design. Furthermore, it is found that the GA increases flexibility, by facilitating the reoptimization of the design after changes in boundary conditions during the design phase. The GA also allows the exploration of 'nonstandard' magnet coil geometries. We conclude that this technique constitutes a powerful complementary tool for the design and optimization of complex scientific apparatus, without replacing the careful thought processes employed in traditional design methods.
Raghunathan, Shriram; Gupta, Sumeet K; Markandeya, Himanshu S; Roy, Kaushik; Irazoqui, Pedro P
2010-10-30
Implantable neural prostheses that deliver focal electrical stimulation upon demand are rapidly emerging as an alternate therapy for roughly a third of the epileptic patient population that is medically refractory. Seizure detection algorithms enable feedback mechanisms to provide focally and temporally specific intervention. Real-time feasibility and computational complexity often limit most reported detection algorithms to implementations using computers for bedside monitoring or external devices communicating with the implanted electrodes. A comparison of algorithms based on detection efficacy does not present a complete picture of the feasibility of the algorithm with limited computational power, as is the case with most battery-powered applications. We present a two-dimensional design optimization approach that takes into account both detection efficacy and hardware cost in evaluating algorithms for their feasibility in an implantable application. Detection features are first compared for their ability to detect electrographic seizures from micro-electrode data recorded from kainate-treated rats. Circuit models are then used to estimate the dynamic and leakage power consumption of the compared features. A score is assigned based on detection efficacy and the hardware cost for each of the features, then plotted on a two-dimensional design space. An optimal combination of compared features is used to construct an algorithm that provides maximal detection efficacy per unit hardware cost. The methods presented in this paper would facilitate the development of a common platform to benchmark seizure detection algorithms for comparison and feasibility analysis in the next generation of implantable neuroprosthetic devices to treat epilepsy.
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
Automated Antenna Design with Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Hornby, Gregory S.; Globus, Al; Linden, Derek S.; Lohn, Jason D.
2006-01-01
Current methods of designing and optimizing antennas by hand are time and labor intensive, and limit complexity. Evolutionary design techniques can overcome these limitations by searching the design space and automatically finding effective solutions. In recent years, evolutionary algorithms have shown great promise in finding practical solutions in large, poorly understood design spaces. In particular, spacecraft antenna design has proven tractable to evolutionary design techniques. Researchers have been investigating evolutionary antenna design and optimization since the early 1990s, and the field has grown in recent years as computer speed has increased and electromagnetic simulators have improved. Two requirements-compliant antennas, one for ST5 and another for TDRS-C, have been automatically designed by evolutionary algorithms. The ST5 antenna is slated to fly this year, and a TDRS-C phased array element has been fabricated and tested. Such automated evolutionary design is enabled by medium-to-high quality simulators and fast modern computers to evaluate computer-generated designs. Evolutionary algorithms automate cut-and-try engineering, substituting automated search though millions of potential designs for intelligent search by engineers through a much smaller number of designs. For evolutionary design, the engineer chooses the evolutionary technique, parameters and the basic form of the antenna, e.g., single wire for ST5 and crossed-element Yagi for TDRS-C. Evolutionary algorithms then search for optimal configurations in the space defined by the engineer. NASA's Space Technology 5 (ST5) mission will launch three small spacecraft to test innovative concepts and technologies. Advanced evolutionary algorithms were used to automatically design antennas for ST5. The combination of wide beamwidth for a circularly-polarized wave and wide impedance bandwidth made for a challenging antenna design problem. From past experience in designing wire antennas, we chose to
Predicting Resistance Mutations Using Protein Design Algorithms
Frey, K.; Georgiev, I; Donald, B; Anderson, A
2010-01-01
Drug resistance resulting from mutations to the target is an unfortunate common phenomenon that limits the lifetime of many of the most successful drugs. In contrast to the investigation of mutations after clinical exposure, it would be powerful to be able to incorporate strategies early in the development process to predict and overcome the effects of possible resistance mutations. Here we present a unique prospective application of an ensemble-based protein design algorithm, K*, to predict potential resistance mutations in dihydrofolate reductase from Staphylococcus aureus using positive design to maintain catalytic function and negative design to interfere with binding of a lead inhibitor. Enzyme inhibition assays show that three of the four highly-ranked predicted mutants are active yet display lower affinity (18-, 9-, and 13-fold) for the inhibitor. A crystal structure of the top-ranked mutant enzyme validates the predicted conformations of the mutated residues and the structural basis of the loss of potency. The use of protein design algorithms to predict resistance mutations could be incorporated in a lead design strategy against any target that is susceptible to mutational resistance.
Problem Solving Techniques for the Design of Algorithms.
ERIC Educational Resources Information Center
Kant, Elaine; Newell, Allen
1984-01-01
Presents model of algorithm design (activity in software development) based on analysis of protocols of two subjects designing three convex hull algorithms. Automation methods, methods for studying algorithm design, role of discovery in problem solving, and comparison of different designs of case study according to model are highlighted.…
Problem Solving Techniques for the Design of Algorithms.
ERIC Educational Resources Information Center
Kant, Elaine; Newell, Allen
1984-01-01
Presents model of algorithm design (activity in software development) based on analysis of protocols of two subjects designing three convex hull algorithms. Automation methods, methods for studying algorithm design, role of discovery in problem solving, and comparison of different designs of case study according to model are highlighted.…
Fast search algorithms for computational protein design.
Traoré, Seydou; Roberts, Kyle E; Allouche, David; Donald, Bruce R; André, Isabelle; Schiex, Thomas; Barbe, Sophie
2016-05-05
One of the main challenges in computational protein design (CPD) is the huge size of the protein sequence and conformational space that has to be computationally explored. Recently, we showed that state-of-the-art combinatorial optimization technologies based on Cost Function Network (CFN) processing allow speeding up provable rigid backbone protein design methods by several orders of magnitudes. Building up on this, we improved and injected CFN technology into the well-established CPD package Osprey to allow all Osprey CPD algorithms to benefit from associated speedups. Because Osprey fundamentally relies on the ability of A* to produce conformations in increasing order of energy, we defined new A* strategies combining CFN lower bounds, with new side-chain positioning-based branching scheme. Beyond the speedups obtained in the new A*-CFN combination, this novel branching scheme enables a much faster enumeration of suboptimal sequences, far beyond what is reachable without it. Together with the immediate and important speedups provided by CFN technology, these developments directly benefit to all the algorithms that previously relied on the DEE/ A* combination inside Osprey* and make it possible to solve larger CPD problems with provable algorithms. © 2016 Wiley Periodicals, Inc.
NASA Technical Reports Server (NTRS)
Roth, J. P.
1972-01-01
Methods for development of logic design together with algorithms for failure testing, a method for design of logic for ultra-large-scale integration, extension of quantum calculus to describe the functional behavior of a mechanism component-by-component and to computer tests for failures in the mechanism using the diagnosis algorithm, and the development of an algorithm for the multi-output 2-level minimization problem are discussed.
EGNAS: an exhaustive DNA sequence design algorithm
2012-01-01
Background The molecular recognition based on the complementary base pairing of deoxyribonucleic acid (DNA) is the fundamental principle in the fields of genetics, DNA nanotechnology and DNA computing. We present an exhaustive DNA sequence design algorithm that allows to generate sets containing a maximum number of sequences with defined properties. EGNAS (Exhaustive Generation of Nucleic Acid Sequences) offers the possibility of controlling both interstrand and intrastrand properties. The guanine-cytosine content can be adjusted. Sequences can be forced to start and end with guanine or cytosine. This option reduces the risk of “fraying” of DNA strands. It is possible to limit cross hybridizations of a defined length, and to adjust the uniqueness of sequences. Self-complementarity and hairpin structures of certain length can be avoided. Sequences and subsequences can optionally be forbidden. Furthermore, sequences can be designed to have minimum interactions with predefined strands and neighboring sequences. Results The algorithm is realized in a C++ program. TAG sequences can be generated and combined with primers for single-base extension reactions, which were described for multiplexed genotyping of single nucleotide polymorphisms. Thereby, possible foldback through intrastrand interaction of TAG-primer pairs can be limited. The design of sequences for specific attachment of molecular constructs to DNA origami is presented. Conclusions We developed a new software tool called EGNAS for the design of unique nucleic acid sequences. The presented exhaustive algorithm allows to generate greater sets of sequences than with previous software and equal constraints. EGNAS is freely available for noncommercial use at http://www.chm.tu-dresden.de/pc6/EGNAS. PMID:22716030
Primal-dual techniques for online algorithms and mechanisms
NASA Astrophysics Data System (ADS)
Liaghat, Vahid
An offline algorithm is one that knows the entire input in advance. An online algorithm, however, processes its input in a serial fashion. In contrast to offline algorithms, an online algorithm works in a local fashion and has to make irrevocable decisions without having the entire input. Online algorithms are often not optimal since their irrevocable decisions may turn out to be inefficient after receiving the rest of the input. For a given online problem, the goal is to design algorithms which are competitive against the offline optimal solutions. In a classical offline scenario, it is often common to see a dual analysis of problems that can be formulated as a linear or convex program. Primal-dual and dual-fitting techniques have been successfully applied to many such problems. Unfortunately, the usual tricks come short in an online setting since an online algorithm should make decisions without knowing even the whole program. In this thesis, we study the competitive analysis of fundamental problems in the literature such as different variants of online matching and online Steiner connectivity, via online dual techniques. Although there are many generic tools for solving an optimization problem in the offline paradigm, in comparison, much less is known for tackling online problems. The main focus of this work is to design generic techniques for solving integral linear optimization problems where the solution space is restricted via a set of linear constraints. A general family of these problems are online packing/covering problems. Our work shows that for several seemingly unrelated problems, primal-dual techniques can be successfully applied as a unifying approach for analyzing these problems. We believe this leads to generic algorithmic frameworks for solving online problems. In the first part of the thesis, we show the effectiveness of our techniques in the stochastic settings and their applications in Bayesian mechanism design. In particular, we introduce new
Navigation Constellation Design Using a Multi-Objective Genetic Algorithm
2015-03-26
NAVIGATION CONSTELLATION DESIGN USING A MULTI-OBJECTIVE GENETIC ALGORITHM THESIS MARCH 2015...the United States. AFIT-ENY-MS-15-M-245 NAVIGATION CONSTELLATION DESIGN USING A MULTI-OBJECTIVE GENETIC ALGORITHM THESIS Presented to...DISTRIBUTION UNLIMITED. AFIT-ENY-MS-15-M-245 NAVIGATION CONSTELLATION DESIGN USING A MULTI-OBJECTIVE GENETIC ALGORITHM Heather C. Diniz
UWB Tracking System Design with TDOA Algorithm
NASA Technical Reports Server (NTRS)
Ni, Jianjun; Arndt, Dickey; Ngo, Phong; Phan, Chau; Gross, Julia; Dusl, John; Schwing, Alan
2006-01-01
This presentation discusses an ultra-wideband (UWB) tracking system design effort using a tracking algorithm TDOA (Time Difference of Arrival). UWB technology is exploited to implement the tracking system due to its properties, such as high data rate, fine time resolution, and low power spectral density. A system design using commercially available UWB products is proposed. A two-stage weighted least square method is chosen to solve the TDOA non-linear equations. Matlab simulations in both two-dimensional space and three-dimensional space show that the tracking algorithm can achieve fine tracking resolution with low noise TDOA data. The error analysis reveals various ways to improve the tracking resolution. Lab experiments demonstrate the UWBTDOA tracking capability with fine resolution. This research effort is motivated by a prototype development project Mini-AERCam (Autonomous Extra-vehicular Robotic Camera), a free-flying video camera system under development at NASA Johnson Space Center for aid in surveillance around the International Space Station (ISS).
Optimal brushless DC motor design using genetic algorithms
NASA Astrophysics Data System (ADS)
Rahideh, A.; Korakianitis, T.; Ruiz, P.; Keeble, T.; Rothman, M. T.
2010-11-01
This paper presents a method for the optimal design of a slotless permanent magnet brushless DC (BLDC) motor with surface mounted magnets using a genetic algorithm. Characteristics of the motor are expressed as functions of motor geometries. The objective function is a combination of losses, volume and cost to be minimized simultaneously. Electrical and mechanical requirements (i.e. voltage, torque and speed) and other limitations (e.g. upper and lower limits of the motor geometries) are cast into constraints of the optimization problem. One sample case is used to illustrate the design and optimization technique.
Mechanical design of DNA nanostructures.
Castro, Carlos E; Su, Hai-Jun; Marras, Alexander E; Zhou, Lifeng; Johnson, Joshua
2015-04-14
Structural DNA nanotechnology is a rapidly emerging field that has demonstrated great potential for applications such as single molecule sensing, drug delivery, and templating molecular components. As the applications of DNA nanotechnology expand, a consideration of their mechanical behavior is becoming essential to understand how these structures will respond to physical interactions. This review considers three major avenues of recent progress in this area: (1) measuring and designing mechanical properties of DNA nanostructures, (2) designing complex nanostructures based on imposed mechanical stresses, and (3) designing and controlling structurally dynamic nanostructures. This work has laid the foundation for mechanically active nanomachines that can generate, transmit, and respond to physical cues in molecular systems.
Design considerations for mechanical snubbers
Severud, L.K.; Summers, G.D.
1980-03-01
The use of mechanical snubbers to restrain piping during an earthquake event is becoming more common in design of nuclear power plants. The design considerations and qualification procedures for mechanical snubbers used on the Fast Flux Test Facility will be presented. Design precautions and requirements for both normal operation and seismic operation are necessary. Effects of environmental vibration (nonseismic) induced through the piping by pump shaft imbalance and fluid flow oscillations will be addressed. Also, the snubber dynamic characteristics of interest to design and snubber design application considerations will be discussed.
A genetic algorithm for solving supply chain network design model
NASA Astrophysics Data System (ADS)
Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.
2013-09-01
Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.
In-Trail Procedure (ITP) Algorithm Design
NASA Technical Reports Server (NTRS)
Munoz, Cesar A.; Siminiceanu, Radu I.
2007-01-01
The primary objective of this document is to provide a detailed description of the In-Trail Procedure (ITP) algorithm, which is part of the Airborne Traffic Situational Awareness In-Trail Procedure (ATSA-ITP) application. To this end, the document presents a high level description of the ITP Algorithm and a prototype implementation of this algorithm in the programming language C.
Organization mechanism and counting algorithm on vertex-cover solutions
NASA Astrophysics Data System (ADS)
Wei, Wei; Zhang, Renquan; Niu, Baolong; Guo, Binghui; Zheng, Zhiming
2015-04-01
Counting the solution number of combinational optimization problems is an important topic in the study of computational complexity, which is concerned with Vertex-Cover in this paper. First, we investigate organizations of Vertex-Cover solution spaces by the underlying connectivity of unfrozen vertices and provide facts on the global and local environment. Then, a Vertex-Cover Solution Number Counting Algorithm is proposed and its complexity analysis is provided, the results of which fit very well with the simulations and have a better performance than those by 1-RSB in the neighborhood of c = e for random graphs. Based on the algorithm, variation and fluctuation on the solution number the statistics are studied to reveal the evolution mechanism of the solution numbers. Furthermore, the marginal probability distributions on the solution space are investigated on both the random graph and scale-free graph to illustrate the different evolution characteristics of their solution spaces. Thus, doing solution number counting based on the graph expression of the solution space should be an alternative and meaningful way to study the hardness of NP-complete and #P-complete problems and the appropriate algorithm design can help to achieve better approximations of solving combinational optimization problems and the corresponding counting problems.
Mechanical Design Handbook for Elastomers
NASA Technical Reports Server (NTRS)
Darlow, M.; Zorzi, E.
1986-01-01
Mechanical Design Handbook for Elastomers reviews state of art in elastomer-damper technology with particular emphasis on applications of highspeed rotor dampers. Self-contained reference but includes some theoretical discussion to help reader understand how and why dampers used for rotating machines. Handbook presents step-by-step procedure for design of elastomer dampers and detailed examples of actual elastomer damper applications.
Testing block subdivision algorithms on block designs
NASA Astrophysics Data System (ADS)
Wiseman, Natalie; Patterson, Zachary
2016-01-01
Integrated land use-transportation models predict future transportation demand taking into account how households and firms arrange themselves partly as a function of the transportation system. Recent integrated models require parcels as inputs and produce household and employment predictions at the parcel scale. Block subdivision algorithms automatically generate parcel patterns within blocks. Evaluating block subdivision algorithms is done by way of generating parcels and comparing them to those in a parcel database. Three block subdivision algorithms are evaluated on how closely they reproduce parcels of different block types found in a parcel database from Montreal, Canada. While the authors who developed each of the algorithms have evaluated them, they have used their own metrics and block types to evaluate their own algorithms. This makes it difficult to compare their strengths and weaknesses. The contribution of this paper is in resolving this difficulty with the aim of finding a better algorithm suited to subdividing each block type. The proposed hypothesis is that given the different approaches that block subdivision algorithms take, it's likely that different algorithms are better adapted to subdividing different block types. To test this, a standardized block type classification is used that consists of mutually exclusive and comprehensive categories. A statistical method is used for finding a better algorithm and the probability it will perform well for a given block type. Results suggest the oriented bounding box algorithm performs better for warped non-uniform sites, as well as gridiron and fragmented uniform sites. It also produces more similar parcel areas and widths. The Generalized Parcel Divider 1 algorithm performs better for gridiron non-uniform sites. The Straight Skeleton algorithm performs better for loop and lollipop networks as well as fragmented non-uniform and warped uniform sites. It also produces more similar parcel shapes and patterns.
HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN
While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...
HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN
While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...
The statistical mechanics of constructive algorithms
NASA Astrophysics Data System (ADS)
West, Ansgar H. L.; Saad, David
1998-11-01
The storage capacity of multilayer networks with overlapping receptive fields is studied for constructive algorithms using Boolean perceptrons as their basic building block which have been investigated within a replica framework. The assumption of weak coupling between subsequently constructed perceptrons is verified within a replica symmetric (RS) ansatz and shown to be negligible in most cases in comparison with correction due to replica symmetry breaking (RSB) in individual perceptrons. The capacities of a tiling-like and variants of the upstart algorithm are then calculated within RS and one-step RSB with the quenched average taken over the individual units separately for networks with up to K = 4000 and K = 600 units respectively. Within this treatment, the storage capacity 0305-4470/31/45/002/img6 seems to exhibit a power-law behaviour in 0305-4470/31/45/002/img7 with an exponent n that may depend on the algorithm and the stability. However, due to finite size effects in K reliable estimates of n could not be extracted. Nevertheless, the results strongly indicate that n should be strictly smaller than 1 within one-step RSB, whereas within RS the Mitchison-Durbin bound is violated for finite K and n>1 may hold asymptotically.
Boiler-turbine control system design using a genetic algorithm
Dimeo, R.; Lee, K.Y.
1995-12-01
This paper discusses the application of a genetic algorithm to control system design for a boiler-turbine plant. In particular the authors study the ability of the genetic algorithm to develop a proportional-integral (PI) controller and a state feedback controller for a non-linear multi-input/multi-output (MIMO) plant model. The plant model is presented along with a discussion of the inherent difficulties in such controller development. A sketch of the genetic algorithm (GA) is presented and its strategy as a method of control system design is discussed. Results are presented for two different control systems that have been designed with the genetic algorithm.
Thalmann Algorithm Decompression Table Generation Software Design Document
2010-09-01
Decompression Table Generation Software Design Document Navy Experimental Diving Unit Author...TITLE (Include Security Classification) (U) THALMANN ALGORITHM DECOMPRESSION TABLE GENERATION SOFTWARE DESIGN DOCUMENT 12. PERSONAL AUTHOR(S...1 2. Decompression Table Generator (TBLP7R
Parallel optimization algorithms and their implementation in VLSI design
NASA Technical Reports Server (NTRS)
Lee, G.; Feeley, J. J.
1991-01-01
Two new parallel optimization algorithms based on the simplex method are described. They may be executed by a SIMD parallel processor architecture and be implemented in VLSI design. Several VLSI design implementations are introduced. An application example is reported to demonstrate that the algorithms are effective.
NASA Technical Reports Server (NTRS)
Roth, J. P.
1972-01-01
The following problems are considered: (1) methods for development of logic design together with algorithms, so that it is possible to compute a test for any failure in the logic design, if such a test exists, and developing algorithms and heuristics for the purpose of minimizing the computation for tests; and (2) a method of design of logic for ultra LSI (large scale integration). It was discovered that the so-called quantum calculus can be extended to render it possible: (1) to describe the functional behavior of a mechanism component by component, and (2) to compute tests for failures, in the mechanism, using the diagnosis algorithm. The development of an algorithm for the multioutput two-level minimization problem is presented and the program MIN 360 was written for this algorithm. The program has options of mode (exact minimum or various approximations), cost function, cost bound, etc., providing flexibility.
Optimal Pid Controller Design Using Adaptive Vurpso Algorithm
NASA Astrophysics Data System (ADS)
Zirkohi, Majid Moradi
2015-04-01
The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.
Optimum synthesis of a four-bar mechanism using the modified bacterial foraging algorithm
NASA Astrophysics Data System (ADS)
Mezura-Montes, Efrén; Portilla-Flores, Edgar A.; Hernández-Ocaña, Betania
2014-05-01
This paper presents the mechanical synthesis of a four-bar mechanism, its definition as a constrained optimisation problem in the presence of one dynamic constraint and its solution with a swarm intelligence algorithm based on the bacteria foraging process. The algorithm is adapted to solve the optimisation problem by adding a suitable constraint-handling technique that is able to incorporate a selection criterion for the two objectives stated by the kinematic analysis of the problem. Moreover, a diversity mechanism, coupled with the attractor operator used by bacteria, is designed to favour the exploration of the search space. Four experiments are designed to validate the proposed model and to test the performance of the algorithm regarding constraint-satisfaction, sub-optimal solutions obtained, performance metrics and an analysis of the solutions based on the simulation of the four-bar mechanism. The results are compared with those provided by four algorithms found in the specialised literature used to solve mechanical design problems. On the basis of the simulation analysis, the solutions obtained by the proposed algorithm lead to a more suitable design based on motion generation and operation quality.
Design of Quantum Algorithms Using Physics Tools
2014-06-02
Farhi, David Gosset, Itay Hen, A. W. Sandvik, Peter Shor, A. P. Young, Francesco Zamponi. Performance of the quantum adiabatic algorithm on random...wider community. Some of the research highlights are outlined below. In joint work with David Gosset, Itay Hen, Anders Sandvik, Peter Young
Robust Algorithms for Penetration Mechanics Problems
1998-02-01
strain rate and studied a purely mechanical problem. Recht26 has adapted the Taylor27 model of mushrooming to the situation in which the penetrator...for tungsten. However, when either the shear modulus for the tungsten block was artificially changed to that for the uranium block, or the defects ...the intense deformations of the rod in the mushroomed region. Computed results for a trial problem indicated that the height of the mushroomed
Theory and Algorithms for Global/Local Design Optimization
2005-09-29
algorithm with memory for optimal design of laminated sandwich composite panels ", Composite Structures, 58 (2002) 513-520. V. B. Gantovnik, Z. Giirdal, L...34, AIAA J., 43 (2005) 1844-1849. D. B. Adams, L. T. Watson, and Z. Gilrdal, " Optimization and blending of composite laminates using genetic algorithms ...Anderson-Cook, " Genetic algorithm optimization and blending of composite laminates by locally
Genetic Algorithms as a Tool for Phased Array Radar Design
2002-06-01
NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS Approved for public release; distribution is unlimited. GENETIC ALGORITHMS AS A...REPORT DATE June 2002 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE: Genetic Algorithms as a Tool for Phased Array Radar...creative ways to design multi-function phased array radars. This thesis proposes that Genetic Algorithms, computer programs that mimic natural selection
Extrapolated gradientlike algorithms for molecular dynamics and celestial mechanics simulations.
Omelyan, I P
2006-09-01
A class of symplectic algorithms is introduced to integrate the equations of motion in many-body systems. The algorithms are derived on the basis of an advanced gradientlike decomposition approach. Its main advantage over the standard gradient scheme is the avoidance of time-consuming evaluations of force gradients by force extrapolation without any loss of precision. As a result, the efficiency of the integration improves significantly. The algorithms obtained are analyzed and optimized using an error-function theory. The best among them are tested in actual molecular dynamics and celestial mechanics simulations for comparison with well-known nongradient and gradient algorithms such as the Störmer-Verlet, Runge-Kutta, Cowell-Numerov, Forest-Ruth, Suzuki-Chin, and others. It is demonstrated that for moderate and high accuracy, the extrapolated algorithms should be considered as the most efficient for the integration of motion in molecular dynamics simulations.
Graph-drawing algorithms geometries versus molecular mechanics in fullereness
NASA Astrophysics Data System (ADS)
Kaufman, M.; Pisanski, T.; Lukman, D.; Borštnik, B.; Graovac, A.
1996-09-01
The algorithms of Kamada-Kawai (KK) and Fruchterman-Reingold (FR) have been recently generalized (Pisanski et al., Croat. Chem. Acta 68 (1995) 283) in order to draw molecular graphs in three-dimensional space. The quality of KK and FR geometries is studied here by comparing them with the molecular mechanics (MM) and the adjacency matrix eigenvectors (AME) algorithm geometries. In order to compare different layouts of the same molecule, an appropriate method has been developed. Its application to a series of experimentally detected fullerenes indicates that the KK, FR and AME algorithms are able to reproduce plausible molecular geometries.
Algorithm for Designing Nanoscale Supramolecular Therapeutics with Increased Anticancer Efficacy.
Kulkarni, Ashish; Pandey, Prithvi; Rao, Poornima; Mahmoud, Ayaat; Goldman, Aaron; Sabbisetti, Venkata; Parcha, Shashikanth; Natarajan, Siva Kumar; Chandrasekar, Vineethkrishna; Dinulescu, Daniela; Roy, Sudip; Sengupta, Shiladitya
2016-09-27
In the chemical world, evolution is mirrored in the origin of nanoscale supramolecular structures from molecular subunits. The complexity of function acquired in a supramolecular system over a molecular subunit can be harnessed in the treatment of cancer. However, the design of supramolecular nanostructures is hindered by a limited atomistic level understanding of interactions between building blocks. Here, we report the development of a computational algorithm, which we term Volvox after the first multicellular organism, that sequentially integrates quantum mechanical energy-state- and force-field-based models with large-scale all-atomistic explicit water molecular dynamics simulations to design stable nanoscale lipidic supramolecular structures. In one example, we demonstrate that Volvox enables the design of a nanoscale taxane supramolecular therapeutic. In another example, we demonstrate that Volvox can be extended to optimizing the ratio of excipients to form a stable nanoscale supramolecular therapeutic. The nanoscale taxane supramolecular therapeutic exerts greater antitumor efficacy than a clinically used taxane in vivo. Volvox can emerge as a powerful tool in the design of nanoscale supramolecular therapeutics for effective treatment of cancer.
A generalized algorithm to design finite field normal basis multipliers
NASA Technical Reports Server (NTRS)
Wang, C. C.
1986-01-01
Finite field arithmetic logic is central in the implementation of some error-correcting coders and some cryptographic devices. There is a need for good multiplication algorithms which can be easily realized. Massey and Omura recently developed a new multiplication algorithm for finite fields based on a normal basis representation. Using the normal basis representation, the design of the finite field multiplier is simple and regular. The fundamental design of the Massey-Omura multiplier is based on a design of a product function. In this article, a generalized algorithm to locate a normal basis in a field is first presented. Using this normal basis, an algorithm to construct the product function is then developed. This design does not depend on particular characteristics of the generator polynomial of the field.
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
NASA Technical Reports Server (NTRS)
Lohn, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris; Norvig, Peter (Technical Monitor)
2000-01-01
We describe a parallel genetic algorithm (GA) that automatically generates circuit designs using evolutionary search. A circuit-construction programming language is introduced and we show how evolution can generate practical analog circuit designs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. We present experimental results as applied to analog filter and amplifier design tasks.
The GRAVITY spectrometers: mechanical design
NASA Astrophysics Data System (ADS)
Fischer, Sebastian; Wiest, Michael; Straubmeier, Christian; Yazici, Senol; Araujo-Hauck, Constanza; Eisenhauer, Frank; Perrin, Guy; Brandner, Wolfgang; Perraut, Karine; Amorim, Antonio; Schöller, Markus; Eckart, Andreas
2010-07-01
Operating on 6 interferometric baselines, i.e. using all 4 UTs, the 2nd generation VLTI instrument GRAVITY will deliver narrow angle astrometry with 10μas accuracy at the infrared K-band. Within the international GRAVITY consortium, the Cologne institute is responsible for the development and construction of the two spectrometers: one for the science object, and one for the fringe tracking object. Optically two individual components, both spectrometers are two separate units with their own housing and interfaces inside the vacuum vessel of GRAVITY. The general design of the spectrometers, however, is similar. The optical layout is separated into beam collimator (with integrated optics and metrology laser injection) and camera system (with detector, dispersive element, & Wollaston filter wheel). Mechanically, this transfers to two regions which are separated by a solid baffle wall incorporating the blocking filter for the metrology Laser wavelength. The optical subunits are mounted in individual rigid tubes which pay respect to the individual shape, size and thermal expansion of the lenses. For a minimized thermal background, the spectrometers are actively cooled down to an operating temperature of 80K in the ambient temperature environment of the GRAVITY vacuum dewar. The integrated optics beam combiner and the metrology laser injection, which are operated at 200/240K, are mounted thermally isolated to the cold housing of the spectrometers. The optical design has shown that the alignment of the detector is crucial to the performance of the spectrometers. Therefore, in addition to four wheel mechanisms, six cryogenic positioning mechanisms are included in the mechanical design of the detector mount.
An algorithm for optimal structural design with frequency constraints
NASA Technical Reports Server (NTRS)
Kiusalaas, J.; Shaw, R. C. J.
1978-01-01
The paper presents a finite element method for minimum weight design of structures with lower-bound constraints on the natural frequencies, and upper and lower bounds on the design variables. The design algorithm is essentially an iterative solution of the Kuhn-Tucker optimality criterion. The three most important features of the algorithm are: (1) a small number of design iterations are needed to reach optimal or near-optimal design, (2) structural elements with a wide variety of size-stiffness may be used, the only significant restriction being the exclusion of curved beam and shell elements, and (3) the algorithm will work for multiple as well as single frequency constraints. The design procedure is illustrated with three simple problems.
Mechanical flexible joint design document
NASA Technical Reports Server (NTRS)
Daily, Vic
1993-01-01
The purpose of this report is to document the status of the Mechanical Flexible Joint (MFJ) Design Subtask with the intent of halting work on the design. Recommendations for future work is included in the case that the task is to be resumed. The MFJ is designed to eliminate two failure points from the current flex joint configuration, the inner 'tripod configuration' and the outer containment jacket. The MFJ will also be designed to flex 13.5 degrees and have three degrees of freedom. By having three degrees of freedom, the MFJ will allow the Low Pressure Fuel Duct to twist and remove the necessity to angulate the full 11 degrees currently required. The current flex joints are very labor intensive and very costly and a simple alternative is being sought. The MFJ is designed with a greater angular displacement, with three degrees of freedom, to reside in the same overall envelope, to meet weight constraints of the current bellows, to be compatible with cryogenic fuel and oxidizers, and also to be man-rated.
Computational Aspects of Realization & Design Algorithms in Linear Systems Theory.
NASA Astrophysics Data System (ADS)
Tsui, Chia-Chi
Realization and design problems are two major problems in linear time-invariant systems control theory and have been solved theoretically. However, little is understood about their numerical properties. Due to the large scale of the problem and the finite precision of computer computation, it is very important and is the purpose of this study to investigate the computational reliability and efficiency of the algorithms for these two problems. In this dissertation, a reliable algorithm to achieve canonical form realization via Hankel matrix is developed. A comparative study of three general realization algorithms, for both numerical reliability and efficiency, shows that the proposed algorithm (via Hankel matrix) is the most preferable one among the three. The design problems, such as the state feedback design for pole placement, the state observer design, and the low order single and multi-functional observer design, have been solved by using canonical form systems matrices. In this dissertation, a set of algorithms for solving these three design problems is developed and analysed. These algorithms are based on Hessenberg form systems matrices which are numerically more reliable to compute than the canonical form systems matrices.
AutoGrow: A Novel Algorithm for Protein Inhibitor Design
Durrant, Jacob; Amaro, Rommie E.; McCammon, J. Andrew
2009-01-01
Due in part to the increasing availability of crystallographic protein structures as well as rapid improvements in computing power, the past few decades have seen an explosion in the field of computer-based rational drug design. Several algorithms have been developed to identify or generate potential ligands in silico by optimizing the ligand-receptor hydrogen bond, electrostatic, and hydrophobic interactions. We here present AutoGrow, a novel computer-aided drug design algorithm that combines the strengths of both fragment-based growing and docking algorithms. To validate AutoGrow, we recreate three crystallographically resolved ligands from their constituent fragments. PMID:19207419
A computerized compensator design algorithm with launch vehicle applications
NASA Technical Reports Server (NTRS)
Mitchell, J. R.; Mcdaniel, W. L., Jr.
1976-01-01
This short paper presents a computerized algorithm for the design of compensators for large launch vehicles. The algorithm is applicable to the design of compensators for linear, time-invariant, control systems with a plant possessing a single control input and multioutputs. The achievement of frequency response specifications is cast into a strict constraint mathematical programming format. An improved solution algorithm for solving this type of problem is given, along with the mathematical necessities for application to systems of the above type. A computer program, compensator improvement program (CIP), has been developed and applied to a pragmatic space-industry-related example.
Genetic algorithms for the construction of D-optimal designs
Heredia-Langner, Alejandro; Carlyle, W M.; Montgomery, D C.; Borror, Connie M.; Runger, George C.
2003-01-01
Computer-generated designs are useful for situations where standard factorial, fractional factorial or response surface designs cannot be easily employed. Alphabetically-optimal designs are the most widely used type of computer-generated designs, and of these, the D-optimal (or D-efficient) class of designs are extremely popular. D-optimal designs are usually constructed by algorithms that sequentially add and delete points from a potential design based using a candidate set of points spaced over the region of interest. We present a technique to generate D-efficient designs using genetic algorithms (GA). This approach eliminates the need to explicitly consider a candidate set of experimental points and it can handle highly constrained regions while maintaining a level of performance comparable to more traditional design construction techniques.
Algorithme intelligent d'optimisation d'un design structurel de grande envergure
NASA Astrophysics Data System (ADS)
Dominique, Stephane
The implementation of an automated decision support system in the field of design and structural optimisation can give a significant advantage to any industry working on mechanical designs. Indeed, by providing solution ideas to a designer or by upgrading existing design solutions while the designer is not at work, the system may reduce the project cycle time, or allow more time to produce a better design. This thesis presents a new approach to automate a design process based on Case-Based Reasoning (CBR), in combination with a new genetic algorithm named Genetic Algorithm with Territorial core Evolution (GATE). This approach was developed in order to reduce the operating cost of the process. However, as the system implementation cost is quite expensive, the approach is better suited for large scale design problem, and particularly for design problems that the designer plans to solve for many different specification sets. First, the CBR process uses a databank filled with every known solution to similar design problems. Then, the closest solutions to the current problem in term of specifications are selected. After this, during the adaptation phase, an artificial neural network (ANN) interpolates amongst known solutions to produce an additional solution to the current problem using the current specifications as inputs. Each solution produced and selected by the CBR is then used to initialize the population of an island of the genetic algorithm. The algorithm will optimise the solution further during the refinement phase. Using progressive refinement, the algorithm starts using only the most important variables for the problem. Then, as the optimisation progress, the remaining variables are gradually introduced, layer by layer. The genetic algorithm that is used is a new algorithm specifically created during this thesis to solve optimisation problems from the field of mechanical device structural design. The algorithm is named GATE, and is essentially a real number
Li, Wei
2017-01-01
Computational scientists have designed many useful algorithms by exploring a biological process or imitating natural evolution. These algorithms can be used to solve engineering optimization problems. Inspired by the change of matter state, we proposed a novel optimization algorithm called differential cloud particles evolution algorithm based on data-driven mechanism (CPDD). In the proposed algorithm, the optimization process is divided into two stages, namely, fluid stage and solid stage. The algorithm carries out the strategy of integrating global exploration with local exploitation in fluid stage. Furthermore, local exploitation is carried out mainly in solid stage. The quality of the solution and the efficiency of the search are influenced greatly by the control parameters. Therefore, the data-driven mechanism is designed for obtaining better control parameters to ensure good performance on numerical benchmark problems. In order to verify the effectiveness of CPDD, numerical experiments are carried out on all the CEC2014 contest benchmark functions. Finally, two application problems of artificial neural network are examined. The experimental results show that CPDD is competitive with respect to other eight state-of-the-art intelligent optimization algorithms.
2017-01-01
Computational scientists have designed many useful algorithms by exploring a biological process or imitating natural evolution. These algorithms can be used to solve engineering optimization problems. Inspired by the change of matter state, we proposed a novel optimization algorithm called differential cloud particles evolution algorithm based on data-driven mechanism (CPDD). In the proposed algorithm, the optimization process is divided into two stages, namely, fluid stage and solid stage. The algorithm carries out the strategy of integrating global exploration with local exploitation in fluid stage. Furthermore, local exploitation is carried out mainly in solid stage. The quality of the solution and the efficiency of the search are influenced greatly by the control parameters. Therefore, the data-driven mechanism is designed for obtaining better control parameters to ensure good performance on numerical benchmark problems. In order to verify the effectiveness of CPDD, numerical experiments are carried out on all the CEC2014 contest benchmark functions. Finally, two application problems of artificial neural network are examined. The experimental results show that CPDD is competitive with respect to other eight state-of-the-art intelligent optimization algorithms. PMID:28761438
Evaluation of Mechanical Losses in Piezoelectric Plates using Genetic algorithm
NASA Astrophysics Data System (ADS)
Arnold, F. J.; Gonçalves, M. S.; Massaro, F. R.; Martins, P. S.
Numerical methods are used for the characterization of piezoelectric ceramics. A procedure based on genetic algorithm is applied to find the physical coefficients and mechanical losses. The coefficients are estimated from a minimum scoring of cost function. Electric impedances are calculated from Mason's model including mechanical losses constant and dependent on frequency as a linear function. The results show that the electric impedance percentage error in the investigated interval of frequencies decreases when mechanical losses depending on frequency are inserted in the model. A more accurate characterization of the piezoelectric ceramics mechanical losses should be considered as frequency dependent.
An algorithm for design of beam compensators.
Renner, W D; O'Connor, T P; Bermudez, N M
1989-07-01
Beam compensators are optimally designed to give a uniform dose to any plane or midsurface that intersects a single beam, or to give a uniform dose to the volume defined by the intersection of two or more beams. The primary and scatter components are taken into account separately, as well as the patient's shape and internal heterogeneities. The design of the beam compensators is formulated as a linear programming problem and solved with a variation of the Simplex Method. Beam weighting factors are also obtained as part of the solution.
Neural-Network-Biased Genetic Algorithms for Materials Design: Evolutionary Algorithms That Learn.
Patra, Tarak K; Meenakshisundaram, Venkatesh; Hung, Jui-Hsiang; Simmons, David S
2017-02-13
Machine learning has the potential to dramatically accelerate high-throughput approaches to materials design, as demonstrated by successes in biomolecular design and hard materials design. However, in the search for new soft materials exhibiting properties and performance beyond those previously achieved, machine learning approaches are frequently limited by two shortcomings. First, because they are intrinsically interpolative, they are better suited to the optimization of properties within the known range of accessible behavior than to the discovery of new materials with extremal behavior. Second, they require large pre-existing data sets, which are frequently unavailable and prohibitively expensive to produce. Here we describe a new strategy, the neural-network-biased genetic algorithm (NBGA), for combining genetic algorithms, machine learning, and high-throughput computation or experiment to discover materials with extremal properties in the absence of pre-existing data. Within this strategy, predictions from a progressively constructed artificial neural network are employed to bias the evolution of a genetic algorithm, with fitness evaluations performed via direct simulation or experiment. In effect, this strategy gives the evolutionary algorithm the ability to "learn" and draw inferences from its experience to accelerate the evolutionary process. We test this algorithm against several standard optimization problems and polymer design problems and demonstrate that it matches and typically exceeds the efficiency and reproducibility of standard approaches including a direct-evaluation genetic algorithm and a neural-network-evaluated genetic algorithm. The success of this algorithm in a range of test problems indicates that the NBGA provides a robust strategy for employing informatics-accelerated high-throughput methods to accelerate materials design in the absence of pre-existing data.
Designing robust control laws using genetic algorithms
NASA Technical Reports Server (NTRS)
Marrison, Chris
1994-01-01
The purpose of this research is to create a method of finding practical, robust control laws. The robustness of a controller is judged by Stochastic Robustness metrics and the level of robustness is optimized by searching for design parameters that minimize a robustness cost function.
Acoustic design of rotor blades using a genetic algorithm
NASA Technical Reports Server (NTRS)
Wells, V. L.; Han, A. Y.; Crossley, W. A.
1995-01-01
A genetic algorithm coupled with a simplified acoustic analysis was used to generate low-noise rotor blade designs. The model includes thickness, steady loading and blade-vortex interaction noise estimates. The paper presents solutions for several variations in the fitness function, including thickness noise only, loading noise only, and combinations of the noise types. Preliminary results indicate that the analysis provides reasonable assessments of the noise produced, and that genetic algorithm successfully searches for 'good' designs. The results show that, for a given required thrust coefficient, proper blade design can noticeably reduce the noise produced at some expense to the power requirements.
Acoustic design of rotor blades using a genetic algorithm
NASA Technical Reports Server (NTRS)
Wells, V. L.; Han, A. Y.; Crossley, W. A.
1995-01-01
A genetic algorithm coupled with a simplified acoustic analysis was used to generate low-noise rotor blade designs. The model includes thickness, steady loading and blade-vortex interaction noise estimates. The paper presents solutions for several variations in the fitness function, including thickness noise only, loading noise only, and combinations of the noise types. Preliminary results indicate that the analysis provides reasonable assessments of the noise produced, and that genetic algorithm successfully searches for 'good' designs. The results show that, for a given required thrust coefficient, proper blade design can noticeably reduce the noise produced at some expense to the power requirements.
An Analysis of Algorithmic Processes and Instructional Design.
ERIC Educational Resources Information Center
Schmid, Richard F.; Gerlach, Vernon S.
1986-01-01
Describes algorithms and shows how they can be applied to the design of instructional systems by relating them to a standard information processing model. Two studies are briefly described which tested serial and parallel processing in learning and offered guidelines for designers. Future research needs are also discussed. (LRW)
Optimal fractional order PID design via Tabu Search based algorithm.
Ateş, Abdullah; Yeroglu, Celaleddin
2016-01-01
This paper presents an optimization method based on the Tabu Search Algorithm (TSA) to design a Fractional-Order Proportional-Integral-Derivative (FOPID) controller. All parameter computations of the FOPID employ random initial conditions, using the proposed optimization method. Illustrative examples demonstrate the performance of the proposed FOPID controller design method.
A strategy for quantum algorithm design assisted by machine learning
NASA Astrophysics Data System (ADS)
Bang, Jeongho; Ryu, Junghee; Yoo, Seokwon; Pawłowski, Marcin; Lee, Jinhyoung
2014-07-01
We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a ‘quantum student’ is being taught by a ‘classical teacher’. In other words, in our method, the learning system is supposed to evolve into a quantum algorithm for a given problem, assisted by a classical main-feedback system. Our method is applicable for designing quantum oracle-based algorithms. We chose, as a case study, an oracle decision problem, called a Deutsch-Jozsa problem. We showed by using Monte Carlo simulations that our simulator can faithfully learn a quantum algorithm for solving the problem for a given oracle. Remarkably, the learning time is proportional to the square root of the total number of parameters, rather than showing the exponential dependence found in the classical machine learning-based method.
Evolutionary algorithms applied to reliable communication network design
NASA Astrophysics Data System (ADS)
Nesmachnow, Sergio; Cancela, Hector; Alba, Enrique
2007-10-01
Several evolutionary algorithms (EAs) applied to a wide class of communication network design problems modelled under the generalized Steiner problem (GSP) are evaluated. In order to provide a fault-tolerant design, a solution to this problem consists of a preset number of independent paths linking each pair of potentially communicating terminal nodes. This usually requires considering intermediate non-terminal nodes (Steiner nodes), which are used to ensure path redundancy, while trying to minimize the overall cost. The GSP is an NP-hard problem for which few algorithms have been proposed. This article presents a comparative study of pure and hybrid EAs applied to the GSP, codified over MALLBA, a general purpose library for combinatorial optimization. The algorithms were tested on several GSPs, and asset efficient numerical results are reported for both serial and distributed models of the evaluated algorithms.
OPTIMUM MECHANICAL DESIGN SYNTHESIS. VOLUME I.
MECHANICAL ENGINEERING, EXPERIMENTAL DESIGN, SYNTHESIS , MECHANICAL DRAWING, OPTIMIZATION, STATE OF THE ART, REPORTS, DYNAMIC PROGRAMMING, CALCULUS OF VARIATIONS, SHOCK ABSORBERS, VIBRATION ISOLATORS.
An iterative algorithm combining model reduction and control design
NASA Technical Reports Server (NTRS)
Hsieh, C.; Kim, J. H.; Zhu, G.; Liu, K.; Skelton, R. E.
1990-01-01
A design strategy which integrates model reduction by modal cost analysis and a multiobjective controller design is proposed. The necessary modeling and control algorithms are easily programmed in Matlab standard software. Hence, this method is very practical for controller design for large space structures. The design algorithm also solves the very important problem of tuning multiple loop controllers (multi-input, multi-output, or MIMO). Instead of the single gain change that is used in standard root locus and gain and phase margin theories, this method tunes multiple loop controllers from low to high gain in a systematic way in the design procedure. This design strategy is applied to NASA's Mini-Mast system.
An iterative algorithm combining model reduction and control design
NASA Technical Reports Server (NTRS)
Hsieh, C.; Kim, J. H.; Zhu, G.; Liu, K.; Skelton, R. E.
1990-01-01
A design strategy which integrates model reduction by modal cost analysis and a multiobjective controller design is proposed. The necessary modeling and control algorithms are easily programmed in Matlab standard software. Hence, this method is very practical for controller design for large space structures. The design algorithm also solves the very important problem of tuning multiple loop controllers (multi-input, multi-output, or MIMO). Instead of the single gain change that is used in standard root locus and gain and phase margin theories, this method tunes multiple loop controllers from low to high gain in a systematic way in the design procedure. This design strategy is applied to NASA's Mini-Mast system.
Design of an acoustic metamaterial lens using genetic algorithms.
Li, Dennis; Zigoneanu, Lucian; Popa, Bogdan-Ioan; Cummer, Steven A
2012-10-01
The present work demonstrates a genetic algorithm approach to optimizing the effective material parameters of an acoustic metamaterial. The target device is an acoustic gradient index (GRIN) lens in air, which ideally possesses a maximized index of refraction, minimized frequency dependence of the material properties, and minimized acoustic impedance mismatch. Applying this algorithm results in complex designs with certain common features, and effective material properties that are better than those present in previous designs. After modifying the optimized unit cell designs to make them suitable for fabrication, a two-dimensional lens was built and experimentally tested. Its performance was in good agreement with simulations. Overall, the optimization approach was able to improve the refractive index but at the cost of increased frequency dependence. The optimal solutions found by the algorithm provide a numerical description of how the material parameters compete with one another and thus describes the level of performance achievable in the GRIN lens.
Microgel mechanics in biomaterial design.
Saxena, Shalini; Hansen, Caroline E; Lyon, L Andrew
2014-08-19
The field of polymeric biomaterials has received much attention in recent years due to its potential for enhancing the biocompatibility of systems and devices applied to drug delivery and tissue engineering. Such applications continually push the definition of biocompatibility from relatively straightforward issues such as cytotoxicity to significantly more complex processes such as reducing foreign body responses or even promoting/recapitulating natural body functions. Hydrogels and their colloidal analogues, microgels, have been and continue to be heavily investigated as viable materials for biological applications because they offer numerous, facile avenues in tailoring chemical and physical properties to approach biologically harmonious integration. Mechanical properties in particular are recently coming into focus as an important manner in which biological responses can be altered. In this Account, we trace how mechanical properties of microgels have moved into the spotlight of research efforts with the realization of their potential impact in biologically integrative systems. We discuss early experiments in our lab and in others focused on synthetic modulation of particle structure at a rudimentary level for fundamental drug delivery studies. These experiments elucidated that microgel mechanics are a consequence of polymer network distribution, which can be controlled by chemical composition or particle architecture. The degree of deformability designed into the microgel allows for a defined response to an imposed external force. We have studied deformation in packed colloidal phases and in translocation events through confined pores; in all circumstances, microgels exhibit impressive deformability in response to their environmental constraints. Microgels further translate their mechanical properties when assembled in films to the properties of the bulk material. In particular, microgel films have been a large focus in our lab as building blocks for self
Understanding Mechanical Design with Respect to Manufacturability
NASA Technical Reports Server (NTRS)
Mondell, Skyler
2010-01-01
At the NASA Prototype Development Laboratory in Kennedy Space Center, Fl, several projects concerning different areas of mechanical design were undertaken in order to better understand the relationship between mechanical design and manufacturabiIity. The assigned projects pertained specifically to the NASA Space Shuttle, Constellation, and Expendable Launch Vehicle programs. During the work term, mechanical design practices relating to manufacturing processes were learned and utilized in order to obtain an understanding of mechanical design with respect to manufacturability.
An optimal structural design algorithm using optimality criteria
NASA Technical Reports Server (NTRS)
Taylor, J. E.; Rossow, M. P.
1976-01-01
An algorithm for optimal design is given which incorporates several of the desirable features of both mathematical programming and optimality criteria, while avoiding some of the undesirable features. The algorithm proceeds by approaching the optimal solution through the solutions of an associated set of constrained optimal design problems. The solutions of the constrained problems are recognized at each stage through the application of optimality criteria based on energy concepts. Two examples are described in which the optimal member size and layout of a truss is predicted, given the joint locations and loads.
A robust Feasible Directions algorithm for design synthesis
NASA Technical Reports Server (NTRS)
Vanderplaats, G. N.
1983-01-01
A nonlinear optimization algorithm is developed which combines the best features of the Method of Feasible Directions and the Generalized Reduced Gradient Method. This algorithm utilizes the direction-finding sub-problem from the Method of Feasible Directions to find a search direction which is equivalent to that of the Generalized Reduced Gradient Method, but does not require the addition of a large number of slack variables associated with inequality constraints. This method provides a core-efficient algorithm for the solution of optimization problems with a large number of inequality constraints. Further optimization efficiency is derived by introducing the concept of infrequent gradient calculations. In addition, it is found that the sensitivity of the optimum design to changes in the problem parameters can be obtained using this method without the need for second derivatives or Lagrange multipliers. A numerical example is given in order to demonstrate the efficiency of the algorithm and the sensitivity analysis.
Design and analysis of Galileo sun acquisition algorithm
NASA Technical Reports Server (NTRS)
Lin, H.-S.
1981-01-01
The Galileo sun acquisition algorithm is used to align the spacecraft antenna with the sun in order to determine spacecraft attitude. It is also used to estimate the spin rate when the spacecraft antenna is not sun oriented, and is capable of performing a rhumb line turn maneuver in the case of two gyro failures. The design of the algorithm is presented in detail along with software implementation at the flowchart level. The six major portions of the algorithm are considered: initialization, sensor measurement mapping, path selection logic, sun detection logic, termination logic, and burn command generation. Analysis is performed to determine the major parameters of the algorithm, and results are verified by computer simulations.
Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms.
Garro, Beatriz A; Vázquez, Roberto A
2015-01-01
Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems.
Designing Artificial Neural Networks Using Particle Swarm Optimization Algorithms
Vázquez, Roberto A.
2015-01-01
Artificial Neural Network (ANN) design is a complex task because its performance depends on the architecture, the selected transfer function, and the learning algorithm used to train the set of synaptic weights. In this paper we present a methodology that automatically designs an ANN using particle swarm optimization algorithms such as Basic Particle Swarm Optimization (PSO), Second Generation of Particle Swarm Optimization (SGPSO), and a New Model of PSO called NMPSO. The aim of these algorithms is to evolve, at the same time, the three principal components of an ANN: the set of synaptic weights, the connections or architecture, and the transfer functions for each neuron. Eight different fitness functions were proposed to evaluate the fitness of each solution and find the best design. These functions are based on the mean square error (MSE) and the classification error (CER) and implement a strategy to avoid overtraining and to reduce the number of connections in the ANN. In addition, the ANN designed with the proposed methodology is compared with those designed manually using the well-known Back-Propagation and Levenberg-Marquardt Learning Algorithms. Finally, the accuracy of the method is tested with different nonlinear pattern classification problems. PMID:26221132
Non-Algorithmic Issues in Automated Computational Mechanics
1991-04-30
appby-is the A-p adaptive methodL Te advantiap of this approa& is that while the com tional FE’s can provide only I algebraic rates o covegence, an...be generally superior to the others. Thus, proper selection of the algorithm for a specific problem can yield better results, often with less...usually analyzed by the finite element method (or any other numerical method). This stage of the design process usually, amounts to massive algebraic
A superlinear interior points algorithm for engineering design optimization
NASA Technical Reports Server (NTRS)
Herskovits, J.; Asquier, J.
1990-01-01
We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.
Design of synthetic biological logic circuits based on evolutionary algorithm.
Chuang, Chia-Hua; Lin, Chun-Liang; Chang, Yen-Chang; Jennawasin, Tanagorn; Chen, Po-Kuei
2013-08-01
The construction of an artificial biological logic circuit using systematic strategy is recognised as one of the most important topics for the development of synthetic biology. In this study, a real-structured genetic algorithm (RSGA), which combines general advantages of the traditional real genetic algorithm with those of the structured genetic algorithm, is proposed to deal with the biological logic circuit design problem. A general model with the cis-regulatory input function and appropriate promoter activity functions is proposed to synthesise a wide variety of fundamental logic gates such as NOT, Buffer, AND, OR, NAND, NOR and XOR. The results obtained can be extended to synthesise advanced combinational and sequential logic circuits by topologically distinct connections. The resulting optimal design of these logic gates and circuits are established via the RSGA. The in silico computer-based modelling technology has been verified showing its great advantages in the purpose.
Distributed genetic algorithms for the floorplan design problem
NASA Technical Reports Server (NTRS)
Cohoon, James P.; Hegde, Shailesh U.; Martin, Worthy N.; Richards, Dana S.
1991-01-01
Designing a VLSI floorplan calls for arranging a given set of modules in the plane to minimize the weighted sum of area and wire-length measures. A method of solving the floorplan design problem using distributed genetic algorithms is presented. Distributed genetic algorithms, based on the paleontological theory of punctuated equilibria, offer a conceptual modification to the traditional genetic algorithms. Experimental results on several problem instances demonstrate the efficacy of this method and indicate the advantages of this method over other methods, such as simulated annealing. The method has performed better than the simulated annealing approach, both in terms of the average cost of the solutions found and the best-found solution, in almost all the problem instances tried.
OSPREY: Protein Design with Ensembles, Flexibility, and Provable Algorithms
Gainza, Pablo; Roberts, Kyle E.; Georgiev, Ivelin; Lilien, Ryan H.; Keedy, Daniel A.; Chen, Cheng-Yu; Reza, Faisal; Anderson, Amy C.; Richardson, David C.; Richardson, Jane S.; Donald, Bruce R.
2013-01-01
Summary We have developed a suite of protein redesign algorithms that improves realistic in silico modeling of proteins. These algorithms are based on three characteristics that make them unique: (1) improved flexibility of the protein backbone, protein side chains, and ligand to accurately capture the conformational changes that are induced by mutations to the protein sequence; (2) modeling of proteins and ligands as ensembles of low-energy structures to better approximate binding affinity; and (3) a globally-optimal protein design search, guaranteeing that the computational predictions are optimal with respect to the input model. Here, we illustrate the importance of these three characteristics. We then describe OSPREY, a protein redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental validation, in several biomedically-relevant settings. We show in detail how OSPREY has been used to predict resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application. PMID:23422427
Design of Automatic Extraction Algorithm of Knowledge Points for MOOCs
Chen, Haijian; Han, Dongmei; Zhao, Lina
2015-01-01
In recent years, Massive Open Online Courses (MOOCs) are very popular among college students and have a powerful impact on academic institutions. In the MOOCs environment, knowledge discovery and knowledge sharing are very important, which currently are often achieved by ontology techniques. In building ontology, automatic extraction technology is crucial. Because the general methods of text mining algorithm do not have obvious effect on online course, we designed automatic extracting course knowledge points (AECKP) algorithm for online course. It includes document classification, Chinese word segmentation, and POS tagging for each document. Vector Space Model (VSM) is used to calculate similarity and design the weight to optimize the TF-IDF algorithm output values, and the higher scores will be selected as knowledge points. Course documents of “C programming language” are selected for the experiment in this study. The results show that the proposed approach can achieve satisfactory accuracy rate and recall rate. PMID:26448738
Genetic Algorithm Design of a 3D Printed Heat Sink
Wu, Tong; Ozpineci, Burak; Ayers, Curtis William
2016-01-01
In this paper, a genetic algorithm- (GA-) based approach is discussed for designing heat sinks based on total heat generation and dissipation for a pre-specified size andshape. This approach combines random iteration processesand genetic algorithms with finite element analysis (FEA) to design the optimized heat sink. With an approach that prefers survival of the fittest , a more powerful heat sink can bedesigned which can cool power electronics more efficiently. Some of the resulting designs can only be 3D printed due totheir complexity. In addition to describing the methodology, this paper also includes comparisons of different cases to evaluate the performance of the newly designed heat sinkcompared to commercially available heat sinks.
The Conceptual Design Algorithm of Inland LNG Barges
NASA Astrophysics Data System (ADS)
Łozowicka, Dorota; Kaup, Magdalena
2017-03-01
The article concerns the problem of inland waterways transport of LNG. Its aim is to present the algorithm of conceptual design of inland barges for LNG transport, intended for exploitation on European waterways. The article describes the areas where LNG barges exist, depending on the allowable operating parameters on the waterways. It presents existing architectural and construction solutions of barges for inland LNG transport, as well as the necessary equipment, due to the nature of cargo. Then the article presents the procedure of the conceptual design of LNG barges, including navigation restrictions and functional and economic criteria. The conceptual design algorithm of LGN barges, presented in the article, allows to preliminary design calculations, on the basis of which, are obtained the main dimensions and parameters of unit, depending on the transport task and the class of inland waterways, on which the transport will be realized.
Design of PID-type controllers using multiobjective genetic algorithms.
Herreros, Alberto; Baeyens, Enrique; Perán, José R
2002-10-01
The design of a PID controller is a multiobjective problem. A plant and a set of specifications to be satisfied are given. The designer has to adjust the parameters of the PID controller such that the feedback interconnection of the plant and the controller satisfies the specifications. These specifications are usually competitive and any acceptable solution requires a tradeoff among them. An approach for adjusting the parameters of a PID controller based on multiobjective optimization and genetic algorithms is presented in this paper. The MRCD (multiobjective robust control design) genetic algorithm has been employed. The approach can be easily generalized to design multivariable coupled and decentralized PID loops and has been successfully validated for a large number of experimental cases.
Designing an Algorithm Animation System To Support Instructional Tasks.
ERIC Educational Resources Information Center
Hamilton-Taylor, Ashley George; Kraemer, Eileen
2002-01-01
The authors are conducting a study of instructors teaching data structure and algorithm topics, with a focus on the use of diagrams and tracing. The results of this study are being used to inform the design of the Support Kit for Animation (SKA). This article describes a preliminary version of SKA, and possible usage scenarios. (Author/AEF)
USING GENETIC ALGORITHMS TO DESIGN ENVIRONMENTALLY FRIENDLY PROCESSES
Genetic algorithm calculations are applied to the design of chemical processes to achieve improvements in environmental and economic performance. By finding the set of Pareto (i.e., non-dominated) solutions one can see how different objectives, such as environmental and economic ...
USING GENETIC ALGORITHMS TO DESIGN ENVIRONMENTALLY FRIENDLY PROCESSES
Genetic algorithm calculations are applied to the design of chemical processes to achieve improvements in environmental and economic performance. By finding the set of Pareto (i.e., non-dominated) solutions one can see how different objectives, such as environmental and economic ...
Synthesis design of artificial magnetic metamaterials using a genetic algorithm.
Chen, P Y; Chen, C H; Wang, H; Tsai, J H; Ni, W X
2008-08-18
In this article, we present a genetic algorithm (GA) as one branch of artificial intelligence (AI) for the optimization-design of the artificial magnetic metamaterial whose structure is automatically generated by computer through the filling element methodology. A representative design example, metamaterials with permeability of negative unity, is investigated and the optimized structures found by the GA are presented. It is also demonstrated that our approach is effective for the synthesis of functional magnetic and electric metamaterials with optimal structures. This GA-based optimization-design technique shows great versatility and applicability in the design of functional metamaterials.
Specific PCR product primer design using memetic algorithm.
Yang, Cheng-Hong; Cheng, Yu-Huei; Chuang, Li-Yeh; Chang, Hsueh-Wei
2009-01-01
To provide feasible primer sets for performing a polymerase chain reaction (PCR) experiment, many primer design methods have been proposed. However, the majority of these methods require a relatively long time to obtain an optimal solution since large quantities of template DNA need to be analyzed. Furthermore, the designed primer sets usually do not provide a specific PCR product size. In recent years, evolutionary computation has been applied to PCR primer design and yielded promising results. In this article, a memetic algorithm (MA) is proposed to solve primer design problems associated with providing a specific product size for PCR experiments. The MA is compared with a genetic algorithm (GA) using an accuracy formula to estimate the quality of the primer design and test the running time. Overall, 50 accession nucleotide sequences were sampled for the comparison of the accuracy of the GA and MA for primer design. Five hundred runs of the GA and MA primer design were performed with PCR product lengths of 150-300 bps and 500-800 bps, and two different methods of calculating T(m) for each accession nucleotide sequence were tested. A comparison of the accuracy results for the GA and MA primer design showed that the MA primer design yielded better results than the GA primer design. The results further indicate that the proposed method finds optimal or near-optimal primer sets and effective PCR products in a dry dock experiment. Related materials are available online at http://bio.kuas.edu.tw/ma-pd/.
Optical design with the aid of a genetic algorithm.
van Leijenhorst, D C; Lucasius, C B; Thijssen, J M
1996-01-01
Natural evolution is widely accepted as being the process underlying the design and optimization of the sensory functions of biological organisms. Using a genetic algorithm, this process is extended to the automatic optimization and design of optical systems, e.g. as used in astronomical telescopes. The results of this feasibility study indicate that various types of aberrations can be corrected quickly and simultaneously, even on small computers.
Biologically inspired binaural hearing aid algorithms: Design principles and effectiveness
NASA Astrophysics Data System (ADS)
Feng, Albert
2002-05-01
Despite rapid advances in the sophistication of hearing aid technology and microelectronics, listening in noise remains problematic for people with hearing impairment. To solve this problem two algorithms were designed for use in binaural hearing aid systems. The signal processing strategies are based on principles in auditory physiology and psychophysics: (a) the location/extraction (L/E) binaural computational scheme determines the directions of source locations and cancels noise by applying a simple subtraction method over every frequency band; and (b) the frequency-domain minimum-variance (FMV) scheme extracts a target sound from a known direction amidst multiple interfering sound sources. Both algorithms were evaluated using standard metrics such as signal-to-noise-ratio gain and articulation index. Results were compared with those from conventional adaptive beam-forming algorithms. In free-field tests with multiple interfering sound sources our algorithms performed better than conventional algorithms. Preliminary intelligibility and speech reception results in multitalker environments showed gains for every listener with normal or impaired hearing when the signals were processed in real time with the FMV binaural hearing aid algorithm. [Work supported by NIH-NIDCD Grant No. R21DC04840 and the Beckman Institute.
Thermoluminescence curves simulation using genetic algorithm with factorial design
NASA Astrophysics Data System (ADS)
Popko, E. A.; Weinstein, I. A.
2016-05-01
The evolutionary approach is an effective optimization tool for numeric analysis of thermoluminescence (TL) processes to assess the microparameters of kinetic models and to determine its effects on the shape of TL peaks. In this paper, the procedure for tuning of genetic algorithm (GA) is presented. This approach is based on multifactorial experiment and allows choosing intrinsic mechanisms of evolutionary operators which provide the most efficient algorithm performance. The proposed method is tested by considering the “one trap-one recombination center” (OTOR) model as an example and advantages for approximation of experimental TL curves are shown.
Convolution kernel design and efficient algorithm for sampling density correction.
Johnson, Kenneth O; Pipe, James G
2009-02-01
Sampling density compensation is an important step in non-cartesian image reconstruction. One of the common techniques to determine weights that compensate for differences in sampling density involves a convolution. A new convolution kernel is designed for sampling density attempting to minimize the error in a fully reconstructed image. The resulting weights obtained using this new kernel are compared with various previous methods, showing a reduction in reconstruction error. A computationally efficient algorithm is also presented that facilitates the calculation of the convolution of finite kernels. Both the kernel and the algorithm are extended to 3D. Copyright 2009 Wiley-Liss, Inc.
A new collage steganographic algorithm using cartoon design
NASA Astrophysics Data System (ADS)
Yi, Shuang; Zhou, Yicong; Pun, Chi-Man; Chen, C. L. Philip
2014-02-01
Existing collage steganographic methods suffer from low payload of embedding messages. To improve the payload while providing a high level of security protection to messages, this paper introduces a new collage steganographic algorithm using cartoon design. It embeds messages into the least significant bits (LSBs) of color cartoon objects, applies different permutations to each object, and adds objects to a cartoon cover image to obtain the stego image. Computer simulations and comparisons demonstrate that the proposed algorithm shows significantly higher capacity of embedding messages compared with existing collage steganographic methods.
An Algorithm for the Mixed Transportation Network Design Problem.
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately.
An Algorithm for the Mixed Transportation Network Design Problem
Liu, Xinyu; Chen, Qun
2016-01-01
This paper proposes an optimization algorithm, the dimension-down iterative algorithm (DDIA), for solving a mixed transportation network design problem (MNDP), which is generally expressed as a mathematical programming with equilibrium constraint (MPEC). The upper level of the MNDP aims to optimize the network performance via both the expansion of the existing links and the addition of new candidate links, whereas the lower level is a traditional Wardrop user equilibrium (UE) problem. The idea of the proposed solution algorithm (DDIA) is to reduce the dimensions of the problem. A group of variables (discrete/continuous) is fixed to optimize another group of variables (continuous/discrete) alternately; then, the problem is transformed into solving a series of CNDPs (continuous network design problems) and DNDPs (discrete network design problems) repeatedly until the problem converges to the optimal solution. The advantage of the proposed algorithm is that its solution process is very simple and easy to apply. Numerical examples show that for the MNDP without budget constraint, the optimal solution can be found within a few iterations with DDIA. For the MNDP with budget constraint, however, the result depends on the selection of initial values, which leads to different optimal solutions (i.e., different local optimal solutions). Some thoughts are given on how to derive meaningful initial values, such as by considering the budgets of new and reconstruction projects separately. PMID:27626803
Exact and approximation algorithms for DNA tag set design.
Măndoiu, Ion I; Trincă, Dragoş
2006-04-01
In this paper, we propose new solution methods for designing tag sets for use in universal DNA arrays. First, we give integer linear programming formulations for two previous formalizations of the tag set design problem. We show that these formulations can be solved to optimality for problem instances of moderate size by using general purpose optimization packages and also give more scalable algorithms based on an approximation scheme for packing linear programs. Second, we note the benefits of periodic tags and establish an interesting connection between the tag design problem and the problem of packing the maximum number of vertex-disjoint directed cycles in a given graph. We show that combining a simple greedy cycle packing algorithm with a previously proposed alphabetic tree search strategy yields an increase of over 40% in the number of tags compared to previous methods.
Design of transonic airfoils and wings using a hybrid design algorithm
NASA Technical Reports Server (NTRS)
Campbell, Richard L.; Smith, Leigh A.
1987-01-01
A method has been developed for designing airfoils and wings at transonic speeds. It utilizes a hybrid design algorithm in an iterative predictor/corrector approach, alternating between analysis code and a design module. This method has been successfully applied to a variety of airfoil and wing design problems, including both transport and highly-swept fighter wing configurations. An efficient approach to viscous airfoild design and the effect of including static aeroelastic deflections in the wing design process are also illustrated.
Martinez-Canales, Monica L.; Heaphy, Robert; Gramacy, Robert B.; Taddy, Matt; Chiesa, Michael L.; Thomas, Stephen W.; Swiler, Laura Painton; Hough, Patricia Diane; Lee, Herbert K. H.; Trucano, Timothy Guy; Gray, Genetha Anne
2006-11-01
This project focused on research and algorithmic development in optimization under uncertainty (OUU) problems driven by earth penetrator (EP) designs. While taking into account uncertainty, we addressed three challenges in current simulation-based engineering design and analysis processes. The first challenge required leveraging small local samples, already constructed by optimization algorithms, to build effective surrogate models. We used Gaussian Process (GP) models to construct these surrogates. We developed two OUU algorithms using 'local' GPs (OUU-LGP) and one OUU algorithm using 'global' GPs (OUU-GGP) that appear competitive or better than current methods. The second challenge was to develop a methodical design process based on multi-resolution, multi-fidelity models. We developed a Multi-Fidelity Bayesian Auto-regressive process (MF-BAP). The third challenge involved the development of tools that are computational feasible and accessible. We created MATLAB{reg_sign} and initial DAKOTA implementations of our algorithms.
Full design of fuzzy controllers using genetic algorithms
NASA Technical Reports Server (NTRS)
Homaifar, Abdollah; Mccormick, ED
1992-01-01
This paper examines the applicability of genetic algorithms (GA) in the complete design of fuzzy logic controllers. While GA has been used before in the development of rule sets or high performance membership functions, the interdependence between these two components dictates that they should be designed together simultaneously. GA is fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. We show the application of this new method to the development of a cart controller.
Full design of fuzzy controllers using genetic algorithms
NASA Technical Reports Server (NTRS)
Homaifar, Abdollah; Mccormick, ED
1992-01-01
This paper examines the applicability of genetic algorithms in the complete design of fuzzy logic controllers. While GA has been used before in the development of rule sets or high performance membership functions, the interdependence between these two components dictates that they should be designed together simultaneously. GA is fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. We show the application of this new method to the development of a cart controller.
Algorithmic design for 3D printing at building scale
Guerguis, Maged; Eikevik, Leif; Obendorf, Andrew; ...
2017-01-01
Here, this paper addresses the use of algorithmic design paired with additive manufacturing and their potential impact on architectural design and fabrication of a full-sized building, as demonstrated with the AMIE project. AMIE (Additive Manufacturing and Integrated Energy) was collaboration to 3d print a building and vehicle. Both the car and building were designed to generate, store and share energy in an effort to reduce or eliminate reliability on the power grid. This paper is intended to outline our methodology in successfully designing for these innovative strategies, with a focus on the use of computational design tools as a catalystmore » for design optimization, integrated project delivery, rapid prototyping and fabrication of building elements using additive manufacturing.« less
Algorithmic design for 3D printing at building scale
Guerguis, Maged; Eikevik, Leif; Obendorf, Andrew; Tryggestad, Lucas; Enquist, Philip; Lee, Brian; Johnson, Benton; Post, Brian K.; Biswas, Kaushik
2017-01-01
Here, this paper addresses the use of algorithmic design paired with additive manufacturing and their potential impact on architectural design and fabrication of a full-sized building, as demonstrated with the AMIE project. AMIE (Additive Manufacturing and Integrated Energy) was collaboration to 3d print a building and vehicle. Both the car and building were designed to generate, store and share energy in an effort to reduce or eliminate reliability on the power grid. This paper is intended to outline our methodology in successfully designing for these innovative strategies, with a focus on the use of computational design tools as a catalyst for design optimization, integrated project delivery, rapid prototyping and fabrication of building elements using additive manufacturing.
Mechanical verification of a schematic Byzantine clock synchronization algorithm
NASA Technical Reports Server (NTRS)
Shankar, Natarajan
1991-01-01
Schneider generalizes a number of protocols for Byzantine fault tolerant clock synchronization and presents a uniform proof for their correctness. The authors present a machine checked proof of this schematic protocol that revises some of the details in Schneider's original analysis. The verification was carried out with the EHDM system developed at the SRI Computer Science Laboratory. The mechanically checked proofs include the verification that the egocentric mean function used in Lamport and Melliar-Smith's Interactive Convergence Algorithm satisfies the requirements of Schneider's protocol.
A disturbance based control/structure design algorithm
NASA Technical Reports Server (NTRS)
Mclaren, Mark D.; Slater, Gary L.
1989-01-01
Some authors take a classical approach to the simultaneous structure/control optimization by attempting to simultaneously minimize the weighted sum of the total mass and a quadratic form, subject to all of the structural and control constraints. Here, the optimization will be based on the dynamic response of a structure to an external unknown stochastic disturbance environment. Such a response to excitation approach is common to both the structural and control design phases, and hence represents a more natural control/structure optimization strategy than relying on artificial and vague control penalties. The design objective is to find the structure and controller of minimum mass such that all the prescribed constraints are satisfied. Two alternative solution algorithms are presented which have been applied to this problem. Each algorithm handles the optimization strategy and the imposition of the nonlinear constraints in a different manner. Two controller methodologies, and their effect on the solution algorithm, will be considered. These are full state feedback and direct output feedback, although the problem formulation is not restricted solely to these forms of controller. In fact, although full state feedback is a popular choice among researchers in this field (for reasons that will become apparent), its practical application is severely limited. The controller/structure interaction is inserted by the imposition of appropriate closed-loop constraints, such as closed-loop output response and control effort constraints. Numerical results will be obtained for a representative flexible structure model to illustrate the effectiveness of the solution algorithms.
Entropy-Based Search Algorithm for Experimental Design
NASA Astrophysics Data System (ADS)
Malakar, N. K.; Knuth, K. H.
2011-03-01
The scientific method relies on the iterated processes of inference and inquiry. The inference phase consists of selecting the most probable models based on the available data; whereas the inquiry phase consists of using what is known about the models to select the most relevant experiment. Optimizing inquiry involves searching the parameterized space of experiments to select the experiment that promises, on average, to be maximally informative. In the case where it is important to learn about each of the model parameters, the relevance of an experiment is quantified by Shannon entropy of the distribution of experimental outcomes predicted by a probable set of models. If the set of potential experiments is described by many parameters, we must search this high-dimensional entropy space. Brute force search methods will be slow and computationally expensive. We present an entropy-based search algorithm, called nested entropy sampling, to select the most informative experiment for efficient experimental design. This algorithm is inspired by Skilling's nested sampling algorithm used in inference and borrows the concept of a rising threshold while a set of experiment samples are maintained. We demonstrate that this algorithm not only selects highly relevant experiments, but also is more efficient than brute force search. Such entropic search techniques promise to greatly benefit autonomous experimental design.
A new algorithm for modeling friction in dynamic mechanical systems
NASA Technical Reports Server (NTRS)
Hill, R. E.
1988-01-01
A method of modeling friction forces that impede the motion of parts of dynamic mechanical systems is described. Conventional methods in which the friction effect is assumed a constant force, or torque, in a direction opposite to the relative motion, are applicable only to those cases where applied forces are large in comparison to the friction, and where there is little interest in system behavior close to the times of transitions through zero velocity. An algorithm is described that provides accurate determination of friction forces over a wide range of applied force and velocity conditions. The method avoids the simulation errors resulting from a finite integration interval used in connection with a conventional friction model, as is the case in many digital computer-based simulations. The algorithm incorporates a predictive calculation based on initial conditions of motion, externally applied forces, inertia, and integration step size. The predictive calculation in connection with an external integration process provides an accurate determination of both static and Coulomb friction forces and resulting motions in dynamic simulations. Accuracy of the results is improved over that obtained with conventional methods and a relatively large integration step size is permitted. A function block for incorporation in a specific simulation program is described. The general form of the algorithm facilitates implementation with various programming languages such as FORTRAN or C, as well as with other simulation programs.
Mechanical considerations and design skills.
Alvis, Robert L.
2008-03-01
The purpose of the report is to provide experienced-based insights into design processes that will benefit designers beginning their employment at Sandia National Laboratories or those assuming new design responsibilities. The main purpose of this document is to provide engineers with the practical aspects of system design. The material discussed here may not be new to some readers, but some of it was to me. Transforming an idea to a design to solve a problem is a skill, and skills are similar to history lessons. We gain these skills from experience, and many of us have not been fortunate enough to grow in an environment that provided the skills that we now need. I was fortunate to grow up on a farm where we had to learn how to maintain and operate several different kinds of engines and machines. If you are like me, my formal experience is partially based upon the two universities from which I graduated, where few practical applications of the technologies were taught. What was taught was mainly theoretical, and few instructors had practical experience to offer the students. I understand this, as students have their hands full just to learn the theoretical. The practical part was mainly left up to 'on the job experience'. However, I believe it is better to learn the practical applications early and apply them quickly 'on the job'. System design engineers need to know several technical things, both in and out of their field of expertise. An engineer is not expected to know everything, but he should know when to ask an expert for assistance. This 'expert' can be in any field, whether it is in analyses, drafting, machining, material properties, testing, etc. The best expert is a person who has practical experience in the area of needed information, and consulting with that individual can be the best and quickest way for one to learn. If the information provided here can improve your design skills and save one design from having a problem, save cost of development, or
An exact algorithm for optimal MAE stack filter design.
Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior
2007-02-01
We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.
Research on Knowledge Based Programming and Algorithm Design.
1981-08-01
algorithm design results will also appear in Steve Tappel’s doctoral disser- tation. Beverly Kedzierski , of the University of Southwestern Louisiana, is...Tom Pressburger, Susan Angebranndt, Beverly Kedzierski , Bernard Mont-Reynaud, and Daniel Chapiro Systems Control, Inc. This section presents an...ideas. The authors would like to thank them, as well as Beverly Kedzierski , Jerry Feldman and Sue Angebranndt for very helpful comments on content and
Creative mechanism design for a prosthetic hand.
Chang, Wen-Tung; Tseng, Ching-Huan; Wu, Long-Long
2004-01-01
In this paper, an auxiliary methodology called the creative mechanism design is introduced into the innovation of gripping devices for prosthetic hands. This methodology is a systematic approach based on modification of existing devices for the generation of all possible topological structures of mechanisms and mechanical devices. An existing gripping device (Teh Lin ATG-5F prosthetic hand) constructed by a planar six-bar linkage with one degree of freedom is dealt with by using this methodology. Through the processes of generalization, number synthesis, specialization and particularization for the existing design, five new mechanisms are created in this study to apply to anthropomorphic prosthetic hands. The results show that the methodology for creative mechanism design is a powerful tool for creating new categories of mechanisms to avoid existing designs that have patent protection and can help designers in the conceptual phase. Also, this methodology is validated as a useful way to improve prosthetic hands for amputees.
Efficient computer algebra algorithms for polynomial matrices in control design
NASA Technical Reports Server (NTRS)
Baras, J. S.; Macenany, D. C.; Munach, R.
1989-01-01
The theory of polynomial matrices plays a key role in the design and analysis of multi-input multi-output control and communications systems using frequency domain methods. Examples include coprime factorizations of transfer functions, cannonical realizations from matrix fraction descriptions, and the transfer function design of feedback compensators. Typically, such problems abstract in a natural way to the need to solve systems of Diophantine equations or systems of linear equations over polynomials. These and other problems involving polynomial matrices can in turn be reduced to polynomial matrix triangularization procedures, a result which is not surprising given the importance of matrix triangularization techniques in numerical linear algebra. Matrices with entries from a field and Gaussian elimination play a fundamental role in understanding the triangularization process. In the case of polynomial matrices, matrices with entries from a ring for which Gaussian elimination is not defined and triangularization is accomplished by what is quite properly called Euclidean elimination. Unfortunately, the numerical stability and sensitivity issues which accompany floating point approaches to Euclidean elimination are not very well understood. New algorithms are presented which circumvent entirely such numerical issues through the use of exact, symbolic methods in computer algebra. The use of such error-free algorithms guarantees that the results are accurate to within the precision of the model data--the best that can be hoped for. Care must be taken in the design of such algorithms due to the phenomenon of intermediate expressions swell.
Orthogonalizing EM: A design-based least squares algorithm.
Xiong, Shifeng; Dai, Bin; Huling, Jared; Qian, Peter Z G
We introduce an efficient iterative algorithm, intended for various least squares problems, based on a design of experiments perspective. The algorithm, called orthogonalizing EM (OEM), works for ordinary least squares and can be easily extended to penalized least squares. The main idea of the procedure is to orthogonalize a design matrix by adding new rows and then solve the original problem by embedding the augmented design in a missing data framework. We establish several attractive theoretical properties concerning OEM. For the ordinary least squares with a singular regression matrix, an OEM sequence converges to the Moore-Penrose generalized inverse-based least squares estimator. For ordinary and penalized least squares with various penalties, it converges to a point having grouping coherence for fully aliased regression matrices. Convergence and the convergence rate of the algorithm are examined. Finally, we demonstrate that OEM is highly efficient for large-scale least squares and penalized least squares problems, and is considerably faster than competing methods when n is much larger than p. Supplementary materials for this article are available online.
Orthogonalizing EM: A design-based least squares algorithm
Xiong, Shifeng; Dai, Bin; Huling, Jared; Qian, Peter Z. G.
2016-01-01
We introduce an efficient iterative algorithm, intended for various least squares problems, based on a design of experiments perspective. The algorithm, called orthogonalizing EM (OEM), works for ordinary least squares and can be easily extended to penalized least squares. The main idea of the procedure is to orthogonalize a design matrix by adding new rows and then solve the original problem by embedding the augmented design in a missing data framework. We establish several attractive theoretical properties concerning OEM. For the ordinary least squares with a singular regression matrix, an OEM sequence converges to the Moore-Penrose generalized inverse-based least squares estimator. For ordinary and penalized least squares with various penalties, it converges to a point having grouping coherence for fully aliased regression matrices. Convergence and the convergence rate of the algorithm are examined. Finally, we demonstrate that OEM is highly efficient for large-scale least squares and penalized least squares problems, and is considerably faster than competing methods when n is much larger than p. Supplementary materials for this article are available online. PMID:27499558
Robust Optimization Design Algorithm for High-Frequency TWTs
NASA Technical Reports Server (NTRS)
Wilson, Jeffrey D.; Chevalier, Christine T.
2010-01-01
Traveling-wave tubes (TWTs), such as the Ka-band (26-GHz) model recently developed for the Lunar Reconnaissance Orbiter, are essential as communication amplifiers in spacecraft for virtually all near- and deep-space missions. This innovation is a computational design algorithm that, for the first time, optimizes the efficiency and output power of a TWT while taking into account the effects of dimensional tolerance variations. Because they are primary power consumers and power generation is very expensive in space, much effort has been exerted over the last 30 years to increase the power efficiency of TWTs. However, at frequencies higher than about 60 GHz, efficiencies of TWTs are still quite low. A major reason is that at higher frequencies, dimensional tolerance variations from conventional micromachining techniques become relatively large with respect to the circuit dimensions. When this is the case, conventional design- optimization procedures, which ignore dimensional variations, provide inaccurate designs for which the actual amplifier performance substantially under-performs that of the design. Thus, this new, robust TWT optimization design algorithm was created to take account of and ameliorate the deleterious effects of dimensional variations and to increase efficiency, power, and yield of high-frequency TWTs. This design algorithm can help extend the use of TWTs into the terahertz frequency regime of 300-3000 GHz. Currently, these frequencies are under-utilized because of the lack of efficient amplifiers, thus this regime is known as the "terahertz gap." The development of an efficient terahertz TWT amplifier could enable breakthrough applications in space science molecular spectroscopy, remote sensing, nondestructive testing, high-resolution "through-the-wall" imaging, biomedical imaging, and detection of explosives and toxic biochemical agents.
Diagonal dominance using function minimization algorithms. [multivariable control system design
NASA Technical Reports Server (NTRS)
Leininger, G. G.
1977-01-01
A new approach to the design of multivariable control systems using the inverse Nyquist array method is proposed. The technique utilizes a conjugate direction function minimization algorithm to achieve dominance over a specified frequency range by minimizing the ratio of the moduli of the off-diagonal terms to the moduli of the diagonal term of the inverse open loop transfer function matrix. The technique is easily implemented in either a batch or interactive computer mode and will yield diagonalization when previously suggested methods fail. The proposed method has been successfully applied to design a control system for a sixteenth order state model of the F-100 turbofan engine with three inputs.
Thrust vector control algorithm design for the Cassini spacecraft
NASA Astrophysics Data System (ADS)
Enright, Paul J.
1993-02-01
This paper describes a preliminary design of the thrust vector control algorithm for the interplanetary spacecraft, Cassini. Topics of discussion include flight software architecture, modeling of sensors, actuators, and vehicle dynamics, and controller design and analysis via classical methods. Special attention is paid to potential interactions with structural flexibilities and propellant dynamics. Controller performance is evaluated in a simulation environment built around a multi-body dynamics model, which contains nonlinear models of the relevant hardware and preliminary versions of supporting attitude determination and control functions.
Thrust vector control algorithm design for the Cassini spacecraft
NASA Technical Reports Server (NTRS)
Enright, Paul J.
1993-01-01
This paper describes a preliminary design of the thrust vector control algorithm for the interplanetary spacecraft, Cassini. Topics of discussion include flight software architecture, modeling of sensors, actuators, and vehicle dynamics, and controller design and analysis via classical methods. Special attention is paid to potential interactions with structural flexibilities and propellant dynamics. Controller performance is evaluated in a simulation environment built around a multi-body dynamics model, which contains nonlinear models of the relevant hardware and preliminary versions of supporting attitude determination and control functions.
A Matrix-Free Algorithm for Multidisciplinary Design Optimization
NASA Astrophysics Data System (ADS)
Lambe, Andrew Borean
Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation. motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and
A Matrix-Free Algorithm for Multidisciplinary Design Optimization
NASA Astrophysics Data System (ADS)
Lambe, Andrew Borean
Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and
An efficient parallel algorithm for accelerating computational protein design
Zhou, Yichao; Xu, Wei; Donald, Bruce R.; Zeng, Jianyang
2014-01-01
Motivation: Structure-based computational protein design (SCPR) is an important topic in protein engineering. Under the assumption of a rigid backbone and a finite set of discrete conformations of side-chains, various methods have been proposed to address this problem. A popular method is to combine the dead-end elimination (DEE) and A* tree search algorithms, which provably finds the global minimum energy conformation (GMEC) solution. Results: In this article, we improve the efficiency of computing A* heuristic functions for protein design and propose a variant of A* algorithm in which the search process can be performed on a single GPU in a massively parallel fashion. In addition, we make some efforts to address the memory exceeding problem in A* search. As a result, our enhancements can achieve a significant speedup of the A*-based protein design algorithm by four orders of magnitude on large-scale test data through pre-computation and parallelization, while still maintaining an acceptable memory overhead. We also show that our parallel A* search algorithm could be successfully combined with iMinDEE, a state-of-the-art DEE criterion, for rotamer pruning to further improve SCPR with the consideration of continuous side-chain flexibility. Availability: Our software is available and distributed open-source under the GNU Lesser General License Version 2.1 (GNU, February 1999). The source code can be downloaded from http://www.cs.duke.edu/donaldlab/osprey.php or http://iiis.tsinghua.edu.cn/∼compbio/software.html. Contact: zengjy321@tsinghua.edu.cn Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24931991
An adaptive multimeme algorithm for designing HIV multidrug therapies.
Neri, Ferrante; Toivanen, Jari; Cascella, Giuseppe Leonardo; Ong, Yew-Soon
2007-01-01
This paper proposes a period representation for modeling the multidrug HIV therapies and an Adaptive Multimeme Algorithm (AMmA) for designing the optimal therapy. The period representation offers benefits in terms of flexibility and reduction in dimensionality compared to the binary representation. The AMmA is a memetic algorithm which employs a list of three local searchers adaptively activated by an evolutionary framework. These local searchers, having different features according to the exploration logic and the pivot rule, have the role of exploring the decision space from different and complementary perspectives and, thus, assisting the standard evolutionary operators in the optimization process. Furthermore, the AMmA makes use of an adaptation which dynamically sets the algorithmic parameters in order to prevent stagnation and premature convergence. The numerical results demonstrate that the application of the proposed algorithm leads to very efficient medication schedules which quickly stimulate a strong immune response to HIV. The earlier termination of the medication schedule leads to lesser unpleasant side effects for the patient due to strong antiretroviral therapy. A numerical comparison shows that the AMmA is more efficient than three popular metaheuristics. Finally, a statistical test based on the calculation of the tolerance interval confirms the superiority of the AMmA compared to the other methods for the problem under study.
An Adaptive Hybrid Genetic Algorithm for Improved Groundwater Remediation Design
NASA Astrophysics Data System (ADS)
Espinoza, F. P.; Minsker, B. S.; Goldberg, D. E.
2001-12-01
Identifying optimal designs for a groundwater remediation system is computationally intensive, especially for complex, nonlinear problems such as enhanced in situ bioremediation technology. To improve performance, we apply a hybrid genetic algorithm (HGA), which is a two-step solution method: a genetic algorithm (GA) for global search using the entire population and then a local search (LS) to improve search speed for only a few individuals in the population. We implement two types of HGAs: a non-adaptive HGA (NAHGA), whose operations are invariant throughout the run, and a self-adaptive HGA (SAHGA), whose operations adapt to the performance of the algorithm. The best settings of the two HGAs for optimal performance are then investigated for a groundwater remediation problem. The settings include the frequency of LS with respect to the normal GA evaluation, probability of individual selection for LS, evolution criterion for LS (Lamarckian or Baldwinian), and number of local search iterations. A comparison of the algorithms' performance under different settings will be presented.
Design of dual-band reflectarray using genetic algorithm
NASA Astrophysics Data System (ADS)
Maruyama, Tamami
2017-07-01
This paper proposes novel design method of dual-band reflectarray using genetic algorithm (GA). Ordinary, each elements of reflectarray are designed to have desired reflection phase. However, when we adopt same polarization in dual frequencies, the element configuration designed to satisfy desired reflection phase in one frequency influences the characteristics in other frequency. Therefore, it is difficult to achieve dual-band reflectarray. To address the issues, we adopt two layer patches for element to increase flexibility of design and optimize the patches configuration using GA. As a result, we achieve novel reflectarray that reflect wave towards the direction of theta equal to 27 deg. and phi equal to 0 deg. in dual frequency simultaneously when incidence wave is coming from the direction of theta equal to 0 deg. and phi equal to 0 deg. in dual frequency.
Chiral metamaterial design using optimized pixelated inclusions with genetic algorithm
NASA Astrophysics Data System (ADS)
Akturk, Cemal; Karaaslan, Muharrem; Ozdemir, Ersin; Ozkaner, Vedat; Dincer, Furkan; Bakir, Mehmet; Ozer, Zafer
2015-03-01
Chiral metamaterials have been a research area for many researchers due to their polarization rotation properties on electromagnetic waves. However, most of the proposed chiral metamaterials are designed depending on experience or time-consuming inefficient simulations. A method is investigated for designing a chiral metamaterial with a strong and natural chirality admittance by optimizing a grid of metallic pixels through both sides of a dielectric sheet placed perpendicular to the incident wave by using a genetic algorithm (GA) technique based on finite element method solver. The effective medium parameters are obtained by using constitutive equations and S parameters. The proposed methodology is very efficient for designing a chiral metamaterial with the desired effective medium parameters. By using GA-based topology, it is proven that a chiral metamaterial can be designed and manufactured more easily and with a low cost.
Linear vs. function-based dose algorithm designs.
Stanford, N
2011-03-01
The performance requirements prescribed in IEC 62387-1, 2007 recommend linear, additive algorithms for external dosimetry [IEC. Radiation protection instrumentation--passive integrating dosimetry systems for environmental and personal monitoring--Part 1: General characteristics and performance requirements. IEC 62387-1 (2007)]. Neither of the two current standards for performance of external dosimetry in the USA address the additivity of dose results [American National Standards Institute, Inc. American National Standard for dosimetry personnel dosimetry performance criteria for testing. ANSI/HPS N13.11 (2009); Department of Energy. Department of Energy Standard for the performance testing of personnel dosimetry systems. DOE/EH-0027 (1986)]. While there are significant merits to adopting a purely linear solution to estimating doses from multi-element external dosemeters, differences in the standards result in technical as well as perception challenges in designing a single algorithm approach that will satisfy both IEC and USA external dosimetry performance requirements. The dosimetry performance testing standards in the USA do not incorporate type testing, but rely on biennial performance tests to demonstrate proficiency in a wide range of pure and mixed fields. The test results are used exclusively to judge the system proficiency, with no specific requirements on the algorithm design. Technical challenges include mixed beta/photon fields with a beta dose as low as 0.30 mSv mixed with 0.05 mSv of low-energy photons. Perception-based challenges, resulting from over 20 y of experience with this type of performance testing in the USA, include the common belief that the overall quality of the dosemeter performance can be judged from performance to pure fields. This paper presents synthetic testing results from currently accredited function-based algorithms and new developed purely linear algorithms. A comparison of the performance data highlights the benefits of each
Mechanical design of walking machines.
Arikawa, Keisuke; Hirose, Shigeo
2007-01-15
The performance of existing actuators, such as electric motors, is very limited, be it power-weight ratio or energy efficiency. In this paper, we discuss the method to design a practical walking machine under this severe constraint with focus on two concepts, the gravitationally decoupled actuation (GDA) and the coupled drive. The GDA decouples the driving system against the gravitational field to suppress generation of negative power and improve energy efficiency. On the other hand, the coupled drive couples the driving system to distribute the output power equally among actuators and maximize the utilization of installed actuator power. First, we depict the GDA and coupled drive in detail. Then, we present actual machines, TITAN-III and VIII, quadruped walking machines designed on the basis of the GDA, and NINJA-I and II, quadruped wall walking machines designed on the basis of the coupled drive. Finally, we discuss walking machines that travel on three-dimensional terrain (3D terrain), which includes the ground, walls and ceiling. Then, we demonstrate with computer simulation that we can selectively leverage GDA and coupled drive by walking posture control.
Comparison of adaptive algorithms for the control of tonal disturbances in mechanical systems
NASA Astrophysics Data System (ADS)
Zilletti, M.; Elliott, S. J.; Cheer, J.
2016-09-01
This paper presents a study on the performance of adaptive control algorithms designed to reduce the vibration of mechanical systems excited by a harmonic disturbance. The mechanical system consists of a mass suspended on a spring and a damper. The system is equipped with a force actuator in parallel with the suspension. The control signal driving the actuator is generated by adjusting the amplitude and phase of a sinusoidal reference signal at the same frequency as the excitation. An adaptive feedforward control algorithm is used to adapt the amplitude and phase of the control signal, to minimise the mean square velocity of the mass. Two adaptation strategies are considered in which the control signal is either updated after each period of the oscillation or at every time sample. The first strategy is traditionally used in vibration control in helicopters for example; the second strategy is normally referred to as the filtered-x least mean square algorithm and is often used to control engine noise in cars. The two adaptation strategies are compared through a parametric study, which investigates the influence of the properties of both the mechanical system and the control system on the convergence speed of the two algorithms.
Hernández-Ocaña, Betania; Pozos-Parra, Ma Del Pilar; Mezura-Montes, Efrén; Portilla-Flores, Edgar Alfredo; Vega-Alvarado, Eduardo; Calva-Yáñez, Maria Bárbara
2016-01-01
This paper presents two-swim operators to be added to the chemotaxis process of the modified bacterial foraging optimization algorithm to solve three instances of the synthesis of four-bar planar mechanisms. One swim favors exploration while the second one promotes fine movements in the neighborhood of each bacterium. The combined effect of the new operators looks to increase the production of better solutions during the search. As a consequence, the ability of the algorithm to escape from local optimum solutions is enhanced. The algorithm is tested through four experiments and its results are compared against two BFOA-based algorithms and also against a differential evolution algorithm designed for mechanical design problems. The overall results indicate that the proposed algorithm outperforms other BFOA-based approaches and finds highly competitive mechanisms, with a single set of parameter values and with less evaluations in the first synthesis problem, with respect to those mechanisms obtained by the differential evolution algorithm, which needed a parameter fine-tuning process for each optimization problem.
Hernández-Ocaña, Betania; Pozos-Parra, Ma. Del Pilar; Mezura-Montes, Efrén; Portilla-Flores, Edgar Alfredo; Vega-Alvarado, Eduardo; Calva-Yáñez, Maria Bárbara
2016-01-01
This paper presents two-swim operators to be added to the chemotaxis process of the modified bacterial foraging optimization algorithm to solve three instances of the synthesis of four-bar planar mechanisms. One swim favors exploration while the second one promotes fine movements in the neighborhood of each bacterium. The combined effect of the new operators looks to increase the production of better solutions during the search. As a consequence, the ability of the algorithm to escape from local optimum solutions is enhanced. The algorithm is tested through four experiments and its results are compared against two BFOA-based algorithms and also against a differential evolution algorithm designed for mechanical design problems. The overall results indicate that the proposed algorithm outperforms other BFOA-based approaches and finds highly competitive mechanisms, with a single set of parameter values and with less evaluations in the first synthesis problem, with respect to those mechanisms obtained by the differential evolution algorithm, which needed a parameter fine-tuning process for each optimization problem. PMID:27057156
Optimal design of link systems using successive zooming genetic algorithm
NASA Astrophysics Data System (ADS)
Kwon, Young-Doo; Sohn, Chang-hyun; Kwon, Soon-Bum; Lim, Jae-gyoo
2009-07-01
Link-systems have been around for a long time and are still used to control motion in diverse applications such as automobiles, robots and industrial machinery. This study presents a procedure involving the use of a genetic algorithm for the optimal design of single four-bar link systems and a double four-bar link system used in diesel engine. We adopted the Successive Zooming Genetic Algorithm (SZGA), which has one of the most rapid convergence rates among global search algorithms. The results are verified by experiment and the Recurdyn dynamic motion analysis package. During the optimal design of single four-bar link systems, we found in the case of identical input/output (IO) angles that the initial and final configurations show certain symmetry. For the double link system, we introduced weighting factors for the multi-objective functions, which minimize the difference between output angles, providing balanced engine performance, as well as the difference between final output angle and the desired magnitudes of final output angle. We adopted a graphical method to select a proper ratio between the weighting factors.
Design technologies for DSP algorithm implementation on heterogeneous architectures
NASA Astrophysics Data System (ADS)
McAllister, John; Yi, Ying; Woods, Roger F.; Walke, Richard L.; Reilly, Darren; Colgan, Kevin
2003-12-01
Computationally intensive digital signal processing (DSP) systems sometimes have real time requirements beyond that which programmable processor platform solutions, consisting of RISC and DSP processors, can achieve. The addition of Field Programmable Gate Array (FPGA) components to these platforms provides a configurable hardware resource where increased parallelism levels allow very large computational rates. Techniques to implement circuit architectures from signal flow graph (SFG) algorithm expression can produce highly efficient processor implementations. Applying folding transformations produces implementations where hardware resource usage is reduced at the possible expense of throughput. In this paper a new development methodology is presented which analyses the SFG algorithm to suggest appropriate folding techniques. By characterizing different folding techniques, a template circuit architecture can be created early in the design process which does not alter throughout the remainder of the implementation process. Retiming techniques applied to the algorithm SFG produces the properly timed implementation from the template. By applying this methodology, architectural exploration can be quickly and efficiently performed to generate a set of implementations (an 'implementation space") to best meet the constraints of the system. When applied to a Normalised Lattice Filter design example, the results demonstrate high savings on FPGA resource usage, with little reduction in real time performance, demonstrating the implementation advantage of employing this methodology.
OSPREY: protein design with ensembles, flexibility, and provable algorithms.
Gainza, Pablo; Roberts, Kyle E; Georgiev, Ivelin; Lilien, Ryan H; Keedy, Daniel A; Chen, Cheng-Yu; Reza, Faisal; Anderson, Amy C; Richardson, David C; Richardson, Jane S; Donald, Bruce R
2013-01-01
We have developed a suite of protein redesign algorithms that improves realistic in silico modeling of proteins. These algorithms are based on three characteristics that make them unique: (1) improved flexibility of the protein backbone, protein side-chains, and ligand to accurately capture the conformational changes that are induced by mutations to the protein sequence; (2) modeling of proteins and ligands as ensembles of low-energy structures to better approximate binding affinity; and (3) a globally optimal protein design search, guaranteeing that the computational predictions are optimal with respect to the input model. Here, we illustrate the importance of these three characteristics. We then describe OSPREY, a protein redesign suite that implements our protein design algorithms. OSPREY has been used prospectively, with experimental validation, in several biomedically relevant settings. We show in detail how OSPREY has been used to predict resistance mutations and explain why improved flexibility, ensembles, and provability are essential for this application. OSPREY is free and open source under a Lesser GPL license. The latest version is OSPREY 2.0. The program, user manual, and source code are available at www.cs.duke.edu/donaldlab/software.php. osprey@cs.duke.edu. Copyright © 2013 Elsevier Inc. All rights reserved.
Design of OFDM radar pulses using genetic algorithm based techniques
NASA Astrophysics Data System (ADS)
Lellouch, Gabriel; Mishra, Amit Kumar; Inggs, Michael
2016-08-01
The merit of evolutionary algorithms (EA) to solve convex optimization problems is widely acknowledged. In this paper, a genetic algorithm (GA) optimization based waveform design framework is used to improve the features of radar pulses relying on the orthogonal frequency division multiplexing (OFDM) structure. Our optimization techniques focus on finding optimal phase code sequences for the OFDM signal. Several optimality criteria are used since we consider two different radar processing solutions which call either for single or multiple-objective optimizations. When minimization of the so-called peak-to-mean envelope power ratio (PMEPR) single-objective is tackled, we compare our findings with existing methods and emphasize on the merit of our approach. In the scope of the two-objective optimization, we first address PMEPR and peak-to-sidelobe level ratio (PSLR) and show that our approach based on the non-dominated sorting genetic algorithm-II (NSGA-II) provides design solutions with noticeable improvements as opposed to random sets of phase codes. We then look at another case of interest where the objective functions are two measures of the sidelobe level, namely PSLR and the integrated-sidelobe level ratio (ISLR) and propose to modify the NSGA-II to include a constrain on the PMEPR instead. In the last part, we illustrate via a case study how our encoding solution makes it possible to minimize the single objective PMEPR while enabling a target detection enhancement strategy, when the SNR metric would be chosen for the detection framework.
Neural-network-biased genetic algorithms for materials design
NASA Astrophysics Data System (ADS)
Patra, Tarak; Meenakshisundaram, Venkatesh; Simmons, David
Machine learning tools have been progressively adopted by the materials science community to accelerate design of materials with targeted properties. However, in the search for new materials exhibiting properties and performance beyond that previously achieved, machine learning approaches are frequently limited by two major shortcomings. First, they are intrinsically interpolative. They are therefore better suited to the optimization of properties within the known range of accessible behavior than to the discovery of new materials with extremal behavior. Second, they require the availability of large datasets, which in some fields are not available and would be prohibitively expensive to produce. Here we describe a new strategy for combining genetic algorithms, neural networks and other machine learning tools, and molecular simulation to discover materials with extremal properties in the absence of pre-existing data. Predictions from progressively constructed machine learning tools are employed to bias the evolution of a genetic algorithm, with fitness evaluations performed via direct molecular dynamics simulation. We survey several initial materials design problems we have addressed with this framework and compare its performance to that of standard genetic algorithm approaches. We acknowledge the W. M. Keck Foundation for support of this work.
ARGOS laser system mechanical design
NASA Astrophysics Data System (ADS)
Deysenroth, M.; Honsberg, M.; Gemperlein, H.; Ziegleder, J.; Raab, W.; Rabien, S.; Barl, L.; Gässler, W.; Borelli, J. L.
2014-07-01
ARGOS, a multi-star adaptive optics system is designed for the wide-field imager and multi-object spectrograph LUCI on the LBT (Large Binocular Telescope). Based on Rayleigh scattering the laser constellation images 3 artificial stars (at 532 nm) per each of the 2 eyes of the LBT, focused at a height of 12 km (Ground Layer Adaptive Optics). The stars are nominally positioned on a circle 2' in radius, but each star can be moved by up to 0.5' in any direction. For all of these needs are following main subsystems necessary: 1. A laser system with its 3 Lasers (Nd:YAG ~18W each) for delivering strong collimated light as for LGS indispensable. 2. The Launch system to project 3 beams per main mirror as a 40 cm telescope to the sky. 3. The Wave Front Sensor with a dichroic mirror. 4. The dichroic mirror unit to grab and interpret the data. 5. A Calibration Unit to adjust the system independently also during day time. 6. Racks + platforms for the WFS units. 7. Platforms and ladders for a secure access. This paper should mainly demonstrate how the ARGOS Laser System is configured and designed to support all other systems.
Optimum detailed design of reinforced concrete frames using genetic algorithms
NASA Astrophysics Data System (ADS)
Govindaraj, V.; Ramasamy, J. V.
2007-06-01
This article presents the application of the genetic algorithm to the optimum detailed design of reinforced concrete frames based on Indian Standard specifications. The objective function is the total cost of the frame which includes the cost of concrete, formwork and reinforcing steel for individual members of the frame. In order for the optimum design to be directly constructible without any further modifications, aspects such as available standard reinforcement bar diameters, spacing requirements of reinforcing bars, modular sizes of members, architectural requirements on member sizes and other practical requirements in addition to relevant codal provisions are incorporated into the optimum design model. The produced optimum design satisfies the strength, serviceability, ductility, durability and other constraints related to good design and detailing practice. The detailing of reinforcements in the beam members is carried out as a sub-level optimization problem. This strategy helps to reduce the size of the optimization problem and saves computational time. The proposed method is demonstrated through several example problems and the optimum results obtained are compared with those in the available literature. It is concluded that the proposed optimum design model can be adopted in design offices as it yields rational, reliable, economical, time-saving and practical designs.
A preliminary design for flight testing the FINDS algorithm
NASA Technical Reports Server (NTRS)
Caglayan, A. K.; Godiwala, P. M.
1986-01-01
This report presents a preliminary design for flight testing the FINDS (Fault Inferring Nonlinear Detection System) algorithm on a target flight computer. The FINDS software was ported onto the target flight computer by reducing the code size by 65%. Several modifications were made to the computational algorithms resulting in a near real-time execution speed. Finally, a new failure detection strategy was developed resulting in a significant improvement in the detection time performance. In particular, low level MLS, IMU and IAS sensor failures are detected instantaneously with the new detection strategy, while accelerometer and the rate gyro failures are detected within the minimum time allowed by the information generated in the sensor residuals based on the point mass equations of motion. All of the results have been demonstrated by using five minutes of sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment.
Design and application of compliant mechanisms for surgical tools.
Kota, S; Lu, K-J; Kreiner, K; Trease, B; Arenas, J; Geiger, J
2005-11-01
This paper introduces the benefits of exploiting elasticity in the engineering design of surgical tools, in general, and of minimally invasive procedures, in particular. Compliant mechanisms are jointless mechanisms that rely on elastic deformation to transmit forces and motion. The lack of traditional joints in these single-piece flexible structures offers many benefits, including the absence of wear debris, pinch points, crevices, and lubrication. Such systems are particularly amenable to embedded sensing for haptic feedback and embedded actuation with active-material actuators. The paper provides an overview of design synthesis methods developed at the Compliant Systems Design Laboratory and focuses specifically on surgical applications. Compliant systems have potential to integrate. well within the constraints of laparoscopic procedures and telerobotic surgery. A load-path representation is used within a genetic algorithm to solve two gripper example problems. In addition, the paper illustrates the design and construction of an organ (kidney) manipulator for use in minimally invasive procedures.
Opto-mechanical design of SCUBA-2
NASA Astrophysics Data System (ADS)
Atad-Ettedgui, Eli; Peacocke, Tully; Montgomery, David; Gostick, David; McGregor, Helen; Cliff, Mark; Saunders, Ian J.; Ploeg, Leo; Dorrepaal, Michiel; van Venrooij, Bart
2006-06-01
This paper describes the opto-mechanical design of a large instrument for sub-mm, SCUBA-2, to be commissioned at JCMT. The scientific requirements, specially the large fov and the constraints of the telescope mechanical structure, lead to a complex optical design using freeform aluminium mirrors . The mechanical design is also challenging with large modules to be mounted and aligned in the telescope as well as the cryogenic instrument containing the mirrors, the filters, the dichroics and the detector modules. The cryogenic isostatic mounting, the structural and thermal designs are presented. This includes details of the fabrication of the structure and design of a shutter mechanism for operation at 4K. The results of the first AIV cool-down are also presented.
VitAL: Viterbi Algorithm for de novo Peptide Design
Unal, E. Besray; Gursoy, Attila; Erman, Burak
2010-01-01
Background Drug design against proteins to cure various diseases has been studied for several years. Numerous design techniques were discovered for small organic molecules for specific protein targets. The specificity, toxicity and selectivity of small molecules are hard problems to solve. The use of peptide drugs enables a partial solution to the toxicity problem. There has been a wide interest in peptide design, but the design techniques of a specific and selective peptide inhibitor against a protein target have not yet been established. Methodology/Principal Findings A novel de novo peptide design approach is developed to block activities of disease related protein targets. No prior training, based on known peptides, is necessary. The method sequentially generates the peptide by docking its residues pair by pair along a chosen path on a protein. The binding site on the protein is determined via the coarse grained Gaussian Network Model. A binding path is determined. The best fitting peptide is constructed by generating all possible peptide pairs at each point along the path and determining the binding energies between these pairs and the specific location on the protein using AutoDock. The Markov based partition function for all possible choices of the peptides along the path is generated by a matrix multiplication scheme. The best fitting peptide for the given surface is obtained by a Hidden Markov model using Viterbi decoding. The suitability of the conformations of the peptides that result upon binding on the surface are included in the algorithm by considering the intrinsic Ramachandran potentials. Conclusions/Significance The model is tested on known protein-peptide inhibitor complexes. The present algorithm predicts peptides that have better binding energies than those of the existing ones. Finally, a heptapeptide is designed for a protein that has excellent binding affinity according to AutoDock results. PMID:20532195
Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm
NASA Technical Reports Server (NTRS)
2005-01-01
This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.
Protein design algorithms predict viable resistance to an experimental antifolate.
Reeve, Stephanie M; Gainza, Pablo; Frey, Kathleen M; Georgiev, Ivelin; Donald, Bruce R; Anderson, Amy C
2015-01-20
Methods to accurately predict potential drug target mutations in response to early-stage leads could drive the design of more resilient first generation drug candidates. In this study, a structure-based protein design algorithm (K* in the OSPREY suite) was used to prospectively identify single-nucleotide polymorphisms that confer resistance to an experimental inhibitor effective against dihydrofolate reductase (DHFR) from Staphylococcus aureus. Four of the top-ranked mutations in DHFR were found to be catalytically competent and resistant to the inhibitor. Selection of resistant bacteria in vitro reveals that two of the predicted mutations arise in the background of a compensatory mutation. Using enzyme kinetics, microbiology, and crystal structures of the complexes, we determined the fitness of the mutant enzymes and strains, the structural basis of resistance, and the compensatory relationship of the mutations. To our knowledge, this work illustrates the first application of protein design algorithms to prospectively predict viable resistance mutations that arise in bacteria under antibiotic pressure.
Improved genetic algorithm for mixed-discrete-continuous design optimization problems
NASA Astrophysics Data System (ADS)
Lee, Kuo-Ming; Tsai, Jinn-Tsong; Liu, Tung-Kuan; Chou, Jyh-Horng
2010-10-01
An improved genetic algorithm (IGA) is presented to solve the mixed-discrete-continuous design optimization problems. The IGA approach combines the traditional genetic algorithm with the experimental design method. The experimental design method is incorporated in the crossover operations to systematically select better genes to tailor the crossover operations in order to find the representative chromosomes to be the new potential offspring, so that the IGA approach possesses the merit of global exploration and obtains better solutions. The presented IGA approach is effectively applied to solve one structural and five mechanical engineering problems. The computational results show that the presented IGA approach can obtain better solutions than both the GA-based and the particle-swarm-optimizer-based methods reported recently.
Design principles and algorithms for automated air traffic management
NASA Technical Reports Server (NTRS)
Erzberger, Heinz
1995-01-01
This paper presents design principles and algorithm for building a real time scheduler. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high altitude airspace far from the airport and low altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time.
Design principles and algorithms for automated air traffic management
NASA Technical Reports Server (NTRS)
Erzberger, Heinz
1995-01-01
This paper presents design principles and algorithm for building a real time scheduler. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high altitude airspace far from the airport and low altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time.
Drought Adaptation Mechanisms Should Guide Experimental Design.
Gilbert, Matthew E; Medina, Viviana
2016-08-01
The mechanism, or hypothesis, of how a plant might be adapted to drought should strongly influence experimental design. For instance, an experiment testing for water conservation should be distinct from a damage-tolerance evaluation. We define here four new, general mechanisms for plant adaptation to drought such that experiments can be more easily designed based upon the definitions. A series of experimental methods are suggested together with appropriate physiological measurements related to the drought adaptation mechanisms. The suggestion is made that the experimental manipulation should match the rate, length, and severity of soil water deficit (SWD) necessary to test the hypothesized type of drought adaptation mechanism.
Design Principles and Algorithms for Air Traffic Arrival Scheduling
NASA Technical Reports Server (NTRS)
Erzberger, Heinz; Itoh, Eri
2014-01-01
This report presents design principles and algorithms for building a real-time scheduler of arrival aircraft based on a first-come-first-served (FCFS) scheduling protocol. The algorithms provide the conceptual and computational foundation for the Traffic Management Advisor (TMA) of the Center/terminal radar approach control facilities (TRACON) automation system, which comprises a set of decision support tools for managing arrival traffic at major airports in the United States. The primary objective of the scheduler is to assign arrival aircraft to a favorable landing runway and schedule them to land at times that minimize delays. A further objective of the scheduler is to allocate delays between high-altitude airspace far away from the airport and low-altitude airspace near the airport. A method of delay allocation is described that minimizes the average operating cost in the presence of errors in controlling aircraft to a specified landing time. This report is a revision of an earlier paper first presented as part of an Advisory Group for Aerospace Research and Development (AGARD) lecture series in September 1995. The authors, during vigorous discussions over the details of this paper, felt it was important to the air-trafficmanagement (ATM) community to revise and extend the original 1995 paper, providing more detail and clarity and thereby allowing future researchers to understand this foundational work as the basis for the TMA's scheduling algorithms.
Library design using genetic algorithms for catalyst discovery and optimization
NASA Astrophysics Data System (ADS)
Clerc, Frederic; Lengliz, Mourad; Farrusseng, David; Mirodatos, Claude; Pereira, Sílvia R. M.; Rakotomalala, Ricco
2005-06-01
This study reports a detailed investigation of catalyst library design by genetic algorithm (GA). A methodology for assessing GA configurations is described. Operators, which promote the optimization speed while being robust to noise and outliers, are revealed through statistical studies. The genetic algorithms were implemented in GA platform software called OptiCat, which enables the construction of custom-made workflows using a tool box of operators. Two separate studies were carried out (i) on a virtual benchmark and (ii) on real surface response which is derived from HT screening. Additionally, we report a methodology to model a complex surface response by binning the search space in small zones that are then independently modeled by linear regression. In contrast to artificial neural networks, this approach allows one to obtain an explicit model in an analogical form that can be further used in Excel or entered in OptiCat to perform simulations. While speeding the implementation of a hybrid algorithm combining a GA with a knowledge-based extraction engine is described, while speeding up the optimization process by means of virtual prescreening the hybrid GA enables one to open the "black-box" by providing knowledge as a set of association rules.
A New Differential Evolution Algorithm for Minimax Optimization in Robust Design.
Qiu, Xin; Xu, Jian-Xin; Xu, Yinghao; Tan, Kay Chen
2017-04-24
Minimax optimization, which is actively involved in numerous robust design problems, aims at pursuing the solutions with best worst-case performances. Although considerable research has been devoted to the development of minimax optimization algorithms, there still exist several fundamental limitations for existing approaches, e.g., restriction on problem types, excessively high computational cost, and low optimization efficiency. To address these issues, a minimax differential evolution algorithm is proposed in this paper. First, a novel bottom-boosting scheme enables the algorithm to identify the promising solutions in a reliable yet efficient manner. After that, a partial-regeneration strategy together with a new mutation operator contribute to an in-depth exploration over solution space. Finally, a proper integration of these newly proposed mechanisms leads to an algorithmic structure that can appropriately handle various types of problems. Empirical comparison with seven famous methods demonstrates the statistical superiority of the proposed algorithm. Successful applications in two open problems of robust design further validate the effectiveness of the new approach.
Lee, Donggil; Lee, Kyounghoon; Kim, Seonghun; Yang, Yongsu
2015-04-01
An automatic abalone grading algorithm that estimates abalone weights on the basis of computer vision using 2D images is developed and tested. The algorithm overcomes the problems experienced by conventional abalone grading methods that utilize manual sorting and mechanical automatic grading. To design an optimal algorithm, a regression formula and R(2) value were investigated by performing a regression analysis for each of total length, body width, thickness, view area, and actual volume against abalone weights. The R(2) value between the actual volume and abalone weight was 0.999, showing a relatively high correlation. As a result, to easily estimate the actual volumes of abalones based on computer vision, the volumes were calculated under the assumption that abalone shapes are half-oblate ellipsoids, and a regression formula was derived to estimate the volumes of abalones through linear regression analysis between the calculated and actual volumes. The final automatic abalone grading algorithm is designed using the abalone volume estimation regression formula derived from test results, and the actual volumes and abalone weights regression formula. In the range of abalones weighting from 16.51 to 128.01 g, the results of evaluation of the performance of algorithm via cross-validation indicate root mean square and worst-case prediction errors of are 2.8 and ±8 g, respectively.
Algorithm To Design Finite-Field Normal-Basis Multipliers
NASA Technical Reports Server (NTRS)
Wang, Charles C.
1988-01-01
Way found to exploit Massey-Omura multiplication algorithm. Generalized algorithm locates normal basis in Galois filed GF(2m) and enables development of another algorithm to construct product function.
Application of Simulated Annealing and Related Algorithms to TWTA Design
NASA Technical Reports Server (NTRS)
Radke, Eric M.
2004-01-01
Simulated Annealing (SA) is a stochastic optimization algorithm used to search for global minima in complex design surfaces where exhaustive searches are not computationally feasible. The algorithm is derived by simulating the annealing process, whereby a solid is heated to a liquid state and then cooled slowly to reach thermodynamic equilibrium at each temperature. The idea is that atoms in the solid continually bond and re-bond at various quantum energy levels, and with sufficient cooling time they will rearrange at the minimum energy state to form a perfect crystal. The distribution of energy levels is given by the Boltzmann distribution: as temperature drops, the probability of the presence of high-energy bonds decreases. In searching for an optimal design, local minima and discontinuities are often present in a design surface. SA presents a distinct advantage over other optimization algorithms in its ability to escape from these local minima. Just as high-energy atomic configurations are visited in the actual annealing process in order to eventually reach the minimum energy state, in SA highly non-optimal configurations are visited in order to find otherwise inaccessible global minima. The SA algorithm produces a Markov chain of points in the design space at each temperature, with a monotonically decreasing temperature. A random point is started upon, and the objective function is evaluated at that point. A stochastic perturbation is then made to the parameters of the point to arrive at a proposed new point in the design space, at which the objection function is evaluated as well. If the change in objective function values (Delta)E is negative, the proposed new point is accepted. If (Delta)E is positive, the proposed new point is accepted according to the Metropolis criterion: rho((Delta)f) = exp((-Delta)E/T), where T is the temperature for the current Markov chain. The process then repeats for the remainder of the Markov chain, after which the temperature is
Application of Simulated Annealing and Related Algorithms to TWTA Design
NASA Technical Reports Server (NTRS)
Radke, Eric M.
2004-01-01
Simulated Annealing (SA) is a stochastic optimization algorithm used to search for global minima in complex design surfaces where exhaustive searches are not computationally feasible. The algorithm is derived by simulating the annealing process, whereby a solid is heated to a liquid state and then cooled slowly to reach thermodynamic equilibrium at each temperature. The idea is that atoms in the solid continually bond and re-bond at various quantum energy levels, and with sufficient cooling time they will rearrange at the minimum energy state to form a perfect crystal. The distribution of energy levels is given by the Boltzmann distribution: as temperature drops, the probability of the presence of high-energy bonds decreases. In searching for an optimal design, local minima and discontinuities are often present in a design surface. SA presents a distinct advantage over other optimization algorithms in its ability to escape from these local minima. Just as high-energy atomic configurations are visited in the actual annealing process in order to eventually reach the minimum energy state, in SA highly non-optimal configurations are visited in order to find otherwise inaccessible global minima. The SA algorithm produces a Markov chain of points in the design space at each temperature, with a monotonically decreasing temperature. A random point is started upon, and the objective function is evaluated at that point. A stochastic perturbation is then made to the parameters of the point to arrive at a proposed new point in the design space, at which the objection function is evaluated as well. If the change in objective function values (Delta)E is negative, the proposed new point is accepted. If (Delta)E is positive, the proposed new point is accepted according to the Metropolis criterion: rho((Delta)f) = exp((-Delta)E/T), where T is the temperature for the current Markov chain. The process then repeats for the remainder of the Markov chain, after which the temperature is
Optimizing nanophotonic cavity designs with the gravitational search algorithm.
Saucer, Timothy W; Sih, Vanessa
2013-09-09
Designing photonic crystal cavities with high quality factors and low mode volumes is of great importance for maximizing interactions of light and matter in metamaterials. Previous work on photonic crystal cavities has revealed dramatic improvements in performance by fine-tuning the device design. In L3 cavities, slight shifts of the holes on the edge of the cavity have been found to greatly increase quality factors without significantly altering the mode volume. Here we demonstrate utilizing a nature inspired search algorithm to efficiently explore a large parameter space. The results converge upon a new cavity model with a high quality factor to mode volume ratio (Q/V = 798,000 (λ/n)(-3)).
Optimal Design of RF Energy Harvesting Device Using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Mori, T.; Sato, Y.; Adriano, R.; Igarashi, H.
2015-11-01
This paper presents optimal design of an RF energy harvesting device using genetic algorithm (GA). In the present RF harvester, a planar spiral antenna (PSA) is loaded with matching and rectifying circuits. On the first stage of the optimal design, the shape parameters of PSA are optimized using . Then, the equivalent circuit of the optimized PSA is derived for optimization of the circuits. Finally, the parameters of RF energy harvesting circuit are optimized to maximize the output power using GA. It is shown that the present optimization increases the output power by a factor of five. The manufactured energy harvester starts working when the input electric field is greater than 0.5 V/m.
Optimal robust motion controller design using multiobjective genetic algorithm.
Sarjaš, Andrej; Svečko, Rajko; Chowdhury, Amor
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm-differential evolution.
Mechanical design of the Mars Pathfinder mission
NASA Technical Reports Server (NTRS)
Eisen, Howard Jay; Buck, Carl W.; Gillis-Smith, Greg R.; Umland, Jeffrey W.
1997-01-01
The Mars Pathfinder mission and the Sojourner rover is reported on, with emphasis on the various mission steps and the performance of the technologies involved. The mechanical design of mission hardware was critical to the success of the entry sequence and the landing operations. The various mechanisms employed are considered.
A Parallel Genetic Algorithm for Automated Electronic Circuit Design
NASA Technical Reports Server (NTRS)
Long, Jason D.; Colombano, Silvano P.; Haith, Gary L.; Stassinopoulos, Dimitris
2000-01-01
Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency
The Mechanism Design Approach to Student Assignment
ERIC Educational Resources Information Center
Pathak, Parag A.
2011-01-01
The mechanism design approach to student assignment involves the theoretical, empirical, and experimental study of systems used to allocate students into schools around the world. Recent practical experience designing systems for student assignment has raised new theoretical questions for the theory of matching and assignment. This article reviews…
The Mechanism Design Approach to Student Assignment
ERIC Educational Resources Information Center
Pathak, Parag A.
2011-01-01
The mechanism design approach to student assignment involves the theoretical, empirical, and experimental study of systems used to allocate students into schools around the world. Recent practical experience designing systems for student assignment has raised new theoretical questions for the theory of matching and assignment. This article reviews…
Design Optimization of an Axial Fan Blade Through Multi-Objective Evolutionary Algorithm
NASA Astrophysics Data System (ADS)
Kim, Jin-Hyuk; Choi, Jae-Ho; Husain, Afzal; Kim, Kwang-Yong
2010-06-01
This paper presents design optimization of an axial fan blade with hybrid multi-objective evolutionary algorithm (hybrid MOEA). Reynolds-averaged Navier-Stokes equations with shear stress transport turbulence model are discretized by the finite volume approximations and solved on hexahedral grids for the flow analyses. The validation of the numerical results was performed with the experimental data for the axial and tangential velocities. Six design variables related to the blade lean angle and blade profile are selected and the Latin hypercube sampling of design of experiments is used to generate design points within the selected design space. Two objective functions namely total efficiency and torque are employed and the multi-objective optimization is carried out to enhance total efficiency and to reduce the torque. The flow analyses are performed numerically at the designed points to obtain values of the objective functions. The Non-dominated Sorting of Genetic Algorithm (NSGA-II) with ɛ -constraint strategy for local search coupled with surrogate model is used for multi-objective optimization. The Pareto-optimal solutions are presented and trade-off analysis is performed between the two competing objectives in view of the design and flow constraints. It is observed that total efficiency is enhanced and torque is decreased as compared to the reference design by the process of multi-objective optimization. The Pareto-optimal solutions are analyzed to understand the mechanism of the improvement in the total efficiency and reduction in torque.
Mechanism design of continuous infrared lens
NASA Astrophysics Data System (ADS)
Su, Yan-qin; Zhang, Jing-xu; Lv, Tian-yu; Yang, Fei; Wang, Fu-guo
2013-09-01
With the development of infrared technology and material, infrared zoom system is playing an important role in the field of photoelectric observation, the demand of infrared systems is increasing rapidly. In order to satisfy the requirement of infrared tracking imaging requirements of a car optoelectronic devices, different kinds of mechanical structure has been discussed, finally, according to the character of the optical design result, cam mechanism is adopted in zoom mechanism design, ball screw has been used in focusing mechanism design. As is known to all, cam is the key part in zoom system, the static, dynamic and thermal characteristics of the cam make great effect on the system performance because of the greater impact of the car's shaking and a larger range of temperature changes, as a result, the FEM analysis is necessary. The static performance is all right obtained by the finite element analysis results, the cam's first -order natural frequency is 97.56 Hz by modal analysis, the deformation of cam in the temperature difference of 80 °C is no more than 0. 003 mm by thermal analysis, which means the mechanical performance of the cam is fine. at last, the focusing mechanism has been designed, and analysis of focusing mechanism precision and encoder theoretical resolving power has been done, this mechanism has the advantages of simple transmission chain and low friction, as well as reducing the transmission error, an absolute encoder is chosen to detect the displacement of the focusing mechanism, the focusing precision is 5μm, the encoder theoretical resolving power is 0.015μm. In addition, the measurements on how to suppress stray radiation have been put forward. The experiment afterward showed that the infrared zoom system performs well, which provides lot of experience in infrared zoom system design and adjustment.
Resizing procedure for optimum design of structures under combined mechanical and thermal loading
NASA Technical Reports Server (NTRS)
Adelman, H. M.; Narayanaswami, R.
1976-01-01
An algorithm is reported for resizing structures subjected to combined thermal and mechanical loading. The algorithm is applicable to uniaxial stress elements (rods) and membrane biaxial stress members. Thermal Fully Stressed Design (TFSD) is based on the basic difference between mechanical and thermal stresses in their response to resizing. The TFSD technique is found to converge in fewer iterations than ordinary fully stressed design for problems where thermal stresses are comparable to the mechanical stresses. The improved convergence is demonstrated by example with a study of a simplified wing structure, built-up with rods and membranes and subjected to a combination of mechanical loads and a three dimensional temperature distribution.
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.
Algorithm design for a gun simulator based on image processing
NASA Astrophysics Data System (ADS)
Liu, Yu; Wei, Ping; Ke, Jun
2015-08-01
In this paper, an algorithm is designed for shooting games under strong background light. Six LEDs are uniformly distributed on the edge of a game machine screen. They are located at the four corners and in the middle of the top and the bottom edges. Three LEDs are enlightened in the odd frames, and the other three are enlightened in the even frames. A simulator is furnished with one camera, which is used to obtain the image of the LEDs by applying inter-frame difference between the even and odd frames. In the resulting images, six LED are six bright spots. To obtain the LEDs' coordinates rapidly, we proposed a method based on the area of the bright spots. After calibrating the camera based on a pinhole model, four equations can be found using the relationship between the image coordinate system and the world coordinate system with perspective transformation. The center point of the image of LEDs is supposed to be at the virtual shooting point. The perspective transformation matrix is applied to the coordinate of the center point. Then we can obtain the virtual shooting point's coordinate in the world coordinate system. When a game player shoots a target about two meters away, using the method discussed in this paper, the calculated coordinate error is less than ten mm. We can obtain 65 coordinate results per second, which meets the requirement of a real-time system. It proves the algorithm is reliable and effective.
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-Based Seismic Design of Steel Frames Utilizing Colliding Bodies Algorithm
Veladi, H.
2014-01-01
A pushover analysis method based on semirigid connection concept is developed and the colliding bodies optimization algorithm is employed to find optimum seismic design of frame structures. Two numerical examples from the literature are studied. The results of the new algorithm are compared to the conventional design methods to show the power or weakness of the algorithm. PMID:25202717
Performance-based seismic design of steel frames utilizing colliding bodies algorithm.
Veladi, H
2014-01-01
A pushover analysis method based on semirigid connection concept is developed and the colliding bodies optimization algorithm is employed to find optimum seismic design of frame structures. Two numerical examples from the literature are studied. The results of the new algorithm are compared to the conventional design methods to show the power or weakness of the algorithm.
NASA Astrophysics Data System (ADS)
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
Controller design based on μ analysis and PSO algorithm.
Lari, Ali; Khosravi, Alireza; Rajabi, Farshad
2014-03-01
In this paper an evolutionary algorithm is employed to address the controller design problem based on μ analysis. Conventional solutions to μ synthesis problem such as D-K iteration method often lead to high order, impractical controllers. In the proposed approach, a constrained optimization problem based on μ analysis is defined and then an evolutionary approach is employed to solve the optimization problem. The goal is to achieve a more practical controller with lower order. A benchmark system named two-tank system is considered to evaluate performance of the proposed approach. Simulation results show that the proposed controller performs more effective than high order H(∞) controller and has close responses to the high order D-K iteration controller as the common solution to μ synthesis problem. © 2013 ISA Published by ISA All rights reserved.
Microfluidic serpentine antennas with designed mechanical tunability.
Huang, YongAn; Wang, Yezhou; Xiao, Lin; Liu, Huimin; Dong, Wentao; Yin, Zhouping
2014-11-07
This paper describes the design and characterization of microfluidic serpentine antennas with reversible stretchability and designed mechanical frequency modulation (FM). The microfluidic antennas are designed based on the Poisson's ratio of the elastomer in which the liquid alloy antenna is embedded, to controllably decrease, stabilize or increase its resonance frequency when being stretched. Finite element modelling was used in combination with experimental verification to investigate the effects of substrate dimensions and antenna aspect ratios on the FM sensitivity to uniaxial stretching. It could be designed within the range of -1.2 to 0.6 GHz per 100% stretch. When the aspect ratio of the serpentine antenna is between 1.0 and 1.5, the resonance frequency is stable under stretching, bending, and twisting. The presented microfluidic serpentine antenna design could be utilized in the field of wireless mobile communication for the design of wearable electronics, with a stable resonance frequency under dynamic applied strain up to 50%.
The design of aerial camera focusing mechanism
NASA Astrophysics Data System (ADS)
Hu, Changchang; Yang, Hongtao; Niu, Haijun
2015-10-01
In order to ensure the imaging resolution of aerial camera and compensating defocusing caused by the changing of atmospheric temperature, pressure, oblique photographing distance and other environmental factor [1,2], and to meeting the overall design requirements of the camera for the lower mass and smaller size , the linear focusing mechanism is designed. Through the target surface support, the target surface component is connected with focusing driving mechanism. Make use of precision ball screws, focusing mechanism transforms the input rotary motion of motor into linear motion of the focal plane assembly. Then combined with the form of linear guide restraint movement, the magnetic encoder is adopted to detect the response of displacement. And the closed loop control is adopted to realize accurate focusing. This paper illustrated the design scheme for a focusing mechanism and analyzed its error sources. It has the advantages of light friction and simple transmission chain and reducing the transmission error effectively. And this paper also analyses the target surface by finite element analysis and lightweight design. Proving that the precision of focusing mechanism can achieve higher than 3um, and the focusing range is +/-2mm.
Mars rover mechanisms designed for Rocky 4
NASA Technical Reports Server (NTRS)
Rivellini, Tommaso P.
1993-01-01
A Mars rover prototype vehicle named Rocky 4 was designed and built at JPL during the fall of 1991 and spring 1992. This vehicle is the fourth in a series of rovers designed to test vehicle mobility and navigation software. Rocky 4 was the first attempt to design a vehicle with 'flight like' mass and functionality. It was consequently necessary to develop highly efficient mechanisms and structures to meet the vehicles very tight mass limit of 3 Kg for the entire mobility system (7 Kg for the full system). This paper will discuss the key mechanisms developed for the rover's innovative drive and suspension system. These are the wheel drive and strut assembly, the rocker-bogie suspension mechanism and the differential pivot. The end-to-end design, analysis, fabrication and testing of these components will also be discussed as will their performance during field testing. The lessons learned from Rocky 4 are already proving invaluable for the design of Rocky 6. Rocky 6 is currently being designed to fly on NASA's MESUR mission to Mars scheduled to launch in 1996.
Development of hybrid genetic algorithms for product line designs.
Balakrishnan, P V Sundar; Gupta, Rakesh; Jacob, Varghese S
2004-02-01
In this paper, we investigate the efficacy of artificial intelligence (AI) based meta-heuristic techniques namely genetic algorithms (GAs), for the product line design problem. This work extends previously developed methods for the single product design problem. We conduct a large scale simulation study to determine the effectiveness of such an AI based technique for providing good solutions and bench mark the performance of this against the current dominant approach of beam search (BS). We investigate the potential advantages of pursuing the avenue of developing hybrid models and then implement and study such hybrid models using two very distinct approaches: namely, seeding the initial GA population with the BS solution, and employing the BS solution as part of the GA operator's process. We go on to examine the impact of two alternate string representation formats on the quality of the solutions obtained by the above proposed techniques. We also explicitly investigate a critical managerial factor of attribute importance in terms of its impact on the solutions obtained by the alternate modeling procedures. The alternate techniques are then evaluated, using statistical analysis of variance, on a fairy large number of data sets, as to the quality of the solutions obtained with respect to the state-of-the-art benchmark and in terms of their ability to provide multiple, unique product line options.
A homogeneous superconducting magnet design using a hybrid optimization algorithm
NASA Astrophysics Data System (ADS)
Ni, Zhipeng; Wang, Qiuliang; Liu, Feng; Yan, Luguang
2013-12-01
This paper employs a hybrid optimization algorithm with a combination of linear programming (LP) and nonlinear programming (NLP) to design the highly homogeneous superconducting magnets for magnetic resonance imaging (MRI). The whole work is divided into two stages. The first LP stage provides a global optimal current map with several non-zero current clusters, and the mathematical model for the LP was updated by taking into account the maximum axial and radial magnetic field strength limitations. In the second NLP stage, the non-zero current clusters were discretized into practical solenoids. The superconducting conductor consumption was set as the objective function both in the LP and NLP stages to minimize the construction cost. In addition, the peak-peak homogeneity over the volume of imaging (VOI), the scope of 5 Gauss fringe field, and maximum magnetic field strength within superconducting coils were set as constraints. The detailed design process for a dedicated 3.0 T animal MRI scanner was presented. The homogeneous magnet produces a magnetic field quality of 6.0 ppm peak-peak homogeneity over a 16 cm by 18 cm elliptical VOI, and the 5 Gauss fringe field was limited within a 1.5 m by 2.0 m elliptical region.
Design of infrasound-detection system via adaptive LMSTDE algorithm
NASA Technical Reports Server (NTRS)
Khalaf, C. S.; Stoughton, J. W.
1984-01-01
A proposed solution to an aviation safety problem is based on passive detection of turbulent weather phenomena through their infrasonic emission. This thesis describes a system design that is adequate for detection and bearing evaluation of infrasounds. An array of four sensors, with the appropriate hardware, is used for the detection part. Bearing evaluation is based on estimates of time delays between sensor outputs. The generalized cross correlation (GCC), as the conventional time-delay estimation (TDE) method, is first reviewed. An adaptive TDE approach, using the least mean square (LMS) algorithm, is then discussed. A comparison between the two techniques is made and the advantages of the adaptive approach are listed. The behavior of the GCC, as a Roth processor, is examined for the anticipated signals. It is shown that the Roth processor has the desired effect of sharpening the peak of the correlation function. It is also shown that the LMSTDE technique is an equivalent implementation of the Roth processor in the time domain. A LMSTDE lead-lag model, with a variable stability coefficient and a convergence criterion, is designed.
Optimal Robust Motion Controller Design Using Multiobjective Genetic Algorithm
Svečko, Rajko
2014-01-01
This paper describes the use of a multiobjective genetic algorithm for robust motion controller design. Motion controller structure is based on a disturbance observer in an RIC framework. The RIC approach is presented in the form with internal and external feedback loops, in which an internal disturbance rejection controller and an external performance controller must be synthesised. This paper involves novel objectives for robustness and performance assessments for such an approach. Objective functions for the robustness property of RIC are based on simple even polynomials with nonnegativity conditions. Regional pole placement method is presented with the aims of controllers' structures simplification and their additional arbitrary selection. Regional pole placement involves arbitrary selection of central polynomials for both loops, with additional admissible region of the optimized pole location. Polynomial deviation between selected and optimized polynomials is measured with derived performance objective functions. A multiobjective function is composed of different unrelated criteria such as robust stability, controllers' stability, and time-performance indexes of closed loops. The design of controllers and multiobjective optimization procedure involve a set of the objectives, which are optimized simultaneously with a genetic algorithm—differential evolution. PMID:24987749
Novel design solutions for fishing reel mechanisms
NASA Astrophysics Data System (ADS)
Lovasz, Erwin-Christian; Modler, Karl-Heinz; Neumann, Rudolf; Gruescu, Corina Mihaela; Perju, Dan; Ciupe, Valentin; Maniu, Inocentiu
2015-07-01
Currently, there are various reels on the market regarding the type of mechanism, which achieves the winding and unwinding of the line. The designers have the purpose of obtaining a linear transmission function, by means of a simple and small-sized mechanism. However, the present solutions are not satisfactory because of large deviations from linearity of the transmission function and complexity of mechanical schema. A novel solution for the reel spool mechanism is proposed. Its kinematic schema and synthesis method are described. The kinematic schema of the chosen mechanism is based on a noncircular gear in series with a scotch-yoke mechanism. The yoke is driven by a stud fixed on the driving noncircular gear. The drawbacks of other models regarding the effects occurring at the ends of the spool are eliminated through achieving an appropriate transmission function of the spool. The linear function approximation with curved end-arches appropriately computed to ensure mathematical continuity is very good. The experimental results on the mechanism model validate the theoretical approach. The developed mechanism solution is recorded under a reel spool mechanism patent.
An advancing front Delaunay triangulation algorithm designed for robustness
NASA Technical Reports Server (NTRS)
Mavriplis, D. J.
1993-01-01
A new algorithm is described for generating an unstructured mesh about an arbitrary two-dimensional configuration. Mesh points are generated automatically by the algorithm in a manner which ensures a smooth variation of elements, and the resulting triangulation constitutes the Delaunay triangulation of these points. The algorithm combines the mathematical elegance and efficiency of Delaunay triangulation algorithms with the desirable point placement features, boundary integrity, and robustness traditionally associated with advancing-front-type mesh generation strategies. The method offers increased robustness over previous algorithms in that it cannot fail regardless of the initial boundary point distribution and the prescribed cell size distribution throughout the flow-field.
An advancing front Delaunay triangulation algorithm designed for robustness
NASA Technical Reports Server (NTRS)
Mavriplis, D. J.
1992-01-01
A new algorithm is described for generating an unstructured mesh about an arbitrary two-dimensional configuration. Mesh points are generated automatically by the algorithm in a manner which ensures a smooth variation of elements, and the resulting triangulation constitutes the Delaunay triangulation of these points. The algorithm combines the mathematical elegance and efficiency of Delaunay triangulation algorithms with the desirable point placement features, boundary integrity, and robustness traditionally associated with advancing-front-type mesh generation strategies. The method offers increased robustness over previous algorithms in that it cannot fail regardless of the initial boundary point distribution and the prescribed cell size distribution throughout the flow-field.
Flight telerobot mechanism design: Problems and challenges
NASA Technical Reports Server (NTRS)
Dahlgren, John B.; Kan, Edwin P.
1989-01-01
Problems and challenges of designing flight telerobot mechanisms are discussed. Specific experiences are drawn from the following system developments: (1) the Force Reflecting Hand Controller, (2) the Smart End Effector, (3) the force-torque sensor, and a generic multi-degrees-of-freedom manipulator.
Combinatorial design of textured mechanical metamaterials.
Coulais, Corentin; Teomy, Eial; de Reus, Koen; Shokef, Yair; van Hecke, Martin
2016-07-28
The structural complexity of metamaterials is limitless, but, in practice, most designs comprise periodic architectures that lead to materials with spatially homogeneous features. More advanced applications in soft robotics, prosthetics and wearable technology involve spatially textured mechanical functionality, which requires aperiodic architectures. However, a naive implementation of such structural complexity invariably leads to geometrical frustration (whereby local constraints cannot be satisfied everywhere), which prevents coherent operation and impedes functionality. Here we introduce a combinatorial strategy for the design of aperiodic, yet frustration-free, mechanical metamaterials that exhibit spatially textured functionalities. We implement this strategy using cubic building blocks-voxels-that deform anisotropically, a local stacking rule that allows cooperative shape changes by guaranteeing that deformed building blocks fit together as in a three-dimensional jigsaw puzzle, and three-dimensional printing. These aperiodic metamaterials exhibit long-range holographic order, whereby the two-dimensional pixelated surface texture dictates the three-dimensional interior voxel arrangement. They also act as programmable shape-shifters, morphing into spatially complex, but predictable and designable, shapes when uniaxially compressed. Finally, their mechanical response to compression by a textured surface reveals their ability to perform sensing and pattern analysis. Combinatorial design thus opens up a new avenue towards mechanical metamaterials with unusual order and machine-like functionalities.
Design considerations for mechanical face seals
NASA Technical Reports Server (NTRS)
Ludwig, L. P.; Greiner, H. F.
1980-01-01
Two companion reports deal with design considerations for improving performance of mechanical face seals, one of family of devices used in general area of fluid sealing of rotating shafts. One report deals with basic seal configuration and other with lubrication of seal.
Combinatorial design of textured mechanical metamaterials
NASA Astrophysics Data System (ADS)
Coulais, Corentin; Teomy, Eial; de Reus, Koen; Shokef, Yair; van Hecke, Martin
2016-07-01
The structural complexity of metamaterials is limitless, but, in practice, most designs comprise periodic architectures that lead to materials with spatially homogeneous features. More advanced applications in soft robotics, prosthetics and wearable technology involve spatially textured mechanical functionality, which requires aperiodic architectures. However, a naive implementation of such structural complexity invariably leads to geometrical frustration (whereby local constraints cannot be satisfied everywhere), which prevents coherent operation and impedes functionality. Here we introduce a combinatorial strategy for the design of aperiodic, yet frustration-free, mechanical metamaterials that exhibit spatially textured functionalities. We implement this strategy using cubic building blocks—voxels—that deform anisotropically, a local stacking rule that allows cooperative shape changes by guaranteeing that deformed building blocks fit together as in a three-dimensional jigsaw puzzle, and three-dimensional printing. These aperiodic metamaterials exhibit long-range holographic order, whereby the two-dimensional pixelated surface texture dictates the three-dimensional interior voxel arrangement. They also act as programmable shape-shifters, morphing into spatially complex, but predictable and designable, shapes when uniaxially compressed. Finally, their mechanical response to compression by a textured surface reveals their ability to perform sensing and pattern analysis. Combinatorial design thus opens up a new avenue towards mechanical metamaterials with unusual order and machine-like functionalities.
Design definition of a mechanical capacitor
NASA Technical Reports Server (NTRS)
Michaelis, T. D.; Schlieban, E. W.; Scott, R. D.
1977-01-01
A design study and analyses of a 10 kW-hr, 15 kW mechanical capacitor system was studied. It was determined that magnetically supported wheels constructed of advanced composites have the potential for high energy density and high power density. Structural concepts are analyzed that yield the highest energy density of any structural design yet reported. Particular attention was paid to the problem of 'friction' caused by magnetic and I to the second power R losses in the suspension and motor-generator subsystems, and low design friction levels have been achieved. The potentially long shelf life of this system, and the absence of wearing parts, provide superior performance over conventional flywheels supported with mechanical bearings. Costs and economies of energy storage wheels were reviewed briefly.
AHTR Mechanical, Structural, And Neutronic Preconceptual Design
Varma, Venugopal Koikal; Holcomb, David Eugene; Peretz, Fred J; Bradley, Eric Craig; Ilas, Dan; Qualls, A L; Zaharia, Nathaniel M
2012-10-01
This report provides an overview of the mechanical, structural, and neutronic aspects of the Advanced High Temperature Reactor (AHTR) design concept. The AHTR is a design concept for a large output Fluoride salt cooled High-temperature Reactor (FHR) that is being developed to enable evaluation of the technology hurdles remaining to be overcome prior to FHRs becoming a commercial reactor class. This report documents the incremental AHTR design maturation performed over the past year and is focused on advancing the design concept to a level of a functional, self-consistent system. The AHTR employs plate type coated particle fuel assemblies with rapid, off-line refueling. Neutronic analysis of the core has confirmed the viability of a 6-month 2-batch cycle with 9 weight-percent enriched uranium fuel. Refueling is intended to be performed automatically under visual guidance using dedicated robotic manipulators. The present design intent is for used fuel to be stored inside of containment for at least 6 months and then transferred to local dry wells for intermediate term, on-site storage. The mechanical and structural concept development effort has included an emphasis on transportation and constructability to minimize construction costs and schedule. The design intent is that all components be factory fabricated into rail transportable modules that are assembled into subsystems at an on-site workshop prior to being lifted into position using a heavy-lift crane in an open-top style construction. While detailed accident identification and response sequence analysis has yet to be performed, the design concept incorporates multiple levels of radioactive material containment including fully passive responses to all identified design basis or non-very-low frequency beyond design basis accidents. Key building design elements include: 1) below grade siting to minimize vulnerability to aircraft impact, 2) multiple natural circulation decay heat rejection chimneys, 3) seismic
Optimization design of satellite separation systems based on Multi-Island Genetic Algorithm
NASA Astrophysics Data System (ADS)
Hu, Xingzhi; Chen, Xiaoqian; Zhao, Yong; Yao, Wen
2014-03-01
The separation systems are crucial for the launch of satellites. With respect to the existing design issues of satellite separation systems, an optimization design approach based on Multi-Island Genetic Algorithm is proposed, and a hierarchical optimization of system mass and separation angular velocity is designed. Multi-Island Genetic Algorithm is studied for the problem and the optimization parameters are discussed. Dynamic analysis of ADAMS used to validate the designs is integrated with iSIGHT. Then the optimization method is employed for a typical problem using the helical compression spring mechanism, and the corresponding objective functions are derived. It turns out that the mass of compression spring catapult is decreased by 30.7% after optimization and the angular velocity can be minimized considering spring stiffness errors. Moreover, ground tests and on-orbit flight indicate that the error of separation speed is controlled within 1% and the angular velocity is reduced by nearly 90%, which proves the design result and the optimization approach.
Lapidoth, Gideon D.; Baran, Dror; Pszolla, Gabriele M.; Norn, Christoffer; Alon, Assaf; Tyka, Michael D.; Fleishman, Sarel J.
2016-01-01
Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function – essential to exert control over all polypeptide degrees of freedom – remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in six the backbone conformation at the core of the antibody binding surface is similar to the natural antibody targets, and in several cases sequence and sidechain conformations recapitulate those seen in the natural antibodies. In the case of an anti-lysozyme antibody, designed antibody CDRs at the periphery of the interface, such as L1 and H2, show a greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, which could enhance affinity and specificity. PMID:25670500
NASA Astrophysics Data System (ADS)
Kanagaraj, G.; Ponnambalam, S. G.; Jawahar, N.; Mukund Nilakantan, J.
2014-10-01
This article presents an effective hybrid cuckoo search and genetic algorithm (HCSGA) for solving engineering design optimization problems involving problem-specific constraints and mixed variables such as integer, discrete and continuous variables. The proposed algorithm, HCSGA, is first applied to 13 standard benchmark constrained optimization functions and subsequently used to solve three well-known design problems reported in the literature. The numerical results obtained by HCSGA show competitive performance with respect to recent algorithms for constrained design optimization problems.
Target Impact Detection Algorithm Using Computer-aided Design (CAD) Model Geometry
2014-09-01
UNCLASSIFIED AD-E403 558 Technical Report ARMET-TR-13024 TARGET IMPACT DETECTION ALGORITHM USING COMPUTER-AIDED DESIGN ( CAD ...DETECTION ALGORITHM USING COMPUTER-AIDED DESIGN ( CAD ) MODEL GEOMETRY 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...This report documents a method and algorithm to export geometry from a three-dimensional, computer-aided design ( CAD ) model in a format that can be
NASA Astrophysics Data System (ADS)
Mallick, Rajnish; Ganguli, Ranjan; Kumar, Ravi
2017-05-01
The optimized design of a smart post-buckled beam actuator (PBA) is performed in this study. A smart material based piezoceramic stack actuator is used as a prime-mover to drive the buckled beam actuator. Piezoceramic actuators are high force, small displacement devices; they possess high energy density and have high bandwidth. In this study, bench top experiments are conducted to investigate the angular tip deflections due to the PBA. A new design of a linear-to-linear motion amplification device (LX-4) is developed to circumvent the small displacement handicap of piezoceramic stack actuators. LX-4 enhances the piezoceramic actuator mechanical leverage by a factor of four. The PBA model is based on dynamic elastic stability and is analyzed using the Mathieu-Hill equation. A formal optimization is carried out using a newly developed meta-heuristic nature inspired algorithm, named as the bat algorithm (BA). The BA utilizes the echolocation capability of bats. An optimized PBA in conjunction with LX-4 generates end rotations of the order of 15° at the output end. The optimized PBA design incurs less weight and induces large end rotations, which will be useful in development of various mechanical and aerospace devices, such as helicopter trailing edge flaps, micro and nano aerial vehicles and other robotic systems.
Computational Design of Animated Mechanical Characters
NASA Astrophysics Data System (ADS)
Coros, Stelian; Thomaszewski, Bernhard; DRZ Team Team
2014-03-01
A factor key to the appeal of modern CG movies and video-games is that the virtual worlds they portray place no bounds on what can be imagined. Rapid manufacturing devices hold the promise of bringing this type of freedom to our own world, by enabling the fabrication of physical objects whose appearance, deformation behaviors and motions can be precisely specified. In order to unleash the full potential of this technology however, computational design methods that create digital content suitable for fabrication need to be developed. In recent work, we presented a computational design system that allows casual users to create animated mechanical characters. Given an articulated character as input, the user designs the animated character by sketching motion curves indicating how they should move. For each motion curve, our framework creates an optimized mechanism that reproduces it as closely as possible. The resulting mechanisms are attached to the character and then connected to each other using gear trains, which are created in a semi-automated fashion. The mechanical assemblies generated with our system can be driven with a single input driver, such as a hand-operated crank or an electric motor, and they can be fabricated using rapid prototyping devices.
Parallel algorithms for placement and routing in VLSI design. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Brouwer, Randall Jay
1991-01-01
The computational requirements for high quality synthesis, analysis, and verification of very large scale integration (VLSI) designs have rapidly increased with the fast growing complexity of these designs. Research in the past has focused on the development of heuristic algorithms, special purpose hardware accelerators, or parallel algorithms for the numerous design tasks to decrease the time required for solution. Two new parallel algorithms are proposed for two VLSI synthesis tasks, standard cell placement and global routing. The first algorithm, a parallel algorithm for global routing, uses hierarchical techniques to decompose the routing problem into independent routing subproblems that are solved in parallel. Results are then presented which compare the routing quality to the results of other published global routers and which evaluate the speedups attained. The second algorithm, a parallel algorithm for cell placement and global routing, hierarchically integrates a quadrisection placement algorithm, a bisection placement algorithm, and the previous global routing algorithm. Unique partitioning techniques are used to decompose the various stages of the algorithm into independent tasks which can be evaluated in parallel. Finally, results are presented which evaluate the various algorithm alternatives and compare the algorithm performance to other placement programs. Measurements are presented on the parallel speedups available.
Lapidoth, Gideon D; Baran, Dror; Pszolla, Gabriele M; Norn, Christoffer; Alon, Assaf; Tyka, Michael D; Fleishman, Sarel J
2015-08-01
Computational design of protein function has made substantial progress, generating new enzymes, binders, inhibitors, and nanomaterials not previously seen in nature. However, the ability to design new protein backbones for function--essential to exert control over all polypeptide degrees of freedom--remains a critical challenge. Most previous attempts to design new backbones computed the mainchain from scratch. Here, instead, we describe a combinatorial backbone and sequence optimization algorithm called AbDesign, which leverages the large number of sequences and experimentally determined molecular structures of antibodies to construct new antibody models, dock them against target surfaces and optimize their sequence and backbone conformation for high stability and binding affinity. We used the algorithm to produce antibody designs that target the same molecular surfaces as nine natural, high-affinity antibodies; in five cases interface sequence identity is above 30%, and in four of those the backbone conformation at the core of the antibody binding surface is within 1 Å root-mean square deviation from the natural antibodies. Designs recapitulate polar interaction networks observed in natural complexes, and amino acid sidechain rigidity at the designed binding surface, which is likely important for affinity and specificity, is high compared to previous design studies. In designed anti-lysozyme antibodies, complementarity-determining regions (CDRs) at the periphery of the interface, such as L1 and H2, show greater backbone conformation diversity than the CDRs at the core of the interface, and increase the binding surface area compared to the natural antibody, potentially enhancing affinity and specificity.
An implementable algorithm for the optimal design centering, tolerancing, and tuning problem
Polak, E.
1982-05-01
An implementable master algorithm for solving optimal design centering, tolerancing, and tuning problems is presented. This master algorithm decomposes the original nondifferentiable optimization problem into a sequence of ordinary nonlinear programming problems. The master algorithm generates sequences with accumulation points that are feasible and satisfy a new optimality condition, which is shown to be stronger than the one previously used for these problems.
Design and realization of disaster assessment algorithm after forest fire
NASA Astrophysics Data System (ADS)
Xu, Aijun; Wang, Danfeng; Tang, Lihua
2008-10-01
Based on GIS technology, this paper mainly focuses on the application of disaster assessment algorithm after forest fire and studies on the design and realization of disaster assessment based on GIS. After forest fire through the analysis and processing of multi-sources and heterogeneous data, this paper integrates the foundation that the domestic and foreign scholars laid of the research on assessment for forest fire loss with the related knowledge of assessment, accounting and forest resources appraisal so as to study and approach the theory framework and assessment index of the research on assessment for forest fire loss. The technologies of extracting boundary, overlay analysis, and division processing of multi-sources spatial data are available to realize the application of the investigation method of the burnt forest area and the computation of the fire area. The assessment provides evidence for fire cleaning in burnt areas and new policy making on restoration in terms of the direct and the indirect economic loss and ecological and environmental damage caused by forest fire under the condition of different fire danger classes and different amounts of forest accumulation, thus makes forest resources protection operated in a faster, more efficient and more economical way. Finally, this paper takes Lin'an city of Zhejiang province as a test area to confirm the method mentioned in the paper in terms of key technologies.
NASA Astrophysics Data System (ADS)
Tancret, F.
2013-06-01
A new alloy design procedure is proposed, combining in a single computational tool several modelling and predictive techniques that have already been used and assessed in the field of materials science and alloy design: a genetic algorithm is used to optimize the alloy composition for target properties and performance on the basis of the prediction of mechanical properties (estimated by Gaussian process regression of data on existing alloys) and of microstructural constitution, stability and processability (evaluated by computational themodynamics). These tools are integrated in a unique Matlab programme. An example is given in the case of the design of a new nickel-base superalloy for future power plant applications (such as the ultra-supercritical (USC) coal-fired plant, or the high-temperature gas-cooled nuclear reactor (HTGCR or HTGR), where the selection criteria include cost, oxidation and creep resistance around 750 °C, long-term stability at service temperature, forgeability, weldability, etc.
Mechanical engineering capstone senior design textbook
NASA Astrophysics Data System (ADS)
Barrett, Rolin Farrar, Jr.
This textbook is intended to bridge the gap between mechanical engineering equations and mechanical engineering design. To that end, real-world examples are used throughout the book. Also, the material is presented in an order that follows the chronological sequence of coursework that must be performed by a student in the typical capstone senior design course in mechanical engineering. In the process of writing this book, the author surveyed the fifty largest engineering schools (as ranked by the American Society of Engineering Education, or ASEE) to determine what engineering instructors are looking for in a textbook. The survey results revealed a clear need for a textbook written expressly for the capstone senior design course as taught throughout the nation. This book is designed to meet that need. This text was written using an organizational method that the author calls the General Topics Format. The format gives the student reader rapid access to the information contained in the text. All manufacturing methods, and some other material presented in this text, have been presented using the General Topics Format. The text uses examples to explain the importance of understanding the environment in which the product will be used and to discuss product abuse. The safety content contained in this text is unique. The Safety chapter teaches engineering ethics and includes a step-by-step guide to resolving ethical conflicts. The chapter includes explanations of rules, recommendations, standards, consensus standards, key safety concepts, and the legal implications of product failure. Key design principles have been listed and explained. The text provides easy-to-follow design steps, helpful for both the student and new engineer. Prototyping is presented as consisting of three phases: organization, building, and refining. A chapter on common manufacturing methods is included for reference.
AHTR Mechanical, Structural, and Neutronic Preconceptual Design
Varma, V.K.; Holcomb, D.E.; Peretz, F.J.; Bradley, E.C.; Ilas, D.; Qualls, A.L.; Zaharia, N.M.
2012-09-15
This report provides an overview of the mechanical, structural, and neutronic aspects of the Advanced High Temperature Reactor (AHTR) design concept. The AHTR is a design concept for a large output Fluoride salt cooled High-temperature Reactor (FHR) that is being developed to enable evaluation of the technology hurdles remaining to be overcome prior to FHRs becoming an option for commercial reactor deployment. This report documents the incremental AHTR design maturation performed over the past year and is focused on advancing the design concept to a level of a functional, self-consistent system. The reactor concept development remains at a preconceptual level of maturity. While the overall appearance of an AHTR design is anticipated to be similar to the current concept, optimized dimensions will differ from those presented here. The AHTR employs plate type coated particle fuel assemblies with rapid, off-line refueling. Neutronic analysis of the core has confirmed the viability of a 6-month two-batch cycle with 9 wt. % enriched uranium fuel. Refueling is intended to be performed automatically under visual guidance using dedicated robotic manipulators. The report includes a preconceptual design of the manipulators, the fuel transfer system, and the used fuel storage system. The present design intent is for used fuel to be stored inside of containment for at least six months and then transferred to local dry wells for intermediate term, on-site storage. The mechanical and structural concept development effort has included an emphasis on transportation and constructability to minimize construction costs and schedule. The design intent is that all components be factory fabricated into rail transportable modules that are assembled into subsystems at an on-site workshop prior to being lifted into position using a heavy-lift crane in an open-top style construction. While detailed accident identification and response sequence analysis has yet to be performed, the design
Mechanical design of SERT 2 thruster system
NASA Technical Reports Server (NTRS)
Zavesky, R. J.; Hurst, E. B.
1972-01-01
The mechanical design of the mercury bombardment thruster that was tested on SERT is described. The report shows how the structural, thermal, electrical, material compatibility, and neutral mercury coating considerations affected the design and integration of the subsystems and components. The SERT 2 spacecraft with two thrusters was launched on February 3, 1970. One thruster operated for 3782 hours and the other for 2011 hours. A high voltage short resulting from buildup of loose eroded material was believed to be the cause of failure.
Degradation mechanisms and accelerated aging test design
Clough, R L; Gillen, K T
1985-01-01
The fundamental mechanisms underlying the chemical degradation of polymers can change as a function of environmental stress level. When this occurs, it greatly complicates any attempt to use accelerated tests for predicting long-term material degradation behaviors. Understanding how degradation mechanisms can change at different stress levels facilitates both the design and the interpretation of aging tests. Oxidative degradation is a predominant mechanism for many polymers exposed to a variety of different environments in the presence of air, and there are two mechanistic considerations which are widely applicable to material oxidation. One involves a physical process, oxygen diffusion, as a rate-limiting step. This mechanism can predominate at high stress levels. The second is a chemical process, the time-dependent decomposition of peroxide species. This leads to chain branching and can become a rate-controlling factor at lower stress levels involving time-scales applicable to use environments. The authors describe methods for identifying the operation of these mechanisms and illustrate the dramatic influence they can have on the degradation behaviors of a number of polymer types. Several commonly used approaches to accelerated aging tests are discussed in light of the behaviors which result from changes in degradation mechanisms. 9 references, 4 figures.
Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design
Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.
2014-01-01
In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057
Hybrid algorithms for fuzzy reverse supply chain network design.
Che, Z H; Chiang, Tzu-An; Kuo, Y C; Cui, Zhihua
2014-01-01
In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods.
Mechanism Design for Incentivizing Social Media Contributions
NASA Astrophysics Data System (ADS)
Singh, Vivek K.; Jain, Ramesh; Kankanhalli, Mohan
Despite recent advancements in user-driven social media platforms, tools for studying user behavior patterns and motivations remain primitive. We highlight the voluntary nature of user contributions and that users can choose when (and when not) to contribute to the common media pool. A Game theoretic framework is proposed to study the dynamics of social media networks where contribution costs are individual but gains are common. We model users as rational selfish agents, and consider domain attributes like voluntary participation, virtual reward structure, network effect, and public-sharing to model the dynamics of this interaction. The created model describes the most appropriate contribution strategy from each user's perspective and also highlights issues like 'free-rider' problem and individual rationality leading to irrational (i.e. sub-optimal) group behavior. We also consider the perspective of the system designer who is interested in finding the best incentive mechanisms to influence the selfish end-users so that the overall system utility is maximized. We propose and compare multiple mechanisms (based on optimal bonus payment, social incentive leveraging, and second price auction) to study how a system designer can exploit the selfishness of its users, to design incentive mechanisms which improve the overall task-completion probability and system performance, while possibly still benefiting the individual users.
Advanced tribology design tools for space mechanisms
NASA Astrophysics Data System (ADS)
Roberts, E. W.; Lewis, S. D.
2001-09-01
The purpose of this paper is to report on the current status of, and updates to, three well-established ESTL/TM design aids and tools which are frequently used in the design of spacecraft mechanisms. The design aids covered are: - Space Tribology Handbook - DOLLS: a database on space oils and greases - CABARET: a ball bearing analysis code. The Space Tribology Handbook has become established as the definitive guide to space tribology. This paper reports on updates made to the Handbook and the plans to incorporate it into ECSS Guidelines. The database known as DOLLS provides the fundamental information needed for selection of a fluid lubricant for space applications. The database is being upgraded to include details on new oils and greases and, where available, new data on the characteristics of listed fluid lubricants. The bearing analysis code, CABARET, allows the prediction of bearing performance for a range of applications from low-speed mechanisms to high-speed turbo-pumps. Its predictive capabilities include torque, contact stress, stiffness thermal effects, cage motion, and fatigue life. Each design aid and its current status are discussed further.
Mechanical Design of Carbon Ion Optics
NASA Technical Reports Server (NTRS)
Haag, Thomas
2005-01-01
Carbon Ion Optics are expected to provide much longer thruster life due to their resistance to sputter erosion. There are a number of different forms of carbon that have been used for fabricating ion thruster optics. The mechanical behavior of carbon is much different than that of most metals, and poses unique design challenges. In order to minimize mission risk, the behavior of carbon must be well understood, and components designed within material limitations. Thermal expansion of the thruster structure must be compatible with thermal expansion of the carbon ion optics. Specially designed interfaces may be needed so that grid gap and aperture alignment are not adversely affected by dissimilar material properties within the thruster. The assembled thruster must be robust and tolerant of launch vibration. The following paper lists some of the characteristics of various carbon materials. Several past ion optics designs are discussed, identifying strengths and weaknesses. Electrostatics and material science are not emphasized so much as the mechanical behavior and integration of grid electrodes into an ion thruster.
Chen, Bor-Sen; Chen, Po-Wei
2010-01-01
In the past decade, the development of synthetic gene networks has attracted much attention from many researchers. In particular, the genetic oscillator known as the repressilator has become a paradigm for how to design a gene network with a desired dynamic behaviour. Even though the repressilator can show oscillatory properties in its protein concentrations, their amplitudes, frequencies and phases are perturbed by the kinetic parametric fluctuations (intrinsic molecular perturbations) and external disturbances (extrinsic molecular noises) of the environment. Therefore, how to design a robust genetic oscillator with desired amplitude, frequency and phase under stochastic intrinsic and extrinsic molecular noises is an important topic for synthetic biology. In this study, based on periodic reference signals with arbitrary amplitudes, frequencies and phases, a robust synthetic gene oscillator is designed by tuning the kinetic parameters of repressilator via a genetic algorithm (GA) so that the protein concentrations can track the desired periodic reference signals under intrinsic and extrinsic molecular noises. GA is a stochastic optimization algorithm which was inspired by the mechanisms of natural selection and evolution genetics. By the proposed GA-based design algorithm, the repressilator can track the desired amplitude, frequency and phase of oscillation under intrinsic and extrinsic noises through the optimization of fitness function. The proposed GA-based design algorithm can mimic the natural selection in evolutionary process to select adequate kinetic parameters for robust genetic oscillators. The design method can be easily extended to any synthetic gene network design with prescribed behaviours. PMID:20535234
The potential of genetic algorithms for conceptual design of rotor systems
NASA Technical Reports Server (NTRS)
Crossley, William A.; Wells, Valana L.; Laananen, David H.
1993-01-01
The capabilities of genetic algorithms as a non-calculus based, global search method make them potentially useful in the conceptual design of rotor systems. Coupling reasonably simple analysis tools to the genetic algorithm was accomplished, and the resulting program was used to generate designs for rotor systems to match requirements similar to those of both an existing helicopter and a proposed helicopter design. This provides a comparison with the existing design and also provides insight into the potential of genetic algorithms in design of new rotors.
Optimal design of low-density SNP arrays for genomic prediction: algorithm and applications
USDA-ARS?s Scientific Manuscript database
Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for their optimal design. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optim...
Lansce Wire Scanning Diagnostics Device Mechanical Design
Rodriguez Esparza, Sergio; Batygin, Yuri K.; Gilpatrick, John D.; Gruchalla, Michael E.; Maestas, Alfred J.; Pillai, Chandra; Raybun, Joseph L.; Sattler, F. D.; Sedillo, James Daniel; Smith, Brian G.
2011-01-01
The Accelerator Operations & Technology Division at Los Alamos National Laboratory operates a linear particle accelerator which utilizes 110 wire scanning diagnostics devices to gain position and intensity information of the proton beam. In the upcoming LANSCE improvements, 51 of these wire scanners are to be replaced with a new design, up-to-date technology and off-the-shelf components. This document outlines the requirements for the mechanical design of the LANSCE wire scanner and presents the recently developed linac wire scanner prototype. Additionally, this document presents the design modifications that have been implemented into the fabrication and assembly of this first linac wire scanner prototype. Also, this document will present the design for the second, third, and fourth wire scanner prototypes being developed. Prototypes 2 and 3 belong to a different section of the particle accelerator and therefore have slightly different design specifications. Prototype 4 is a modification of a previously used wire scanner in our facility. Lastly, the paper concludes with a plan for future work on the wire scanner development.
Design and implementation of intelligent electronic warfare decision making algorithm
NASA Astrophysics Data System (ADS)
Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun
2017-05-01
Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.
NASA Technical Reports Server (NTRS)
Sidik, S. M.
1973-01-01
An algorithm and computer program are presented for generating all the distinct 2(p-q) fractional factorial designs. Some applications of this algorithm to the construction of tables of designs and of designs for nonstandard situations and its use in Bayesian design are discussed. An appendix includes a discussion of an actual experiment whose design was facilitated by the algorithm.
A Nonhomogeneous Cuckoo Search Algorithm Based on Quantum Mechanism for Real Parameter Optimization.
Cheung, Ngaam J; Ding, Xue-Ming; Shen, Hong-Bin
2017-02-01
Cuckoo search (CS) algorithm is a nature-inspired search algorithm, in which all the individuals have identical search behaviors. However, this simple homogeneous search behavior is not always optimal to find the potential solution to a special problem, and it may trap the individuals into local regions leading to premature convergence. To overcome the drawback, this paper presents a new variant of CS algorithm with nonhomogeneous search strategies based on quantum mechanism to enhance search ability of the classical CS algorithm. Featured contributions in this paper include: 1) quantum-based strategy is developed for nonhomogeneous update laws and 2) we, for the first time, present a set of theoretical analyses on CS algorithm as well as the proposed algorithm, respectively, and conclude a set of parameter boundaries guaranteeing the convergence of the CS algorithm and the proposed algorithm. On 24 benchmark functions, we compare our method with five existing CS-based methods and other ten state-of-the-art algorithms. The numerical results demonstrate that the proposed algorithm is significantly better than the original CS algorithm and the rest of compared methods according to two nonparametric tests.
Analysis and optimal design of an underactuated finger mechanism for LARM hand
NASA Astrophysics Data System (ADS)
Yao, Shuangji; Ceccarelli, Marco; Carbone, Giuseppe; Zhan, Qiang; Lu, Zhen
2011-09-01
This paper aims to present general design considerations and optimality criteria for underactuated mechanisms in finger designs. Design issues related to grasping task of robotic fingers are discussed. Performance characteristics are outlined as referring to several aspects of finger mechanisms. Optimality criteria of the finger performances are formulated after careful analysis. A general design algorithm is summarized and formulated as a suitable multi-objective optimization problem. A numerical case of an underactuated robot finger design for Laboratory of Robotics and Mechatronics (LARM) hand is illustrated with the aim to show the practical feasibility of the proposed concepts and computations.
NASA Technical Reports Server (NTRS)
Lawton, Pat
2004-01-01
The objective of this work was to support the design of improved IUE NEWSIPS high dispersion extraction algorithms. The purpose of this work was to evaluate use of the Linearized Image (LIHI) file versus the Re-Sampled Image (SIHI) file, evaluate various extraction, and design algorithms for evaluation of IUE High Dispersion spectra. It was concluded the use of the Re-Sampled Image (SIHI) file was acceptable. Since the Gaussian profile worked well for the core and the Lorentzian profile worked well for the wings, the Voigt profile was chosen for use in the extraction algorithm. It was found that the gamma and sigma parameters varied significantly across the detector, so gamma and sigma masks for the SWP detector were developed. Extraction code was written.
Annicchiarico, W
2001-01-01
Structural optimization is an engineering field which deal with the improvement of existing solutions or even more find new solutions that are better than the previous ones under some selected criterion. Shape optimization is a research area in this field and it is involved in developing new methodologies to find better structural design based on the shape as resistant element, as for example solutions with the less stress concentration zones and made with the minimum amount of material. The goal of this doctoral dissertation is to present and discuss a general structural shape optimization methodology able to optimize several structural systems or mechanical devices. The approach presented herein is based on global search optimization tools such as Genetic Algorithms and geometric design elements by means of beta-splines curves and surfaces representation. Finally the great versatility of the developed tool is presented and discussed with an application example.
Design of asynchronous phase detection algorithms optimized for wide frequency response.
Crespo, Daniel; Quiroga, Juan Antonio; Gomez-Pedrero, Jose Antonio
2006-06-10
In many fringe pattern processing applications the local phase has to be obtained from a sinusoidal irradiance signal with unknown local frequency. This process is called asynchronous phase demodulation. Existing algorithms for asynchronous phase detection, or asynchronous algorithms, have been designed to yield no algebraic error in the recovered value of the phase for any signal frequency. However, each asynchronous algorithm has a characteristic frequency response curve. Existing asynchronous algorithms present a range of frequencies with low response, reaching zero for particular values of the signal frequency. For real noisy signals, low response implies a low signal-to-noise ratio in the recovered phase and therefore unreliable results. We present a new Fourier-based methodology for designing asynchronous algorithms with any user-defined frequency response curve and known limit of algebraic error. We show how asynchronous algorithms designed with this method can have better properties for real conditions of noise and signal frequency variation.
Mechanical Design of the Merlin Payload
NASA Astrophysics Data System (ADS)
Lucarelli, Stefano; Weimer, Peter; Wuehrer, Christian; Leone, Arturo; Olympio, Raymond; Cucciarre, Francesca; Natusch, Andreas; Bode, Markus
2014-06-01
Merlin (Methane Remote Sensing LIDAR Mission) is a joint CNES/DLR mission aimed at achieving a better understanding of the global methane cycle and of the processes that control the changes of atmospheric methane by exchange of methane between biosphere and atmosphere.Airbus Defence and Space has been selected by DLR as the prime contractor for the payload, which is based on the use of an IPDA LIDAR instrument.The paper shows the mechanical architecture of the payload, whose core consists of a CFRP optical bank supporting the laser source as well as two telescopes for transmission and reception of the LIDAR signal. It also provides an overview of how the mechanical design copes with the challenges posed by accommodation, thermo-elastic and environmental requirements.
FORTE antenna element and release mechanism design
Rohweller, D.J.; Butler, T.Af.
1995-02-01
The Fast On-Orbit Recording of Transient Events (FORTE) satellite being built by Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL) has as its most prominent feature a large deployable (11 m by 5 m) log periodic antenna to monitor emissions from electrical storms on the Earth. This paper describes the antenna and the design for the long elements and explains the dynamics of their deployment and the damping system employed. It also describes the unique paraffin-actuated reusable tie-down and release mechanism employed in the system.
MASCARA: opto-mechanical design and integration
NASA Astrophysics Data System (ADS)
Spronck, Julien F. P.; Lesage, Anna-Léa.; Stuik, Remko; Bettonvil, Felix; Snellen, Ignas A. G.
2014-07-01
MASCARA, the Multi-site All-Sky CAmeRA, consists of several fully-automated stations. Its goal is to find exoplanets transiting the brightest stars, in the mV = 4 to 8 magnitude range. Each station contains five wide- angle cameras monitoring the near-entire sky at each location. The five cameras are located in a temperature- controlled enclosure and look at the sky through five windows. A housing with a moving roof protects MASCARA from the environment. Here, we present the opto-mechanical design of the first MASCARA station.
Design Features of Modern Mechanical Ventilators.
MacIntyre, Neil
2016-12-01
A positive-pressure breath ideally should provide a VT that is adequate for gas exchange and appropriate muscle unloading while minimizing any risk for injury or discomfort. The latest generation of ventilators uses sophisticated feedback systems to sculpt positive-pressure breaths according to patient effort and respiratory system mechanics. Currently, however, these new control strategies are not totally closed-loop systems. This is because the automatic input variables remain limited, some clinician settings are still required, and the specific features of the perfect breath design still are not entirely clear. Despite these limitations, there are some rationale for many of these newer feedback features.
FORTE antenna element and release mechanism design
NASA Technical Reports Server (NTRS)
Rohweller, David J.; Butler, Thomas A.
1995-01-01
The Fast On-Orbit Recording of Transient Events (FORTE) satellite being built by Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL) has as its most prominent feature a large deployable (11 m by 5 m) log periodic antenna to monitor emissions from electrical storms on the Earth. This paper describes the antenna and the design for the long elements and explains the dynamics of their deployment and the damping system employed. It also describes the unique paraffin-actuated reusable tie-down and release mechanism employed in the system.
Optimal Design of Passive Power Filters Based on Pseudo-parallel Genetic Algorithm
NASA Astrophysics Data System (ADS)
Li, Pei; Li, Hongbo; Gao, Nannan; Niu, Lin; Guo, Liangfeng; Pei, Ying; Zhang, Yanyan; Xu, Minmin; Chen, Kerui
2017-05-01
The economic costs together with filter efficiency are taken as targets to optimize the parameter of passive filter. Furthermore, the method of combining pseudo-parallel genetic algorithm with adaptive genetic algorithm is adopted in this paper. In the early stages pseudo-parallel genetic algorithm is introduced to increase the population diversity, and adaptive genetic algorithm is used in the late stages to reduce the workload. At the same time, the migration rate of pseudo-parallel genetic algorithm is improved to change with population diversity adaptively. Simulation results show that the filter designed by the proposed method has better filtering effect with lower economic cost, and can be used in engineering.
The design and implementation of MPI master-slave parallel genetic algorithm
NASA Astrophysics Data System (ADS)
Liu, Shuping; Cheng, Yanliu
2013-03-01
In this paper, the MPI master-slave parallel genetic algorithm is implemented by analyzing the basic genetic algorithm and parallel MPI program, and building a Linux cluster. This algorithm is used for the test of maximum value problems (Rosen brocks function) .And we acquire the factors influencing the master-slave parallel genetic algorithm by deriving from the analysis of test data. The experimental data shows that the balanced hardware configuration and software design optimization can improve the performance of system in the complexity of the computing environment using the master-slave parallel genetic algorithms.
Optimal design of electric machine using genetic algorithms coupled with direct method
Oh, Y.H.; Chung, T.K. . Dept. of Electrical Engineering); Kim, M.K. . FA Research Inst.); Jung, H.K. . School of Electrical Engineering)
1999-05-01
This paper discusses the development of a new optimization algorithm for DC motor design. In principle, the new algorithm utilizes a mixed method that consists of genetic algorithms in conjunction with direct search method. The genetic algorithms are used for locating the global optimum region while the direct search method is used to achieve objective function convergence. In order to validate the effectiveness, the new algorithm has been applied to an actual DC motor. Field and torque characteristics of the DC motor are computed using finite element method and the principle of virtual work, respectively.
Design methodology for optimal hardware implementation of wavelet transform domain algorithms
NASA Astrophysics Data System (ADS)
Johnson-Bey, Charles; Mickens, Lisa P.
2005-05-01
The work presented in this paper lays the foundation for the development of an end-to-end system design methodology for implementing wavelet domain image/video processing algorithms in hardware using Xilinx field programmable gate arrays (FPGAs). With the integration of the Xilinx System Generator toolbox, this methodology will allow algorithm developers to design and implement their code using the familiar MATLAB/Simulink development environment. By using this methodology, algorithm developers will not be required to become proficient in the intricacies of hardware design, thus reducing the design cycle and time-to-market.
Using a Genetic Algorithm to Design Nuclear Electric Spacecraft
NASA Technical Reports Server (NTRS)
Pannell, William P.
2003-01-01
The basic approach to to design nuclear electric spacecraft is to generate a group of candidate designs, see how "fit" the design are, and carry best design forward to the next generation. Some designs eliminated, some randomly modified and carried forward.
Nonlinear Analysis and Optimal Design of Dynamic Mechanical Systems for Spacecraft Application.
1986-02-01
Mechanisms, vibrational analysis, optimization , geometric nonlinearity , material nonlinearity 20. AUSTRACT (C..,I.,.. 01 ".Id*If oO...p .,d Id.MII( by... nonlinear finite element analysis procedure for three-dimensional mechanisms. A niew optimization algorithm has also been developed based on the Gauss DD I...1986 NONLINEAR ANALYSIS AND OPTIMAL DESIGN OF DYNAMIC MECHANICAL SYSTEMS FOR SPACECRAFT APPLICATION Air Force Office of Scientific Research Grant No
An improved POCS super-resolution infrared image reconstruction algorithm based on visual mechanism
NASA Astrophysics Data System (ADS)
Liu, Jinsong; Dai, Shaosheng; Guo, Zhongyuan; Zhang, Dezhou
2016-09-01
The traditional projection onto convex sets (POCS) super-resolution (SR) reconstruction algorithm can only get reconstructed images with poor contrast, low signal-to-noise ratio and blurring edges. In order to solve the above disadvantages, an improved POCS SR infrared image reconstruction algorithm based on visual mechanism is proposed, which introduces data consistency constraint with variable correction thresholds to highlight the target edges and filter out background noises; further, the algorithm introduces contrast constraint considering the resolving ability of human eyes into the traditional algorithm, enhancing the contrast of the image reconstructed adaptively. The experimental results show that the improved POCS algorithm can acquire high quality infrared images whose contrast, average gradient and peak signal to noise ratio are improved many times compared with traditional algorithm.
NASA Technical Reports Server (NTRS)
Izumi, K. H.; Thompson, J. L.; Groce, J. L.; Schwab, R. W.
1986-01-01
The design requirements for a 4D path definition algorithm are described. These requirements were developed for the NASA ATOPS as an extension of the Local Flow Management/Profile Descent algorithm. They specify the processing flow, functional and data architectures, and system input requirements, and recommended the addition of a broad path revision (reinitialization) function capability. The document also summarizes algorithm design enhancements and the implementation status of the algorithm on an in-house PDP-11/70 computer. Finally, the requirements for the pilot-computer interfaces, the lateral path processor, and guidance and steering function are described.
Damage Mechanics of Composite Materials: Constitutive Modeling and Computational Algorithms
1991-04-21
Damage Mechanics", Appl. Mech. Rev., Vol. 37, Jan ., pp. 1-6. 15. KRAJCINOVIC, D., (1985), "Constitutive Theories for Solids with Defective Microstruc...damage models; see, e.g., Krajcinovic (1984,1986,1989) and Bazant (1986) for a comprehensive literature review. There are, however, some micromechanical...Solids, Vol. 37, No. 4, pp. 435-453. 5. BAZANT , Z., (1986), "Mechanics of Distributed Cracking",Appl. Mech. Rev., Vol. 39, No. 5 pp. 675-705. 6. BUDIANSKY
NASA Astrophysics Data System (ADS)
Zecchin, A. C.; Simpson, A. R.; Maier, H. R.; Marchi, A.; Nixon, J. B.
2012-09-01
Evolutionary algorithms (EAs) have been applied successfully to many water resource problems, such as system design, management decision formulation, and model calibration. The performance of an EA with respect to a particular problem type is dependent on how effectively its internal operators balance the exploitation/exploration trade-off to iteratively find solutions of an increasing quality. For a given problem, different algorithms are observed to produce a variety of different final performances, but there have been surprisingly few investigations into characterizing how the different internal mechanisms alter the algorithm's searching behavior, in both the objective and decision space, to arrive at this final performance. This paper presents metrics for analyzing the searching behavior of ant colony optimization algorithms, a particular type of EA, for the optimal water distribution system design problem, which is a classical NP-hard problem in civil engineering. Using the proposed metrics, behavior is characterized in terms of three different attributes: (1) the effectiveness of the search in improving its solution quality and entering into optimal or near-optimal regions of the search space, (2) the extent to which the algorithm explores as it converges to solutions, and (3) the searching behavior with respect to the feasible and infeasible regions. A range of case studies is considered, where a number of ant colony optimization variants are applied to a selection of water distribution system optimization problems. The results demonstrate the utility of the proposed metrics to give greater insight into how the internal operators affect each algorithm's searching behavior.
[Optimizing algorithm design of piecewise linear classifier for spectra].
Lan, Tian-Ge; Fang, Yong-Hua; Xiong, Wei; Kong, Chao; Li, Da-Cheng; Dong, Da-Ming
2008-11-01
Being able to identify pollutant gases quickly and accurately is a basic request of spectroscopic technique for envirment monitoring for spectral classifier. Piecewise linear classifier is simple needs less computational time and approachs nonlinear boundary beautifully. Combining piecewise linear classifier and linear support vector machine which is based on the principle of maximizing margin, an optimizing algorithm for single side piecewise linear classifier was devised. Experimental results indicate that the piecewise linear classifier trained by the optimizing algorithm proposed in this paper can approach nonolinear boundary with fewer super_planes and has higher veracity for classification and recognition.
Design specification for the whole-body algorithm
NASA Technical Reports Server (NTRS)
Fitzjerrell, D. G.
1974-01-01
The necessary requirements and guidelines for the construction of a computer program of the whole-body algorithm are presented. The minimum subsystem models required to effectively simulate the total body response to stresses of interest are (1) cardiovascular (exercise/LBNP/tilt); (2) respiratory (Grodin's model); (3) thermoregulatory (Stolwijk's model); and (4) long-term circulatory fluid and electrolyte (Guyton's model). The whole-body algorithm must be capable of simulating response to stresses from CO2 inhalation, hypoxia, thermal environmental exercise (sitting and supine), LBNP, and tilt (changing body angles in gravity).
DESIGNING SUSTAINABLE PROCESSES WITH SIMULATION: THE WASTE REDUCTION (WAR) ALGORITHM
The WAR Algorithm, a methodology for determining the potential environmental impact (PEI) of a chemical process, is presented with modifications that account for the PEI of the energy consumed within that process. From this theory, four PEI indexes are used to evaluate the envir...
DESIGNING SUSTAINABLE PROCESSES WITH SIMULATION: THE WASTE REDUCTION (WAR) ALGORITHM
The WAR Algorithm, a methodology for determining the potential environmental impact (PEI) of a chemical process, is presented with modifications that account for the PEI of the energy consumed within that process. From this theory, four PEI indexes are used to evaluate the envir...
High pressure humidification columns: Design equations, algorithm, and computer code
Enick, R.M.; Klara, S.M.; Marano, J.J.
1994-07-01
This report describes the detailed development of a computer model to simulate the humidification of an air stream in contact with a water stream in a countercurrent, packed tower, humidification column. The computer model has been developed as a user model for the Advanced System for Process Engineering (ASPEN) simulator. This was done to utilize the powerful ASPEN flash algorithms as well as to provide ease of use when using ASPEN to model systems containing humidification columns. The model can easily be modified for stand-alone use by incorporating any standard algorithm for performing flash calculations. The model was primarily developed to analyze Humid Air Turbine (HAT) power cycles; however, it can be used for any application that involves a humidifier or saturator. The solution is based on a multiple stage model of a packed column which incorporates mass and energy, balances, mass transfer and heat transfer rate expressions, the Lewis relation and a thermodynamic equilibrium model for the air-water system. The inlet air properties, inlet water properties and a measure of the mass transfer and heat transfer which occur in the column are the only required input parameters to the model. Several example problems are provided to illustrate the algorithm`s ability to generate the temperature of the water, flow rate of the water, temperature of the air, flow rate of the air and humidity of the air as a function of height in the column. The algorithm can be used to model any high-pressure air humidification column operating at pressures up to 50 atm. This discussion includes descriptions of various humidification processes, detailed derivations of the relevant expressions, and methods of incorporating these equations into a computer model for a humidification column.
Two-frame algorithm to design quadrature filters in phase shifting interferometry.
Mosiño, J F; Gutiérrez-García, J C; Gutiérrez-García, T A; Macías-Preza, J M
2010-11-22
The main purpose of this paper is to present a method to design tunable quadrature filters in phase shifting interferometry. From a general tunable two-frame algorithm introduced, a set of individual filters corresponding to each quadrature conditions of the filter is obtained. Then, through a convolution algorithm of this set of filters the desired symmetric quadrature filter is recovered. Finally, the method is applied to obtain several tunable filters, like four and five-frame algorithms.
Efficient multi-value connected component labeling algorithm and its ASIC design
NASA Astrophysics Data System (ADS)
Sang, Hongshi; Zhang, Jing; Zhang, Tianxu
2007-12-01
An efficient connected component labeling algorithm for multi-value image is proposed in this paper. The algorithm is simple and inerratic suitable for hardware design. A one-dimensional array is used to store equivalence pairs. Record organization of equivalence table is advantageously to find the minimum equivalent label, and can shrink time on processing equivalence table. A pipelined architecture of the algorithm is described to enhance system performance.
Design of error-compensating algorithms for sinusoidal phase shifting interferometry
Groot, Peter de
2009-12-10
An improved approach to interferometry using sinusoidal phase shifting balances several harmonic components in the interference signal against each other. The resulting computationally efficient phase-estimation algorithms have low sensitivity to errors such as spurious intensity noise, vibration, and errors in the phase shift pattern. Specific example algorithms employing 8 and 12 camera frames illustrate design principles that are extendable to algorithms of any length for applications that would benefit from a simplified, sinusoidal phase shift.
An Effective Algorithm for Generation of Factorial Designs with Generalized Minimum Aberration
Fang, Kai-Tai; Zhang, Aijun; Li, Runze
2009-01-01
Fractional factorial designs are popular and widely used for industrial experiments. Generalized minimum aberration is an important criterion recently proposed for both regular and non-regular designs. This paper provides a formal optimization treatment on optimal designs with generalized minimum aberration. New lower bounds and optimality results are developed for resolution-III designs. Based on these results, an effective computer search algorithm is provided for sub-design selection, and new optimal designs are reported. PMID:19756247
A novel algorithm of maximin Latin hypercube design using successive local enumeration
NASA Astrophysics Data System (ADS)
Zhu, Huaguang; Liu, Li; Long, Teng; Peng, Lei
2012-05-01
The design of computer experiments (DoCE) is a key technique in the field of metamodel-based design optimization. Space-filling and projective properties are desired features in DoCE. In this article, a novel algorithm of maximin Latin hypercube design (LHD) using successive local enumeration (SLE) is proposed for generating arbitrary m points in n-dimensional space. Testing results compared with lhsdesign function, binary encoded genetic algorithm (BinGA), permutation encoded genetic algorithm (PermGA) and translational propagation algorithm (TPLHD) indicate that SLE is effective to generate sampling points with good space-filling and projective properties. The accuracies of metamodels built with the sampling points produced by lhsdesign function and SLE are compared to illustrate the preferable performance of SLE. Through the comparative study on efficiency with BinGA, PermGA, and TPLHD, as a novel algorithm of LHD sampling techniques, SLE has good space-filling property and acceptable efficiency.
NASA Astrophysics Data System (ADS)
Lu, Y. C.; Jan, J. C.; Hung, S. L.; Hung, G. H.
2013-10-01
This work develops an augmented particle swarm optimization (AugPSO) algorithm using two new strategies,: boundary-shifting and particle-position-resetting. The purpose of the algorithm is to optimize the design of truss structures. Inspired by a heuristic, the boundary-shifting approach forces particles to move to the boundary between feasible and infeasible regions in order to increase the convergence rate in searching. The purpose of the particle-position-resetting approach, motivated by mutation scheme in genetic algorithms (GAs), is to increase the diversity of particles and to prevent the solution of particles from falling into local minima. The performance of the AugPSO algorithm was tested on four benchmark truss design problems involving 10, 25, 72 and 120 bars. The convergence rates and final solutions achieved were compared among the simple PSO, the PSO with passive congregation (PSOPC) and the AugPSO algorithms. The numerical results indicate that the new AugPSO algorithm outperforms the simple PSO and PSOPC algorithms. The AugPSO achieved a new and superior optimal solution to the 120-bar truss design problem. Numerical analyses showed that the AugPSO algorithm is more robust than the PSO and PSOPC algorithms.
Design and analysis of closed-loop decoder adaptation algorithms for brain-machine interfaces.
Dangi, Siddharth; Orsborn, Amy L; Moorman, Helene G; Carmena, Jose M
2013-07-01
Closed-loop decoder adaptation (CLDA) is an emerging paradigm for achieving rapid performance improvements in online brain-machine interface (BMI) operation. Designing an effective CLDA algorithm requires making multiple important decisions, including choosing the timescale of adaptation, selecting which decoder parameters to adapt, crafting the corresponding update rules, and designing CLDA parameters. These design choices, combined with the specific settings of CLDA parameters, will directly affect the algorithm's ability to make decoder parameters converge to values that optimize performance. In this article, we present a general framework for the design and analysis of CLDA algorithms and support our results with experimental data of two monkeys performing a BMI task. First, we analyze and compare existing CLDA algorithms to highlight the importance of four critical design elements: the adaptation timescale, selective parameter adaptation, smooth decoder updates, and intuitive CLDA parameters. Second, we introduce mathematical convergence analysis using measures such as mean-squared error and KL divergence as a useful paradigm for evaluating the convergence properties of a prototype CLDA algorithm before experimental testing. By applying these measures to an existing CLDA algorithm, we demonstrate that our convergence analysis is an effective analytical tool that can ultimately inform and improve the design of CLDA algorithms.
Use of Algorithm of Changes for Optimal Design of Heat Exchanger
NASA Astrophysics Data System (ADS)
Tam, S. C.; Tam, H. K.; Chio, C. H.; Tam, L. M.
2010-05-01
For economic reasons, the optimal design of heat exchanger is required. Design of heat exchanger is usually based on the iterative process. The design conditions, equipment geometries, the heat transfer and friction factor correlations are totally involved in the process. Using the traditional iterative method, many trials are needed for satisfying the compromise between the heat exchange performance and the cost consideration. The process is cumbersome and the optimal design is often depending on the design engineer's experience. Therefore, in the recent studies, many researchers, reviewed in [1], applied the genetic algorithm (GA) [2] for designing the heat exchanger. The results outperformed the traditional method. In this study, the alternative approach, algorithm of changes, is proposed for optimal design of shell-tube heat exchanger [3]. This new method, algorithm of changes based on I Ching (???), is developed originality by the author. In the algorithms, the hexagram operations in I Ching has been generalized to binary string case and the iterative procedure which imitates the I Ching inference is also defined. On the basis of [3], the shell inside diameter, tube outside diameter, and baffles spacing were treated as the design (or optimized) variables. The cost of the heat exchanger was arranged as the objective function. Through the case study, the results show that the algorithm of changes is comparable to the GA method. Both of method can find the optimal solution in a short time. However, without interchanging information between binary strings, the algorithm of changes has advantage on parallel computation over GA.
NASA Astrophysics Data System (ADS)
Afshar, M. H.
2007-04-01
This paper exploits the unique feature of the Ant Colony Optimization Algorithm (ACOA), namely incremental solution building mechanism, to develop partially constraint ACO algorithms for the solution of optimization problems with explicit constraints. The method is based on the provision of a tabu list for each ant at each decision point of the problem so that some constraints of the problem are satisfied. The application of the method to the problem of storm water network design is formulated and presented. The network nodes are considered as the decision points and the nodal elevations of the network are used as the decision variables of the optimization problem. Two partially constrained ACO algorithms are formulated and applied to a benchmark example of storm water network design and the results are compared with those of the original unconstrained algorithm and existing methods. In the first algorithm the positive slope constraints are satisfied explicitly and the rest are satisfied by using the penalty method while in the second one the satisfaction of constraints regarding the maximum ratio of flow depth to the diameter are also achieved explicitly via the tabu list. The method is shown to be very effective and efficient in locating the optimal solutions and in terms of the convergence characteristics of the resulting ACO algorithms. The proposed algorithms are also shown to be relatively insensitive to the initial colony used compared to the original algorithm. Furthermore, the method proves itself capable of finding an optimal or near-optimal solution, independent of the discretisation level and the size of the colony used.
Mechanical cloak design by direct lattice transformation
Bückmann, Tiemo; Kadic, Muamer; Schittny, Robert; Wegener, Martin
2015-01-01
Spatial coordinate transformations have helped simplifying mathematical issues and solving complex boundary-value problems in physics for decades already. More recently, material-parameter transformations have also become an intuitive and powerful engineering tool for designing inhomogeneous and anisotropic material distributions that perform wanted functions, e.g., invisibility cloaking. A necessary mathematical prerequisite for this approach to work is that the underlying equations are form invariant with respect to general coordinate transformations. Unfortunately, this condition is not fulfilled in elastic–solid mechanics for materials that can be described by ordinary elasticity tensors. Here, we introduce a different and simpler approach. We directly transform the lattice points of a 2D discrete lattice composed of a single constituent material, while keeping the properties of the elements connecting the lattice points the same. After showing that the approach works in various areas, we focus on elastic–solid mechanics. As a demanding example, we cloak a void in an effective elastic material with respect to static uniaxial compression. Corresponding numerical calculations and experiments on polymer structures made by 3D printing are presented. The cloaking quality is quantified by comparing the average relative SD of the strain vectors outside of the cloaked void with respect to the homogeneous reference lattice. Theory and experiment agree and exhibit very good cloaking performance. PMID:25848021
Mechanical cloak design by direct lattice transformation.
Bückmann, Tiemo; Kadic, Muamer; Schittny, Robert; Wegener, Martin
2015-04-21
Spatial coordinate transformations have helped simplifying mathematical issues and solving complex boundary-value problems in physics for decades already. More recently, material-parameter transformations have also become an intuitive and powerful engineering tool for designing inhomogeneous and anisotropic material distributions that perform wanted functions, e.g., invisibility cloaking. A necessary mathematical prerequisite for this approach to work is that the underlying equations are form invariant with respect to general coordinate transformations. Unfortunately, this condition is not fulfilled in elastic-solid mechanics for materials that can be described by ordinary elasticity tensors. Here, we introduce a different and simpler approach. We directly transform the lattice points of a 2D discrete lattice composed of a single constituent material, while keeping the properties of the elements connecting the lattice points the same. After showing that the approach works in various areas, we focus on elastic-solid mechanics. As a demanding example, we cloak a void in an effective elastic material with respect to static uniaxial compression. Corresponding numerical calculations and experiments on polymer structures made by 3D printing are presented. The cloaking quality is quantified by comparing the average relative SD of the strain vectors outside of the cloaked void with respect to the homogeneous reference lattice. Theory and experiment agree and exhibit very good cloaking performance.
ERIC Educational Resources Information Center
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
ERIC Educational Resources Information Center
Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao
2016-01-01
In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…
LANSCE wire scanning diagnostics device mechanical design
Rodriguez Esparza, Sergio
2010-01-01
The Los Alamos Neutron Science Center (LANSCE) is one of the major experimental science facilities at the Los Alamos National Laboratory (LANL). The core of LANSCE's work lies in the operation of a powerful linear accelerator, which accelerates protons up to 84% the speed oflight. These protons are used for a variety of purposes, including materials testing, weapons research and isotopes production. To assist in guiding the proton beam, a series of over one hundred wire scanners are used to measure the beam profile at various locations along the half-mile length of the particle accelerator. A wire scanner is an electro-mechanical device that moves a set of wires through a particle beam and measures the secondary emissions from the resulting beam-wire interaction to obtain beam intensity information. When supplemented with data from a position sensor, this information is used to determine the cross-sectional profile of the beam. This measurement allows beam operators to adjust parameters such as acceleration, beam steering, and focus to ensure that the beam reaches its destination as effectively as possible. Some of the current wire scanners are nearly forty years old and are becoming obsolete. The problem with current wire scanners comes in the difficulty of maintenance and reliability. The designs of these wire scanners vary making it difficult to keep spare parts that would work on all designs. Also many of the components are custom built or out-dated technology and are no longer in production.
"Basic MR Relaxation Mechanisms & Contrast Agent Design"
De León-Rodríguez, Luis M.; Martins, André F.; Pinho, Marco; Rofsky, Neil; Sherry, A. Dean
2015-01-01
The diagnostic capabilities of magnetic resonance imaging (MRI) have undergone continuous and substantial evolution by virtue of hardware and software innovations and the development and implementation of exogenous contrast media. Thirty years since the first MRI contrast agent was approved for clinical use, a reliance on MR contrast media persists largely to improve image quality with higher contrast resolution and to provide additional functional characterization of normal and abnormal tissues. Further development of MR contrast media is an important component in the quest for continued augmentation of diagnostic capabilities. In this review we will detail the many important considerations when pursuing the design and use of MR contrast media. We will offer a perspective on the importance of chemical stability, particularly kinetic stability, and how this influences one's thinking about the safety of metal-ligand based contrast agents. We will discuss the mechanisms involved in magnetic resonance relaxation in the context of probe design strategies. A brief description of currently available contrast agents will be accompanied by an in-depth discussion that highlights promising MRI contrast agents in development for future clinical and research applications. Our intention is to give a diverse audience an improved understanding of the factors involved in developing new types of safe and highly efficient MR contrast agents and, at the same time, provide an appreciation of the insights into physiology and disease that newer types of responsive agents can provide. PMID:25975847
ACCESS: thermal mechanical design and performance
NASA Astrophysics Data System (ADS)
Kaiser, Mary E.; Morris, Matthew J.; Hansen, Jason; Jensen, Scott; McCandliss, Stephan R.; Rauscher, Bernard J.; Kimble, Randy A.; Kruk, Jeffrey W.; Pelton, Russell; Mott, D. Brent; Wen, Yiting; Gardner, Jonathan P.; Benford, Dominic J.; Woodgate, Bruce E.; Wright, Edward L.; Feldman, Paul D.; Moos, H. Warren; Riess, Adam G.; Bohlin, Ralph; Deustua, Susana E.; Dixon, W. V.; Sahnow, David J.; Kurucz, Robert; Lampton, Michael; Perlmutter, Saul
2013-09-01
Establishing improved spectrophotometric standards is important for a broad range of missions and is relevant to many astrophysical problems. ACCESS, "Absolute Color Calibration Experiment for Standard Stars", is a series of rocket-borne sub-orbital missions and ground-based experiments designed to enable improvements in the precision of the astrophysical flux scale through the transfer of absolute laboratory detector standards from the National Institute of Standards and Technology (NIST) to a network of stellar standards with a calibration accuracy of 1% and a spectral resolving power of 500 across the 0.35-1.7μm bandpass. Achieving a calibration accuracy of 1% not only requires an accurate calibration transfer from the detector standards to the instrument, but it also requires characterization and stability of the detector as well as a thermal background that contributes less than 1% to the flux per resolution element in the near-infrared (1.7μm) spectral region of the ACCESS bandpass. This paper describes the thermal mechanical design for achieving a low thermal background across the ACCESS spectral bandpass.
ACCESS: Thermal Mechanical Design, Performance, and Status
NASA Astrophysics Data System (ADS)
Kaiser, Mary Elizabeth; Morris, M. J.; McCandliss, S. R.; Rauscher, B. J.; Kimble, R. A.; Kruk, J. W.; Wright, E. L.; Bohlin, R.; Kurucz, R. L.; Riess, A. G.; Pelton, R.; Deustua, S. E.; Dixon, W. V.; Sahnow, D. J.; Benford, D. J.; Gardner, J. P.; Feldman, P. D.; Moos, H. W.; Lampton, M.; Perlmutter, S.; Woodgate, B. E.
2014-01-01
Systematic errors associated with astrophysical data used to probe fundamental astrophysical questions, such as SNeIa observations used to constrain dark energy theories, are now rivaling and exceeding the statistical errors associated with these measurements. ACCESS: Absolute Color Calibration Experiment for Standard Stars is a series of rocket-borne sub-orbital missions and ground-based experiments designed to enable improvements in the precision of the astrophysical flux scale through the transfer of absolute laboratory detector standards from the National Institute of Standards and Technology (NIST) to a network of stellar standards with a calibration accuracy of 1% and a spectral resolving power of 500 across the 0.35 - 1.7μm bandpass. Achieving this level of accuracy requires characterization and stability of the instrument and detector including a thermal background that contributes less than 1% to the flux per resolution element in the NIR. We will present the instrument and calibration status with a focus on the thermal mechanical design and associated performance data. The detector control and performance will be presented in a companion poster (Morris, et al). NASA APRA sounding rocket grant NNX08AI65G supports this work.
cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design.
Pan, Yuchao; Dong, Yuxi; Zhou, Jingtian; Hallen, Mark; Donald, Bruce R; Zeng, Jianyang; Xu, Wei
2016-09-01
Finding the global minimum energy conformation (GMEC) of a huge combinatorial search space is the key challenge in computational protein design (CPD) problems. Traditional algorithms lack a scalable and efficient distributed design scheme, preventing researchers from taking full advantage of current cloud infrastructures. We design cloud OSPREY (cOSPREY), an extension to a widely used protein design software OSPREY, to allow the original design framework to scale to the commercial cloud infrastructures. We propose several novel designs to integrate both algorithm and system optimizations, such as GMEC-specific pruning, state search partitioning, asynchronous algorithm state sharing, and fault tolerance. We evaluate cOSPREY on three different cloud platforms using different technologies and show that it can solve a number of large-scale protein design problems that have not been possible with previous approaches.
cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design
Pan, Yuchao; Dong, Yuxi; Zhou, Jingtian; Hallen, Mark; Donald, Bruce R.; Xu, Wei
2016-01-01
Abstract Finding the global minimum energy conformation (GMEC) of a huge combinatorial search space is the key challenge in computational protein design (CPD) problems. Traditional algorithms lack a scalable and efficient distributed design scheme, preventing researchers from taking full advantage of current cloud infrastructures. We design cloud OSPREY (cOSPREY), an extension to a widely used protein design software OSPREY, to allow the original design framework to scale to the commercial cloud infrastructures. We propose several novel designs to integrate both algorithm and system optimizations, such as GMEC-specific pruning, state search partitioning, asynchronous algorithm state sharing, and fault tolerance. We evaluate cOSPREY on three different cloud platforms using different technologies and show that it can solve a number of large-scale protein design problems that have not been possible with previous approaches. PMID:27154509
An Object-Oriented Collection of Minimum Degree Algorithms: Design, Implementation, and Experiences
NASA Technical Reports Server (NTRS)
Kumfert, Gary; Pothen, Alex
1999-01-01
The multiple minimum degree (MMD) algorithm and its variants have enjoyed 20+ years of research and progress in generating fill-reducing orderings for sparse, symmetric positive definite matrices. Although conceptually simple, efficient implementations of these algorithms are deceptively complex and highly specialized. In this case study, we present an object-oriented library that implements several recent minimum degree-like algorithms. We discuss how object-oriented design forces us to decompose these algorithms in a different manner than earlier codes and demonstrate how this impacts the flexibility and efficiency of our C++ implementation. We compare the performance of our code against other implementations in C or Fortran.
A general theory known as the WAste Reduction (WASR) algorithm has been developed to describe the flow and the generation of potential environmental impact through a chemical process. This theory integrates environmental impact assessment into chemical process design Potential en...
A general theory known as the WAste Reduction (WASR) algorithm has been developed to describe the flow and the generation of potential environmental impact through a chemical process. This theory integrates environmental impact assessment into chemical process design Potential en...
Algorithm of probabilistic assessment of fully-mechanized longwall downtime
NASA Astrophysics Data System (ADS)
Domrachev, A. N.; Rib, S. V.; Govorukhin, Yu M.; Krivopalov, V. G.
2017-09-01
The problem of increasing the load on a long fully-mechanized longwall has several aspects, one of which is the improvement of efficiency in using available stoping equipment due to the increase in coefficient of the machine operating time of a shearer and other mining machines that form an integral part of the longwall set of equipment. The task of predicting the reliability indicators of stoping equipment is solved by the statistical evaluation of parameters of downtime exponential distribution and failure recovery. It is more difficult to solve the problems of downtime accounting in case of accidents in the face workings and, despite the statistical data on accidents in mine workings, no solution has been found to date. The authors have proposed a variant of probability assessment of workings caving using Poisson distribution and the duration of their restoration using normal distribution. The above results confirm the possibility of implementing the approach proposed by the authors.
2006-09-01
BASED OPTIMIZATION OF ADVANCED SOLAR CELL DESIGNS MODELED IN SILVACO ATLASTM by James Utsler September 2006 Thesis Co-Advisors...TITLE AND SUBTITLE Genetic Algorithm Based Optimization of Advanced Solar Cell Designs Modeled in SIlvaco ATLASTM 6. AUTHOR(S) James D. Utsler 5...was modeled using the Silvaco ATLASTM software. The output of the ATLASTM simulation runs served as the input to the genetic algorithm. The genetic
Matott, L Shawn; Bartelt-Hunt, Shannon L; Rabideau, Alan J; Fowler, K R
2006-10-15
Although heuristic optimization techniques are increasingly applied in environmental engineering applications, algorithm selection and configuration are often approached in an ad hoc fashion. In this study, the design of a multilayer sorptive barrier system served as a benchmark problem for evaluating several algorithm-tuning procedures, as applied to three global optimization techniques (genetic algorithms, simulated annealing, and particle swarm optimization). Each design problem was configured as a combinatorial optimization in which sorptive materials were selected for inclusion in a landfill liner to minimize the transport of three common organic contaminants. Relative to multilayer sorptive barrier design, study results indicate (i) the binary-coded genetic algorithm is highly efficient and requires minimal tuning, (ii) constraint violations must be carefully integrated to avoid poor algorithm convergence, and (iii) search algorithm performance is strongly influenced by the physical-chemical properties of the organic contaminants of concern. More generally, the results suggest that formal algorithm tuning, which has not been widely applied to environmental engineering optimization, can significantly improve algorithm performance and provide insight into the physical processes that control environmental systems.
Design and FPGA implementation of real-time automatic image enhancement algorithm
NASA Astrophysics Data System (ADS)
Dong, GuoWei; Hou, ZuoXun; Tang, Qi; Pan, Zheng; Li, Xin
2016-11-01
In order to improve image processing quality and boost processing rate, this paper proposes an real-time automatic image enhancement algorithm. It is based on the histogram equalization algorithm and the piecewise linear enhancement algorithm, and it calculate the relationship of the histogram and the piecewise linear function by analyzing the histogram distribution for adaptive image enhancement. Furthermore, the corresponding FPGA processing modules are designed to implement the methods. Especially, the high-performance parallel pipelined technology and inner potential parallel processing ability of the modules are paid more attention to ensure the real-time processing ability of the complete system. The simulations and the experimentations show that the algorithm is based on the design and implementation of FPGA hardware circuit less cost on hardware, high real-time performance, the good processing performance in different sceneries. The algorithm can effectively improve the image quality, and would have wide prospect on imaging processing field.
NASA Technical Reports Server (NTRS)
Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.
1986-01-01
The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented.
NASA Technical Reports Server (NTRS)
Caglayan, A. K.; Godiwala, P. M.; Morrell, F. R.
1986-01-01
This paper summarizes the modifications made to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of an update frequency, are also presented.
Advanced algorithms for radiographic material discrimination and inspection system design
NASA Astrophysics Data System (ADS)
Gilbert, Andrew J.; McDonald, Benjamin S.; Deinert, Mark R.
2016-10-01
X-ray and neutron radiography are powerful tools for non-invasively inspecting the interior of objects. However, current methods are limited in their ability to differentiate materials when multiple materials are present, especially within large and complex objects. Past work has demonstrated that the spectral shift that X-ray beams undergo in traversing an object can be used to detect and quantify nuclear materials. The technique uses a spectrally sensitive detector and an inverse algorithm that varies the composition of the object until the X-ray spectrum predicted by X-ray transport matches the one measured. Here we show that this approach can be adapted to multi-mode radiography, with energy integrating detectors, and that the Cramér-Rao lower bound can be used to choose an optimal set of inspection modes a priori. We consider multi-endpoint X-ray radiography alone, or in combination with neutron radiography using deuterium-deuterium (DD) or deuterium-tritium (DT) sources. We show that for an optimal mode choice, the algorithm can improve discrimination between high-Z materials, specifically between tungsten and plutonium, and estimate plutonium mass within a simulated nuclear material storage system to within 1%.
Design of a fuzzy differential evolution algorithm to predict non-deposition sediment transport
NASA Astrophysics Data System (ADS)
Ebtehaj, Isa; Bonakdari, Hossein
2017-04-01
Since the flow entering a sewer contains solid matter, deposition at the bottom of the channel is inevitable. It is difficult to understand the complex, three-dimensional mechanism of sediment transport in sewer pipelines. Therefore, a method to estimate the limiting velocity is necessary for optimal designs. Due to the inability of gradient-based algorithms to train Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for non-deposition sediment transport prediction, a new hybrid ANFIS method based on a differential evolutionary algorithm (ANFIS-DE) is developed. The training and testing performance of ANFIS-DE is evaluated using a wide range of dimensionless parameters gathered from the literature. The input combination used to estimate the densimetric Froude number (Fr) parameters includes the volumetric sediment concentration (C V ), ratio of median particle diameter to hydraulic radius (d/R), ratio of median particle diameter to pipe diameter (d/D) and overall friction factor of sediment (λ s ). The testing results are compared with the ANFIS model and regression-based equation results. The ANFIS-DE technique predicted sediment transport at limit of deposition with lower root mean square error (RMSE = 0.323) and mean absolute percentage of error (MAPE = 0.065) and higher accuracy (R 2 = 0.965) than the ANFIS model and regression-based equations.
Design of monoliths through their mechanical properties.
Podgornik, Aleš; Savnik, Aleš; Jančar, Janez; Krajnc, Nika Lendero
2014-03-14
Chromatographic monoliths have several interesting properties making them attractive supports for analytics but also for purification, especially of large biomolecules and bioassemblies. Although many of monolith features were thoroughly investigated, there is no data available to predict how monolith mechanical properties affect its chromatographic performance. In this work, we investigated the effect of porosity, pore size and chemical modification on methacrylate monolith compression modulus. While a linear correlation between pore size and compression modulus was found, the effect of porosity was highly exponential. Through these correlations it was concluded that chemical modification affects monolith porosity without changing the monolith skeleton integrity. Mathematical model to describe the change of monolith permeability as a function of monolith compression modulus was derived and successfully validated for monoliths of different geometries and pore sizes. It enables the prediction of pressure drop increase due to monolith compressibility for any monolith structural characteristics, such as geometry, porosity, pore size or mobile phase properties like viscosity or flow rate, based solely on the data of compression modulus and structural data of non-compressed monolith. Furthermore, it enables simple determination of monolith pore size at which monolith compressibility is the smallest and the most robust performance is expected. Data of monolith compression modulus in combination with developed mathematical model can therefore be used for the prediction of monolith permeability during its implementation but also to accelerate the design of novel chromatographic monoliths with desired hydrodynamic properties for particular application.
NASA Astrophysics Data System (ADS)
Rao, Jagu S.; Tiwari, R.
2015-03-01
A Pareto optimal design analysis is carried out on the design of magnetic thrust bearings using multi-objective genetic algorithms. Two configurations of bearings have been considered with the minimization of power loss and weight of the bearing as objectives for performance comparisons. A multi-objective evolutionary algorithm is utilized to generate Pareto frontiers at different operating loads. As the load increases, the Pareto frontier reduces to a single point at a peak load for both configurations. Pareto optimal design analysis is used to study characteristics of design variables and other parameters. Three distinct operating load zones have been observed.
A hybrid algorithm for transonic airfoil and wing design
NASA Technical Reports Server (NTRS)
Campbell, Richard L.; Smith, Leigh A.
1987-01-01
The present method for the design of transonic airfoils and wings employs a predictor/corrector approach in which an analysis code calculates the flowfield for an initial geometry, then modifies it on the basis of the difference between calculated and target pressures. This allows the design method to be straightforwardly coupled with any existing analysis code, as presently undertaken with several two- and three-dimensional potential flow codes. The results obtained indicate that the method is robust and accurate, even in the cases of airfoils with strongly supercritical flow and shocks. The design codes are noted to require computational resources typical of current pure-inverse methods.
Clairvoyant fusion: a new methodology for designing robust detection algorithms
NASA Astrophysics Data System (ADS)
Schaum, Alan
2016-10-01
Many realistic detection problems cannot be solved with simple statistical tests for known alternative probability models. Uncontrollable environmental conditions, imperfect sensors, and other uncertainties transform simple detection problems with likelihood ratio solutions into composite hypothesis (CH) testing problems. Recently many multi- and hyperspectral sensing CH problems have been addressed with a new approach. Clairvoyant fusion (CF) integrates the optimal detectors ("clairvoyants") associated with every unspecified value of the parameters appearing in a detection model. For problems with discrete parameter values, logical rules emerge for combining the decisions of the associated clairvoyants. For many problems with continuous parameters, analytic methods of CF have been found that produce closed-form solutions-or approximations for intractable problems. Here the principals of CF are reviewed and mathematical insights are described that have proven useful in the derivation of solutions. It is also shown how a second-stage fusion procedure can be used to create theoretically superior detection algorithms for ALL discrete parameter problems.
Vision-based vehicle detection and tracking algorithm design
NASA Astrophysics Data System (ADS)
Hwang, Junyeon; Huh, Kunsoo; Lee, Donghwi
2009-12-01
The vision-based vehicle detection in front of an ego-vehicle is regarded as promising for driver assistance as well as for autonomous vehicle guidance. The feasibility of vehicle detection in a passenger car requires accurate and robust sensing performance. A multivehicle detection system based on stereo vision has been developed for better accuracy and robustness. This system utilizes morphological filter, feature detector, template matching, and epipolar constraint techniques in order to detect the corresponding pairs of vehicles. After the initial detection, the system executes the tracking algorithm for the vehicles. The proposed system can detect front vehicles such as the leading vehicle and side-lane vehicles. The position parameters of the vehicles located in front are obtained based on the detection information. The proposed vehicle detection system is implemented on a passenger car, and its performance is verified experimentally.
Improved mine blast algorithm for optimal cost design of water distribution systems
NASA Astrophysics Data System (ADS)
Sadollah, Ali; Guen Yoo, Do; Kim, Joong Hoon
2015-12-01
The design of water distribution systems is a large class of combinatorial, nonlinear optimization problems with complex constraints such as conservation of mass and energy equations. Since feasible solutions are often extremely complex, traditional optimization techniques are insufficient. Recently, metaheuristic algorithms have been applied to this class of problems because they are highly efficient. In this article, a recently developed optimizer called the mine blast algorithm (MBA) is considered. The MBA is improved and coupled with the hydraulic simulator EPANET to find the optimal cost design for water distribution systems. The performance of the improved mine blast algorithm (IMBA) is demonstrated using the well-known Hanoi, New York tunnels and Balerma benchmark networks. Optimization results obtained using IMBA are compared to those using MBA and other optimizers in terms of their minimum construction costs and convergence rates. For the complex Balerma network, IMBA offers the cheapest network design compared to other optimization algorithms.
Optimal design of optical reference signals by use of a genetic algorithm
NASA Astrophysics Data System (ADS)
Saez-Landete, José; Salcedo-Sanz, Sancho; Rosa-Zurera, Manuel; Alonso, José; Bernabeu, Eusebio
2005-10-01
A new technique for the generation of optical reference signals with optimal properties is presented. In grating measurement systems a reference signal is needed to achieve an absolute measurement of the position. The optical signal is the autocorrelation of two codes with binary transmittance. For a long time, the design of this type of code has required great computational effort, which limits the size of the code to ˜30 elements. Recently, the application of the dividing rectangles (DIRECT) algorithm has allowed the automatic design of codes up to 100 elements. Because of the binary nature of the problem and the parallel processing of the genetic algorithms, these algorithms are efficient tools for obtaining codes with particular autocorrelation properties. We design optimum zero reference codes with arbitrary length by means of a genetic algorithm enhanced with a restricted search operator.
New Meta Algorithms for Engineering Design Using Surrogate Functions
2005-04-01
Dennis, Jr., and Parviz Moin, Opti- mal aeroacoustic shape design using the surrogate management frame- work, Optimization and Engineering, 5(2):101...122, 2004. e Alison L. Marsden, Meng Wang, J. E. Dennis, Jr., and Parviz Moin), Suppression of vortex-shedding noise via derivative-free shape opti...solution. Contact: Dr. Dominique Orban (514)340-4711 ext 5967 "* Trailing edge design We have a collaboration with Parviz Moin’s tur- bulent flow group in
EvoOligo: oligonucleotide probe design with multiobjective evolutionary algorithms.
Shin, Soo-Yong; Lee, In-Hee; Cho, Young-Min; Yang, Kyung-Ae; Zhang, Byoung-Tak
2009-12-01
Probe design is one of the most important tasks in successful deoxyribonucleic acid microarray experiments. We propose a multiobjective evolutionary optimization method for oligonucleotide probe design based on the multiobjective nature of the probe design problem. The proposed multiobjective evolutionary approach has several distinguished features, compared with previous methods. First, the evolutionary approach can find better probe sets than existing simple filtering methods with fixed threshold values. Second, the multiobjective approach can easily incorporate the user's custom criteria or change the existing criteria. Third, our approach tries to optimize the combination of probes for the given set of genes, in contrast to other tools that independently search each gene for qualifying probes. Lastly, the multiobjective optimization method provides various sets of probe combinations, among which the user can choose, depending on the target application. The proposed method is implemented as a platform called EvoOligo and is available for service on the web. We test the performance of EvoOligo by designing probe sets for 19 types of Human Papillomavirus and 52 genes in the Arabidopsis Calmodulin multigene family. The design results from EvoOligo are proven to be superior to those from well-known existing probe design tools, such as OligoArray and OligoWiz.
Jaton, Florian
2017-09-01
This article documents the practical efforts of a group of scientists designing an image-processing algorithm for saliency detection. By following the actors of this computer science project, the article shows that the problems often considered to be the starting points of computational models are in fact provisional results of time-consuming, collective and highly material processes that engage habits, desires, skills and values. In the project being studied, problematization processes lead to the constitution of referential databases called 'ground truths' that enable both the effective shaping of algorithms and the evaluation of their performances. Working as important common touchstones for research communities in image processing, the ground truths are inherited from prior problematization processes and may be imparted to subsequent ones. The ethnographic results of this study suggest two complementary analytical perspectives on algorithms: (1) an 'axiomatic' perspective that understands algorithms as sets of instructions designed to solve given problems computationally in the best possible way, and (2) a 'problem-oriented' perspective that understands algorithms as sets of instructions designed to computationally retrieve outputs designed and designated during specific problematization processes. If the axiomatic perspective on algorithms puts the emphasis on the numerical transformations of inputs into outputs, the problem-oriented perspective puts the emphasis on the definition of both inputs and outputs.
Rasmussen, Luke V; Thompson, Will K; Pacheco, Jennifer A; Kho, Abel N; Carrell, David S; Pathak, Jyotishman; Peissig, Peggy L; Tromp, Gerard; Denny, Joshua C; Starren, Justin B
2014-10-01
Design patterns, in the context of software development and ontologies, provide generalized approaches and guidance to solving commonly occurring problems, or addressing common situations typically informed by intuition, heuristics and experience. While the biomedical literature contains broad coverage of specific phenotype algorithm implementations, no work to date has attempted to generalize common approaches into design patterns, which may then be distributed to the informatics community to efficiently develop more accurate phenotype algorithms. Using phenotyping algorithms stored in the Phenotype KnowledgeBase (PheKB), we conducted an independent iterative review to identify recurrent elements within the algorithm definitions. We extracted and generalized recurrent elements in these algorithms into candidate patterns. The authors then assessed the candidate patterns for validity by group consensus, and annotated them with attributes. A total of 24 electronic Medical Records and Genomics (eMERGE) phenotypes available in PheKB as of 1/25/2013 were downloaded and reviewed. From these, a total of 21 phenotyping patterns were identified, which are available as an online data supplement. Repeatable patterns within phenotyping algorithms exist, and when codified and cataloged may help to educate both experienced and novice algorithm developers. The dissemination and application of these patterns has the potential to decrease the time to develop algorithms, while improving portability and accuracy. Copyright © 2014 Elsevier Inc. All rights reserved.
Designer spin systems via inverse statistical mechanics
NASA Astrophysics Data System (ADS)
DiStasio, Robert A., Jr.; Marcotte, Étienne; Car, Roberto; Stillinger, Frank H.; Torquato, Salvatore
2013-10-01
nature of the target radial spin-spin correlation function. In the future, it will be interesting to explore whether such inverse statistical-mechanical techniques could be employed to design materials with desired spin properties.
Preliminary Design of a Manned Nuclear Electric Propulsion Vehicle Using Genetic Algorithms
Irwin, Ryan W.; Tinker, Michael L.
2005-02-06
Nuclear electric propulsion (NEP) vehicles will be needed for future manned missions to Mars and beyond. Candidate designs must be identified for further detailed design from a large array of possibilities. Genetic algorithms have proven their utility in conceptual design studies by effectively searching a large design space to pinpoint unique optimal designs. This research combined analysis codes for NEP subsystems with a genetic algorithm. The use of penalty functions with scaling ratios was investigated to increase computational efficiency. Also, the selection of design variables for optimization was considered to reduce computation time without losing beneficial design search space. Finally, trend analysis of a reference mission to the asteroids yielded a group of candidate designs for further analysis.
Preliminary Design of a Manned Nuclear Electric Propulsion Vehicle Using Genetic Algorithms
NASA Technical Reports Server (NTRS)
Irwin, Ryan W.; Tinker, Michael L.
2005-01-01
Nuclear electric propulsion (NEP) vehicles will be needed for future manned missions to Mars and beyond. Candidate designs must be identified for further detailed design from a large array of possibilities. Genetic algorithms have proven their utility in conceptual design studies by effectively searching a large design space to pinpoint unique optimal designs. This research combined analysis codes for NEP subsystems with a genetic algorithm. The use of penalty functions with scaling ratios was investigated to increase computational efficiency. Also, the selection of design variables for optimization was considered to reduce computation time without losing beneficial design search space. Finally, trend analysis of a reference mission to the asteroids yielded a group of candidate designs for further analysis.
Cui, Ganglong; Yang, Weitao
2011-05-28
The significance of conical intersections in photophysics, photochemistry, and photodissociation of polyatomic molecules in gas phase has been demonstrated by numerous experimental and theoretical studies. Optimization of conical intersections of small- and medium-size molecules in gas phase has currently become a routine optimization process, as it has been implemented in many electronic structure packages. However, optimization of conical intersections of small- and medium-size molecules in solution or macromolecules remains inefficient, even poorly defined, due to large number of degrees of freedom and costly evaluations of gradient difference and nonadiabatic coupling vectors. In this work, based on the sequential quantum mechanics and molecular mechanics (QM/MM) and QM/MM-minimum free energy path methods, we have designed two conical intersection optimization methods for small- and medium-size molecules in solution or macromolecules. The first one is sequential QM conical intersection optimization and MM minimization for potential energy surfaces; the second one is sequential QM conical intersection optimization and MM sampling for potential of mean force surfaces, i.e., free energy surfaces. In such methods, the region where electronic structures change remarkably is placed into the QM subsystem, while the rest of the system is placed into the MM subsystem; thus, dimensionalities of gradient difference and nonadiabatic coupling vectors are decreased due to the relatively small QM subsystem. Furthermore, in comparison with the concurrent optimization scheme, sequential QM conical intersection optimization and MM minimization or sampling reduce the number of evaluations of gradient difference and nonadiabatic coupling vectors because these vectors need to be calculated only when the QM subsystem moves, independent of the MM minimization or sampling. Taken together, costly evaluations of gradient difference and nonadiabatic coupling vectors in solution or
Designing Fuzzy Algorithms to Develop Healthy Dietary Pattern
Asghari, Golaleh; Ejtahed, Hanieh-Sadat; Sarsharzadeh, Mohammad Mahdi; Nazeri, Pantea; Mirmiran, Parvin
2013-01-01
Background Fuzzy logic, a mathematical approach, defines the percentage of desirability for recommended amount of food groups and describes the range of intakes, from deficiency to excess. Objectives The purpose of this research was to find the best fuzzy dietary pattern that constraints energy and nutrients by the iterative algorithm. Materials and Methods An index is derived that reflects how closely the diet of an individual meets all the nutrient requirements set by the dietary reference intake. Fuzzy pyramid pattern was applied for the energy levels from 1000 to 4000 Kcal which estimated the range of recommended servings for seven food groups including fruits, vegetables, grains, meats, milk, oils, fat and added sugar. Results The optimum (lower attention – upper attention) recommended servings per day for fruits, vegetables, grain, meat, dairy, and oils of the 2000 kcal diet were 4.06 (3.75-4.25), 6.69 (6.25-7.00), 5.69 (5.75-6.25), 4.94 (4.5-5.2), 2.75(2.50-3.00), and 2.56 (2.5-2.75), respectively. The fuzzy pattern met most recommended nutrient intake levels except for potassium and vitamin E, which were estimated at 98% and 69% of the dietary reference intake, respectively. Conclusions Using fuzzy logic provides an elegant mathematical solution for finding the optimum point of food groups in dietary pattern. PMID:24454416
Advanced algorithms for radiographic material discrimination and inspection system design
Gilbert, Andrew J.; McDonald, Benjamin S.; Deinert, Mark R.
2016-10-01
X-ray and neutron radiography are powerful tools for non-invasively inspecting the interior of objects. Materials can be discriminated by noting how the radiographic signal changes with variations in the input spectrum or inspection mode. However, current methods are limited in their ability to differentiate when multiple materials are present, especially within large and complex objects. With X-ray radiography, the inability to distinguish materials of a similar atomic number is especially problematic. To overcome these critical limitations, we augmented our existing inverse problem framework with two important expansions: 1) adapting the previous methodology for use with multi-modal radiography and energy-integrating detectors, and 2) applying the Cramer-Rao lower bound to select an optimal set of inspection modes for a given application a priori. Adding these expanded capabilities to our algorithmic framework with adaptive regularization, we observed improved discrimination between high-Z materials, specifically plutonium and tungsten. The combined system can estimate plutonium mass within our simulated system to within 1%. Three types of inspection modes were modeled: multi-endpoint X-ray radiography alone; in combination with neutron radiography using deuterium-deuterium (DD); or in combination with neutron radiography using deuterium-tritium (DT) sources.
Aerodynamics Design and Genetic Algorithms for Optimization of Airship Bodies
NASA Astrophysics Data System (ADS)
Nejati, Vahid; Matsuuchi, Kazuo
A special and effective aerodynamics calculation method has been applied for the flow field around a body of revolution to find the drag coefficient for a wide range of Reynolds numbers. The body profile is described by a first order continuous axial singularity distribution. The solution of the direct problem then gives the radius and inviscid velocity distribution. Viscous effects are considered by means of an integral boundary layer procedure, and for determination of the transition location the forced transition criterion is applied. By avoiding those profiles, which result in the separation of the boundary layer, the drag can be calculated at the end of the body by using Young's formula. In this study, a powerful optimization procedure known as a Genetic Algorithms (GA) is used for the first time in the shape optimization of airship hulls. GA represents a particular artificial intelligence technique for large spaces, striking a remarkable balance between exploration and exploitation of search space. This method could reach to minimum objective function through a better path, and also could minimize the drag coefficient faster for different Reynolds number regimes. It was found that GA is a powerful method for such multi-dimensional, multi-modal and nonlinear objective function.
Overlay measurement accuracy enhancement by design and algorithm
NASA Astrophysics Data System (ADS)
Lee, Honggoo; Lee, Byongseog; Han, Sangjun; Kim, Myoungsoo; Kwon, Wontaik; Park, Sungki; Choi, DongSub; Lee, Dohwa; Jeon, Sanghuck; Lee, Kangsan; Itzkovich, Tal; Amir, Nuriel; Volkovich, Roie; Herzel, Eitan; Wagner, Mark; El Kodadi, Mohamed
2015-03-01
Advanced design nodes require more complex lithography techniques, such as double patterning, as well as advanced materials like hard masks. This poses new challenge for overlay metrology and process control. In this publication several step are taken to face these challenges. Accurate overlay metrology solutions are demonstrated for advanced memory devices.
Two algorithms for neural-network design and training with application to channel equalization.
Sweatman, C Z; Mulgrew, B; Gibson, G J
1998-01-01
We describe two algorithms for designing and training neural-network classifiers. The first, the linear programming slab algorithm (LPSA), is motivated by the problem of reconstructing digital signals corrupted by passage through a dispersive channel and by additive noise. It constructs a multilayer perceptron (MLP) to separate two disjoint sets by using linear programming methods to identify network parameters. The second, the perceptron learning slab algorithm (PLSA), avoids the computational costs of linear programming by using an error-correction approach to identify parameters. Both algorithms operate in highly constrained parameter spaces and are able to exploit symmetry in the classification problem. Using these algorithms, we develop a number of procedures for the adaptive equalization of a complex linear 4-quadrature amplitude modulation (QAM) channel, and compare their performance in a simulation study. Results are given for both stationary and time-varying channels, the latter based on the COST 207 GSM propagation model.
A Computer Environment for Beginners' Learning of Sorting Algorithms: Design and Pilot Evaluation
ERIC Educational Resources Information Center
Kordaki, M.; Miatidis, M.; Kapsampelis, G.
2008-01-01
This paper presents the design, features and pilot evaluation study of a web-based environment--the SORTING environment--for the learning of sorting algorithms by secondary level education students. The design of this environment is based on modeling methodology, taking into account modern constructivist and social theories of learning while at…
A Computer Environment for Beginners' Learning of Sorting Algorithms: Design and Pilot Evaluation
ERIC Educational Resources Information Center
Kordaki, M.; Miatidis, M.; Kapsampelis, G.
2008-01-01
This paper presents the design, features and pilot evaluation study of a web-based environment--the SORTING environment--for the learning of sorting algorithms by secondary level education students. The design of this environment is based on modeling methodology, taking into account modern constructivist and social theories of learning while at…
On Polymorphic Circuits and Their Design Using Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Stoica, Adrian; Zebulum, Ricardo; Keymeulen, Didier; Lohn, Jason; Clancy, Daniel (Technical Monitor)
2002-01-01
This paper introduces the concept of polymorphic electronics (polytronics) - referring to electronics with superimposed built-in functionality. A function change does not require switches/reconfiguration as in traditional approaches. Instead the change comes from modifications in the characteristics of devices involved in the circuit, in response to controls such as temperature, power supply voltage (VDD), control signals, light, etc. The paper illustrates polytronic circuits in which the control is done by temperature, morphing signals, and VDD respectively. Polytronic circuits are obtained by evolutionary design/evolvable hardware techniques. These techniques are ideal for the polytronics design, a new area that lacks design guidelines, know-how,- yet the requirements/objectives are easy to specify and test. The circuits are evolved/synthesized in two different modes. The first mode explores an unstructured space, in which transistors can be interconnected freely in any arrangement (in simulations only). The second mode uses a Field Programmable Transistor Array (FPTA) model, and the circuit topology is sought as a mapping onto a programmable architecture (these experiments are performed both in simulations and on FPTA chips). The experiments demonstrated the synthesis. of polytronic circuits by evolution. The capacity of storing/hiding "extra" functions provides for watermark/invisible functionality, thus polytronics may find uses in intelligence/security applications.
Dietrich, Arne; Haider, Hilde
2015-08-01
Creative thinking is arguably the pinnacle of cerebral functionality. Like no other mental faculty, it has been omnipotent in transforming human civilizations. Probing the neural basis of this most extraordinary capacity, however, has been doggedly frustrated. Despite a flurry of activity in cognitive neuroscience, recent reviews have shown that there is no coherent picture emerging from the neuroimaging work. Based on this, we take a different route and apply two well established paradigms to the problem. First is the evolutionary framework that, despite being part and parcel of creativity research, has no informed experimental work in cognitive neuroscience. Second is the emerging prediction framework that recognizes predictive representations as an integrating principle of all cognition. We show here how the prediction imperative revealingly synthesizes a host of new insights into the way brains process variation-selection thought trials and present a new neural mechanism for the partial sightedness in human creativity. Our ability to run offline simulations of expected future environments and action outcomes can account for some of the characteristic properties of cultural evolutionary algorithms running in brains, such as degrees of sightedness, the formation of scaffolds to jump over unviable intermediate forms, or how fitness criteria are set for a selection process that is necessarily hypothetical. Prospective processing in the brain also sheds light on how human creating and designing - as opposed to biological creativity - can be accompanied by intentions and foresight. This paper raises questions about the nature of creative thought that, as far as we know, have never been asked before.
Chen, Deng-kai; Gu, Rong; Gu, Yu-feng; Yu, Sui-huai
2016-01-01
Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design. PMID:27630709
Yang, Yan-Pu; Chen, Deng-Kai; Gu, Rong; Gu, Yu-Feng; Yu, Sui-Huai
2016-01-01
Consumers' Kansei needs reflect their perception about a product and always consist of a large number of adjectives. Reducing the dimension complexity of these needs to extract primary words not only enables the target product to be explicitly positioned, but also provides a convenient design basis for designers engaging in design work. Accordingly, this study employs a numerical design structure matrix (NDSM) by parameterizing a conventional DSM and integrating genetic algorithms to find optimum Kansei clusters. A four-point scale method is applied to assign link weights of every two Kansei adjectives as values of cells when constructing an NDSM. Genetic algorithms are used to cluster the Kansei NDSM and find optimum clusters. Furthermore, the process of the proposed method is presented. The details of the proposed approach are illustrated using an example of electronic scooter for Kansei needs clustering. The case study reveals that the proposed method is promising for clustering Kansei needs adjectives in product emotional design.
Phase Response Design of Recursive All-Pass Digital Filters Using a Modified PSO Algorithm.
Chang, Wei-Der
2015-01-01
This paper develops a new design scheme for the phase response of an all-pass recursive digital filter. A variant of particle swarm optimization (PSO) algorithm will be utilized for solving this kind of filter design problem. It is here called the modified PSO (MPSO) algorithm in which another adjusting factor is more introduced in the velocity updating formula of the algorithm in order to improve the searching ability. In the proposed method, all of the designed filter coefficients are firstly collected to be a parameter vector and this vector is regarded as a particle of the algorithm. The MPSO with a modified velocity formula will force all particles into moving toward the optimal or near optimal solution by minimizing some defined objective function of the optimization problem. To show the effectiveness of the proposed method, two different kinds of linear phase response design examples are illustrated and the general PSO algorithm is compared as well. The obtained results show that the MPSO is superior to the general PSO for the phase response design of digital recursive all-pass filter.
Co-design of software and hardware to implement remote sensing algorithms
Theiler, J. P.; Frigo, J.; Gokhale, M.; Szymanski, J. J.
2001-01-01
Both for offline searches through large data archives and for onboard computation at the sensor head, there is a growing need for ever-more rapid processing of remote sensing data. For many algorithms of use in remote sensing, the bulk of the processing takes place in an 'inner loop' with a large number of simple operations. For these algorithms, dramatic speedups can often be obtained with specialized hardware. The difficulty and expense of digital design continues to limit applicability of this approach, but the development of new design tools is making this approach more feasible, and some notable successes have been reported. On the other hand, it is often the case that processing can also be accelerated by adopting a more sophisticated algorithm design. Unfortunately, a more sophisticated algorithm is much harder to implement in hardware, so these approaches are often at odds with each other. With careful planning, however, it is sometimes possible to combine software and hardware design in such a way that each complements the other, and the final implementation achieves speedup that would not have been possible with a hardware-only or a software-only solution. We will in particular discuss the co-design of software and hardware to achieve substantial speedup of algorithms for multispectral image segmentation and for endmember identification.
On the impact of communication complexity in the design of parallel numerical algorithms
NASA Technical Reports Server (NTRS)
Gannon, D.; Vanrosendale, J.
1984-01-01
This paper describes two models of the cost of data movement in parallel numerical algorithms. One model is a generalization of an approach due to Hockney, and is suitable for shared memory multiprocessors where each processor has vector capabilities. The other model is applicable to highly parallel nonshared memory MIMD systems. In the second model, algorithm performance is characterized in terms of the communication network design. Techniques used in VLSI complexity theory are also brought in, and algorithm independent upper bounds on system performance are derived for several problems that are important to scientific computation.
The design of efficient dynamic programming and transfer matrix enumeration algorithms
NASA Astrophysics Data System (ADS)
Conway, Andrew R.
2017-09-01
Many algorithms have been developed for enumerating various combinatorial objects in time exponentially less than the number of objects. Two common classes of algorithms are dynamic programming and the transfer matrix method. This paper covers the design and implementation of such algorithms. A host of general techniques for improving efficiency are described. Three quite different example problems are used for detailed examples: 1324 pattern avoiding permutations, three-dimensional polycubes (using a novel approach), and two-dimensional directed animals. Other examples from the literature are used when appropriate to describe applicability of various techniques, but the paper does not attempt to survey all applications.
NASA Astrophysics Data System (ADS)
Southall, Hugh L.; O'Donnell, Teresa H.; Derov, John S.
2010-04-01
EGO is an evolutionary, data-adaptive algorithm which can be useful for optimization problems with expensive cost functions. Many antenna design problems qualify since complex computational electromagnetics (CEM) simulations can take significant resources. This makes evolutionary algorithms such as genetic algorithms (GA) or particle swarm optimization (PSO) problematic since iterations of large populations are required. In this paper we discuss multiparameter optimization of a wideband, single-element antenna over a metamaterial ground plane and the interfacing of EGO (optimization) with a full-wave CEM simulation (cost function evaluation).
Li, Zong-Tao; Wu, Tie-Jun; Lin, Can-Long; Ma, Long-Hua
2011-01-01
A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform.
Li, Zong-Tao; Wu, Tie-Jun; Lin, Can-Long; Ma, Long-Hua
2011-01-01
A new generalized optimum strapdown algorithm with coning and sculling compensation is presented, in which the position, velocity and attitude updating operations are carried out based on the single-speed structure in which all computations are executed at a single updating rate that is sufficiently high to accurately account for high frequency angular rate and acceleration rectification effects. Different from existing algorithms, the updating rates of the coning and sculling compensations are unrelated with the number of the gyro incremental angle samples and the number of the accelerometer incremental velocity samples. When the output sampling rate of inertial sensors remains constant, this algorithm allows increasing the updating rate of the coning and sculling compensation, yet with more numbers of gyro incremental angle and accelerometer incremental velocity in order to improve the accuracy of system. Then, in order to implement the new strapdown algorithm in a single FPGA chip, the parallelization of the algorithm is designed and its computational complexity is analyzed. The performance of the proposed parallel strapdown algorithm is tested on the Xilinx ISE 12.3 software platform and the FPGA device XC6VLX550T hardware platform on the basis of some fighter data. It is shown that this parallel strapdown algorithm on the FPGA platform can greatly decrease the execution time of algorithm to meet the real-time and high precision requirements of system on the high dynamic environment, relative to the existing implemented on the DSP platform. PMID:22164058
A novel scheme to design the filter for CT reconstruction using FBP algorithm.
Shi, Hongli; Luo, Shuqian
2013-06-01
The Filtered Back-Projection (FBP) algorithm is the most important technique for computerized tomographic (CT) imaging, in which the ramp filter plays a key role. FBP algorithm had been derived using the continuous system model. However, it has to be discretized in practical applications, which necessarily produces distortion in the reconstructed images. A novel scheme is proposed to design the filters to substitute the standard ramp filter to improve the reconstruction performance for parallel beam tomography. The design scheme is presented under the discrete image model and discrete projection environment. The designs are achieved by constrained optimization procedures. The designed filter can be regarded as the optimal filter for the corresponding parameters in some ways. Some filters under given parameters (such as image size and scanning angles) have been designed. The performance evaluation of CT reconstruction shows that the designed filters are better than the ramp filter in term of some general criteria. The 2-D or 3-D FBP algorithms for fan beam tomography used in most CT systems, are obtained by modifying the FBP algorithm for parallel beam tomography. Therefore, the designed filters can be used for fan beam tomography and have potential applications in practical CT systems.
NASA Astrophysics Data System (ADS)
Aiyoshi, Eitaro; Masuda, Kazuaki
On the basis of market fundamentalism, new types of social systems with the market mechanism such as electricity trading markets and carbon dioxide (CO2) emission trading markets have been developed. However, there are few textbooks in science and technology which present the explanation that Lagrange multipliers can be interpreted as market prices. This tutorial paper explains that (1) the steepest descent method for dual problems in optimization, and (2) Gauss-Seidel method for solving the stationary conditions of Lagrange problems with market principles, can formulate the mechanism of market pricing, which works even in the information-oriented modern society. The authors expect readers to acquire basic knowledge on optimization theory and algorithms related to economics and to utilize them for designing the mechanism of more complicated markets.
The Design of Flux-Corrected Transport (FCT) Algorithms for Structured Grids
NASA Astrophysics Data System (ADS)
Zalesak, Steven T.
A given flux-corrected transport (FCT) algorithm consists of three components: (1) a high order algorithm to which it reduces in smooth parts of the flow; (2) a low order algorithm to which it reduces in parts of the flow devoid of smoothness; and (3) a flux limiter which calculates the weights assigned to the high and low order fluxes in various regions of the flow field. One way of optimizing an FCT algorithm is to optimize each of these three components individually. We present some of the ideas that have been developed over the past 30 years toward this end. These include the use of very high order spatial operators in the design of the high order fluxes, non-clipping flux limiters, the appropriate choice of constraint variables in the critical flux-limiting step, and the implementation of a "failsafe" flux-limiting strategy. This chapter confines itself to the design of FCT algorithms for structured grids, using a finite volume formalism, for this is the area with which the present author is most familiar. The reader will find excellent material on the design of FCT algorithms for unstructured grids, using both finite volume and finite element formalisms, in the chapters by Professors Löhner, Baum, Kuzmin, Turek, and Möller in the present volume.
Small, high pressure ratio compressor: Aerodynamic and mechanical design
NASA Technical Reports Server (NTRS)
Bryce, C. A.; Erwin, J. R.; Perrone, G. L.; Nelson, E. L.; Tu, R. K.; Bosco, A.
1973-01-01
The Small, High-Pressure-Ratio Compressor Program was directed toward the analysis, design, and fabrication of a centrifugal compressor providing a 6:1 pressure ratio and an airflow rate of 2.0 pounds per second. The program consists of preliminary design, detailed areodynamic design, mechanical design, and mechanical acceptance tests. The preliminary design evaluate radial- and backward-curved blades, tandem bladed impellers, impeller-and diffuser-passage boundary-layer control, and vane, pipe, and multiple-stage diffusers. Based on this evaluation, a configuration was selected for detailed aerodynamic and mechanical design. Mechanical acceptance test was performed to demonstrate that mechanical design objectives of the research package were met.
Evolutionary algorithm for the neutrino factory front end design
Poklonskiy, Alexey A.; Neuffer, David; /Fermilab
2009-01-01
The Neutrino Factory is an important tool in the long-term neutrino physics program. Substantial effort is put internationally into designing this facility in order to achieve desired performance within the allotted budget. This accelerator is a secondary beam machine: neutrinos are produced by means of the decay of muons. Muons, in turn, are produced by the decay of pions, produced by hitting the target by a beam of accelerated protons suitable for acceleration. Due to the physics of this process, extra conditioning of the pion beam coming from the target is needed in order to effectively perform subsequent acceleration. The subsystem of the Neutrino Factory that performs this conditioning is called Front End, its main performance characteristic is the number of the produced muons.
Design and experimental evaluation of flexible manipulator control algorithms
Kwon, D.S.; Hwang, D.H.; Babcock, S.M.; Kress, R.L.; Lew, J.Y.; Evans, M.S.
1995-04-01
Within the Environmental Restoration and Waste Management Program of the US Department of Energy, the remediation of single-shell radioactive waste storage tanks is one of the areas that challenge state-of-the-art equipment and methods. The use of long-reach manipulators is being seriously considered for this task. Because of high payload capacity and high length-to-cross-section ratio requirements, these long-reach manipulator systems are expected to use hydraulic actuators and to exhibit significant structural flexibility. The controller has been designed to compensate for the hydraulic actuator dynamics by using a load-compensated velocity feedforward loop and to increase the bandwidth by using an inner pressure feedback loop. Shaping filter techniques have been applied as feedforward controllers to avoid structural vibrations during operation. Various types of shaping filter methods have been investigated. Among them, a new approach, referred to as a ``feedforward simulation filter`` that uses embedded simulation, has been presented.
Design of a blade stiffened composite panel by a genetic algorithm
NASA Technical Reports Server (NTRS)
Nagendra, S.; Haftka, R. T.; Gurdal, Z.
1993-01-01
Genetic algorithms (GAs) readily handle discrete problems, and can be made to generate many optima, as is presently illustrated for the case of design for minimum-weight stiffened panels with buckling constraints. The GA discrete design procedure proved superior to extant alternatives for both stiffened panels with cutouts and without cutouts. High computational costs are, however, associated with this discrete design approach at the current level of its development.
New bionic navigation algorithm based on the visual navigation mechanism of bees
NASA Astrophysics Data System (ADS)
Huang, Yufeng; Liu, Yi; Liu, Jianguo
2015-04-01
Through some research on visual navigation mechanisms of flying insects especially honeybees, a novel navigation algorithm integrating entropy flow with Kalman filter has been introduced in this paper. Concepts of entropy image and entropy flow are also introduced, which can characterize topographic features and measure changes of the image respectively. To characterize texture feature and spatial distribution of an image, a new concept of contrast entropy image has been presented in this paper. Applying the contrast entropy image to the navigation algorithm to test its' performance of navigation and comparing with simulation results of intensity entropy image, a conclusion that contrast entropy image performs better and more robust in navigation has been made.
Mechanical Design Support System Based on Thinking Process Development Diagram
NASA Astrophysics Data System (ADS)
Mase, Hisao; Kinukawa, Hiroshi; Morii, Hiroshi; Nakao, Masayuki; Hatamura, Yotaro
This paper describes a system that directly supports a design process in a mechanical domain. This system is based on a thinking process development diagram that draws distinctions between requirement, tasks, solutions, and implementation, which enables designers to expand and deepen their thoughts of design. The system provides five main functions that designers require in each phase of the proposed design process: (1) thinking process description support which enables designers to describe their thoughts, (2) creativity support by term association with thesauri, (3) timely display of design knowledge including know-how obtained through earlier failures, general design theories, standard-parts data, and past designs, (4) design problem solving support using 46 kinds of thinking operations, and (5) proper technology transfer support which accumulates not only design conclusions but also the design process. Though this system is applied to mechanical engineering as the first target domain, it can be easily expanded to many other domains such as architecture and electricity.
Mechanical Design of the DAMPE BGO Calorimeter
NASA Astrophysics Data System (ADS)
Hu, Yiming; Wu, Jian; Feng, Changqing; Zhang, Yunlong; Chen, Dengyi; Chang, Jin
The Dark Matter Particle Explorer, DAMPE, is a new designed satellite developed for the CASs new Innovation 2020 program. As the main component of DAMPE, the new designed BGO calorimeter consists of 308 BGO Crystals coupled with photomultiplier tube.The reliability and safety of the BGO Calorimeter structure play a very important role in the operation of whole detector. During the rocket launch, the calorimeter structure should be stable against vibration and environmental factors to ensure detector works in good conditions. In this article, we make the BGO calorimeter structure design, and then prove that it will work in the environments of rocket launch and flight.
Peto, Myron; Kloczkowski, Andrzej; Honavar, Vasant; Jernigan, Robert L
2008-01-01
Background By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Naïve Bayes and other machine learning algorithms we are able to distinguish between two classes of protein sequences: those folding to highly-designable conformations, or those folding to poorly- or non-designable conformations. Results First, we generate all possible compact lattice conformations for the specified shape (a hexagon or a triangle) on the 2D triangular lattice. Then we generate all possible binary hydrophobic/polar (H/P) sequences and by using a specified energy function, thread them through all of these compact conformations. If for a given sequence the lowest energy is obtained for a particular lattice conformation we assume that this sequence folds to that conformation. Highly-designable conformations have many H/P sequences folding to them, while poorly-designable conformations have few or no H/P sequences. We classify sequences as folding to either highly – or poorly-designable conformations. We have randomly selected subsets of the sequences belonging to highly-designable and poorly-designable conformations and used them to train several different standard machine learning algorithms. Conclusion By using these machine learning algorithms with ten-fold cross-validation we are able to classify the two classes of sequences with high accuracy – in some cases exceeding 95%. PMID:19014713
NASA Astrophysics Data System (ADS)
Lin, Jeng-Wen; Shen, Pu Fun; Wen, Hao-Ping
2015-10-01
The application of a repetitive control mechanism for use in a mechanical control system has been a topic of investigation. The fundamental purpose of repetitive control is to eliminate disturbances in a mechanical control system. This paper presents two different repetitive control laws using individual types of basis function feedback and their combinations. These laws adjust the command given to a feedback control system to eliminate tracking errors, generally resulting from periodic disturbance. Periodic errors can be reduced through linear basis functions using regression and a genetic algorithm. The results illustrate that repetitive control is most effective method for eliminating disturbances. When the data are stabilized, the tracking error of the obtained convergence value, 10-14, is the optimal solution, verifying that the proposed regression and genetic algorithm can satisfactorily reduce periodic errors.
Analysis and design of algorithm-based fault-tolerant systems
NASA Technical Reports Server (NTRS)
Nair, V. S. Sukumaran
1990-01-01
An important consideration in the design of high performance multiprocessor systems is to ensure the correctness of the results computed in the presence of transient and intermittent failures. Concurrent error detection and correction have been applied to such systems in order to achieve reliability. Algorithm Based Fault Tolerance (ABFT) was suggested as a cost-effective concurrent error detection scheme. The research was motivated by the complexity involved in the analysis and design of ABFT systems. To that end, a matrix-based model was developed and, based on that, algorithms for both the design and analysis of ABFT systems are formulated. These algorithms are less complex than the existing ones. In order to reduce the complexity further, a hierarchical approach is developed for the analysis of large systems.
NASA Astrophysics Data System (ADS)
Reed, Patrick; Minsker, Barbara S.; Goldberg, David E.
2003-07-01
Many water resources problems require careful balancing of fiscal, technical, and social objectives. Informed negotiation and balancing of objectives can be greatly aided through the use of evolutionary multiobjective optimization (EMO) algorithms, which can evolve entire tradeoff (or Pareto) surfaces within a single run. The primary difficulty in using these methods lies in the large number of parameters that must be specified to ensure that these algorithms effectively quantify design tradeoffs. This technical note addresses this difficulty by introducing a multipopulation design methodology that automates parameter specification for the nondominated sorted genetic algorithm-II (NSGA-II). The NSGA-II design methodology is successfully demonstrated on a multiobjective long-term groundwater monitoring application. Using this methodology, multiobjective optimization problems can now be solved automatically with only a few simple user inputs.
Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design
Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco
2016-01-01
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms. PMID:27886061
Accelerating Families of Fuzzy K-Means Algorithms for Vector Quantization Codebook Design.
Mata, Edson; Bandeira, Silvio; de Mattos Neto, Paulo; Lopes, Waslon; Madeiro, Francisco
2016-11-23
The performance of signal processing systems based on vector quantization depends on codebook design. In the image compression scenario, the quality of the reconstructed images depends on the codebooks used. In this paper, alternatives are proposed for accelerating families of fuzzy K-means algorithms for codebook design. The acceleration is obtained by reducing the number of iterations of the algorithms and applying efficient nearest neighbor search techniques. Simulation results concerning image vector quantization have shown that the acceleration obtained so far does not decrease the quality of the reconstructed images. Codebook design time savings up to about 40% are obtained by the accelerated versions with respect to the original versions of the algorithms.
Optimization of experimental design in fMRI: a general framework using a genetic algorithm.
Wager, Tor D; Nichols, Thomas E
2003-02-01
This article describes a method for selecting design parameters and a particular sequence of events in fMRI so as to maximize statistical power and psychological validity. Our approach uses a genetic algorithm (GA), a class of flexible search algorithms that optimize designs with respect to single or multiple measures of fitness. Two strengths of the GA framework are that (1) it operates with any sort of model, allowing for very specific parameterization of experimental conditions, including nonstandard trial types and experimentally observed scanner autocorrelation, and (2) it is flexible with respect to fitness criteria, allowing optimization over known or novel fitness measures. We describe how genetic algorithms may be applied to experimental design for fMRI, and we use the framework to explore the space of possible fMRI design parameters, with the goal of providing information about optimal design choices for several types of designs. In our simulations, we considered three fitness measures: contrast estimation efficiency, hemodynamic response estimation efficiency, and design counterbalancing. Although there are inherent trade-offs between these three fitness measures, GA optimization can produce designs that outperform random designs on all three criteria simultaneously.
EMILiO: a fast algorithm for genome-scale strain design.
Yang, Laurence; Cluett, William R; Mahadevan, Radhakrishnan
2011-05-01
Systems-level design of cell metabolism is becoming increasingly important for renewable production of fuels, chemicals, and drugs. Computational models are improving in the accuracy and scope of predictions, but are also growing in complexity. Consequently, efficient and scalable algorithms are increasingly important for strain design. Previous algorithms helped to consolidate the utility of computational modeling in this field. To meet intensifying demands for high-performance strains, both the number and variety of genetic manipulations involved in strain construction are increasing. Existing algorithms have experienced combinatorial increases in computational complexity when applied toward the design of such complex strains. Here, we present EMILiO, a new algorithm that increases the scope of strain design to include reactions with individually optimized fluxes. Unlike existing approaches that would experience an explosion in complexity to solve this problem, we efficiently generated numerous alternate strain designs producing succinate, l-glutamate and l-serine. This was enabled by successive linear programming, a technique new to the area of computational strain design.
Uncertainty-based Optimization Algorithms in Designing Fractionated Spacecraft
Ning, Xin; Yuan, Jianping; Yue, Xiaokui
2016-01-01
A fractionated spacecraft is an innovative application of a distributive space system. To fully understand the impact of various uncertainties on its development, launch and in-orbit operation, we use the stochastic missioncycle cost to comprehensively evaluate the survivability, flexibility, reliability and economy of the ways of dividing the various modules of the different configurations of fractionated spacecraft. We systematically describe its concept and then analyze its evaluation and optimal design method that exists during recent years and propose the stochastic missioncycle cost for comprehensive evaluation. We also establish the models of the costs such as module development, launch and deployment and the impacts of their uncertainties respectively. Finally, we carry out the Monte Carlo simulation of the complete missioncycle costs of various configurations of the fractionated spacecraft under various uncertainties and give and compare the probability density distribution and statistical characteristics of its stochastic missioncycle cost, using the two strategies of timing module replacement and non-timing module replacement. The simulation results verify the effectiveness of the comprehensive evaluation method and show that our evaluation method can comprehensively evaluate the adaptability of the fractionated spacecraft under different technical and mission conditions. PMID:26964755
NASA Technical Reports Server (NTRS)
Tinker, Michael L.; Steincamp, James W.; Stewart, Eric T.; Patton, Bruce W.; Pannell, William P.; Newby, Ronald L.; Coffman, Mark E.; Qualls, A. L.; Bancroft, S.; Molvik, Greg
2003-01-01
The Nuclear Electric Vehicle Optimization Toolset (NEVOT) optimizes the design of all major Nuclear Electric Propulsion (NEP) vehicle subsystems for a defined mission within constraints and optimization parameters chosen by a user. The tool uses a Genetic Algorithm (GA) search technique to combine subsystem designs and evaluate the fitness of the integrated design to fulfill a mission. The fitness of an individual is used within the GA to determine its probability of survival through successive generations in which the designs with low fitness are eliminated and replaced with combinations or mutations of designs with higher fitness. The program can find optimal solutions for different sets of fitness metrics without modification and can create and evaluate vehicle designs that might never be conceived of through traditional design techniques. It is anticipated that the flexible optimization methodology will expand present knowledge of the design trade-offs inherent in designing nuclear powered space vehicles and lead to improved NEP designs.
Should my patient use a mechanical lift? Part 2: algorithm and case application.
Douglas, Brenda; Fitzpatrick, Diane; Golub-Victor, Ann; Lowe, Susan M
2014-03-01
The use of algorithms for safe patient handling in the acute care setting has been established and integrated into the standards of practice. This is not the case in the home care setting where the patient and caregivers are at risk for injury during patient transfers. Many factors need to be assessed before recommending a mechanical lift for home use. Some of the factors include the patient's weight-bearing status, cognitive level, and upper extremity strength, and the caregiver's ability to lift more than 35 pounds. All of these factors have been included in the clinical decision-making algorithm described in this article. Two case scenarios are presented to assist the reader with the analysis and application of the algorithm.
NASA Astrophysics Data System (ADS)
Canadell, Marta; Haro, Àlex
2017-05-01
We present several algorithms for computing normally hyperbolic invariant tori carrying quasi-periodic motion of a fixed frequency in families of dynamical systems. The algorithms are based on a KAM scheme presented in Canadell and Haro (J Nonlinear Sci, 2016. doi: 10.1007/s00332-017-9389-y), to find the parameterization of the torus with prescribed dynamics by detuning parameters of the model. The algorithms use different hyperbolicity and reducibility properties and, in particular, compute also the invariant bundles and Floquet transformations. We implement these methods in several 2-parameter families of dynamical systems, to compute quasi-periodic arcs, that is, the parameters for which 1D normally hyperbolic invariant tori with a given fixed frequency do exist. The implementation lets us to perform the continuations up to the tip of the quasi-periodic arcs, for which the invariant curves break down. Three different mechanisms of breakdown are analyzed, using several observables, leading to several conjectures.
MSFC Three Point Docking Mechanism design review
NASA Astrophysics Data System (ADS)
Schaefer, Otto; Ambrosio, Anthony
1992-12-01
In the next few decades, we will be launching expensive satellites and space platforms that will require recovery for economic reasons, because of initial malfunction, servicing, repairs, or out of a concern for post lifetime debris removal. The planned availability of a Three Point Docking Mechanism (TPDM) is a positive step towards an operational satellite retrieval infrastructure. This study effort supports NASA/MSFC engineering work in developing an automated docking capability. The work was performed by the Grumman Space & Electronics Group as a concept evaluation/test for the Tumbling Satellite Retrieval Kit. Simulation of a TPDM capture was performed in Grumman's Large Amplitude Space Simulator (LASS) using mockups of both parts (the mechanism and payload). Similar TPDM simulation activities and more extensive hardware testing was performed at NASA/MSFC in the Flight Robotics Laboratory and Space Station/Space Operations Mechanism Test Bed (6-DOF Facility).
MSFC Three Point Docking Mechanism design review
NASA Technical Reports Server (NTRS)
Schaefer, Otto; Ambrosio, Anthony
1992-01-01
In the next few decades, we will be launching expensive satellites and space platforms that will require recovery for economic reasons, because of initial malfunction, servicing, repairs, or out of a concern for post lifetime debris removal. The planned availability of a Three Point Docking Mechanism (TPDM) is a positive step towards an operational satellite retrieval infrastructure. This study effort supports NASA/MSFC engineering work in developing an automated docking capability. The work was performed by the Grumman Space & Electronics Group as a concept evaluation/test for the Tumbling Satellite Retrieval Kit. Simulation of a TPDM capture was performed in Grumman's Large Amplitude Space Simulator (LASS) using mockups of both parts (the mechanism and payload). Similar TPDM simulation activities and more extensive hardware testing was performed at NASA/MSFC in the Flight Robotics Laboratory and Space Station/Space Operations Mechanism Test Bed (6-DOF Facility).
Multidisciplinary Design, Analysis, and Optimization Tool Development Using a Genetic Algorithm
NASA Technical Reports Server (NTRS)
Pak, Chan-gi; Li, Wesley
2009-01-01
Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) to automate analysis and design process by leveraging existing tools to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic, and hypersonic aircraft. This is a promising technology, but faces many challenges in large-scale, real-world application. This report describes current approaches, recent results, and challenges for multidisciplinary design, analysis, and optimization as demonstrated by experience with the Ikhana fire pod design.!
Directional design of optical lens based on metallic nano-slits by Yang-Gu algorithm
NASA Astrophysics Data System (ADS)
Zhu, Qiaofen; Zhang, Yan
2010-11-01
Directional design of optical lenses based on metallic nano-slits that can focus light in different style by Yang-Gu (YG) algorithm. Both of the relative phase and amplitude of emitting light scattered by surface plasmon in a single subwavelength slit and modulated by the width of the slit or the thickness of the lens of the lens have been considered in the design processing. A form of the YG algorithm which considers both the phase and amplitude changing is derived. Two kinds of nanolenses are designed by this numerical method, one with one focal spot, and another with two focal spots in one focal plane. According to the finite-different time-domain (FDTD) method numerical calculation, it is found that the functions of the designed lenses agree well with preassigned goal. This method may be useful to design subwavelength optical devices that can be integrated into other optical and optoelectronic elements.
The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic
Li, Ning; Martínez, José-Fernán; Díaz, Vicente Hernández
2015-01-01
Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively. PMID:26266412
The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic.
Li, Ning; Martínez, José-Fernán; Hernández Díaz, Vicente
2015-08-10
Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters' dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.
Infrastructure Retrofit Design via Composite Mechanics
NASA Technical Reports Server (NTRS)
Chamis, Christos, C.; Gotsis,Pascal K.
1998-01-01
Select applications are described to illustrate the concept for retrofitting reinforced concrete infrastructure with fiber reinforced plastic laminates. The concept is first illustrated by using an axially loaded reinforced concrete column. A reinforced concrete arch and a dome are then used to illustrate the versatility of the concept. Advanced methods such as finite element structural analysis and progressive structural fracture are then used to evaluate the retrofitting laminate adequacy. Results obtains show that retrofits can be designed to double and even triple the as-designed load of the select reinforced concrete infrastructures.
Validation of space/ground antenna control algorithms using a computer-aided design tool
NASA Technical Reports Server (NTRS)
Gantenbein, Rex E.
1995-01-01
The validation of the algorithms for controlling the space-to-ground antenna subsystem for Space Station Alpha is an important step in assuring reliable communications. These algorithms have been developed and tested using a simulation environment based on a computer-aided design tool that can provide a time-based execution framework with variable environmental parameters. Our work this summer has involved the exploration of this environment and the documentation of the procedures used to validate these algorithms. We have installed a variety of tools in a laboratory of the Tracking and Communications division for reproducing the simulation experiments carried out on these algorithms to verify that they do meet their requirements for controlling the antenna systems. In this report, we describe the processes used in these simulations and our work in validating the tests used.
Rolamite - A new mechanical design concept
NASA Technical Reports Server (NTRS)
Wilkes, D. F.
1967-01-01
Rolamite, a mechanical suspension system, provides substantial reductions in friction in the realm of extremely low bearing pressures. In addition, rolamite devices are easily microminiaturized, are extremely tolerant of production variations and are inherently capable of virtually all functions to construct most electromechanical devices.
A Proposal of CAD Mechanism for Design Knowledge Management
NASA Astrophysics Data System (ADS)
Nomaguchi, Yutaka; Yoshioka, Masaharu; Tomiyama, Tetsuo
In this paper, we propose a fundamental idea of a new CAD mechanism to facilitate design knowledge management. This mechanism encourages a designer to externalise his/her knowledge during a design process and facilitates sharing and reuse of such externalised design knowledge in later stages. We also describe the implementation of this idea called DDMS (Design Documentation Management System). DDMS works as a front end to KIEF (Knowledge Intensive Engineering Framework), which we have been developing. We also illustrate an example of machining tool design to demonstrate the features of DDMS.
The design and results of an algorithm for intelligent ground vehicles
NASA Astrophysics Data System (ADS)
Duncan, Matthew; Milam, Justin; Tote, Caleb; Riggins, Robert N.
2010-01-01
This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for its 2009 Intelligent Ground Vehicle Competition (IGVC) robot called Anassa V. The BSC robotics team is comprised of undergraduate computer science, engineering technology, marketing students, and one robotics faculty advisor. The team has participated in IGVC since the year 2000. A major part of the design process that the BSC team uses each year for IGVC is a fully documented "Post-IGVC Analysis." Over the nine years since 2000, the lessons the students learned from these analyses have resulted in an ever-improving, highly successful autonomous algorithm. The algorithm employed in Anassa V is a culmination of past successes and new ideas, resulting in Anassa V earning several excellent IGVC 2009 performance awards, including third place overall. The paper will discuss all aspects of the design of this autonomous robotic system, beginning with the design process and ending with test results for both simulation and real environments.
Genetic algorithm with a crossover elitist preservation mechanism for protein-ligand docking.
Guan, Boxin; Zhang, Changsheng; Ning, Jiaxu
2017-09-13
Protein-ligand docking plays an important role in computer-aided pharmaceutical development. Protein-ligand docking can be defined as a search algorithm with a scoring function, whose aim is to determine the conformation of the ligand and the receptor with the lowest energy. Hence, to improve an efficient algorithm has become a very significant challenge. In this paper, a novel search algorithm based on crossover elitist preservation mechanism (CEP) for solving protein-ligand docking problems is proposed. The proposed algorithm, namely genetic algorithm with crossover elitist preservation (CEPGA), employ the CEP to keep the elite individuals of the last generation and make the crossover more efficient and robust. The performance of CEPGA is tested on sixteen molecular docking complexes from RCSB protein data bank. In comparison with GA, LGA and SODOCK in the aspects of lowest energy and highest accuracy, the results of which indicate that the CEPGA is a reliable and successful method for protein-ligand docking problems.
Geometric design of mechanical linkages for contact specifications
NASA Astrophysics Data System (ADS)
Robson, Nina Patarinsky
2008-10-01
This dissertation focuses on the kinematic synthesis of mechanical linkages in order to guide an end-effortor so that it maintains contact with specified objects in its workspace. Assuming the serial chain does not have full mobility in its workspace, the contact geometry is used to determine the dimensions of the serial chain. The approach to this problem, is to use the relative curvature of the contact of the end-effector with one or more objects to define velocity and acceleration specifications for its movement. This provides kinematic constraints that are used to synthesize the dimensions of the serial chain. The mathematical formulation of the geometric design problem, leads to systems of multivariable polynomial equations, which are solved exactly using sparse matrix resultants and polynomial homotopy methods. The results from this research yield planar RR and 4R linkages that match a specified contact geometry, spatial TS, parallel RRS and perpendicular RRS linkages that have a required acceleration specification. A new strategy for a robot recovery from actuator failures is demonstrated for the Mars Exploratory Rover Arm. In extending this work to spatial serial chains, a new method based on sparse matrix resultants was developed, which solves exact synthesis problems with acceleration constraints. Further the research builds on the theoretical concepts of contact relationships for spatial movement. The connection between kinematic synthesis and contact problems and its extension to spatial synthesis are developed in this dissertation for the first time and are new contributions. The results, which rely upon the use of surface curvature effects to reduce the number of fixtures needed to immobilize an object, find applications in robot grasping and part-fixturing. The recovery strategy, presented in this research is also a new concept. The recognition that it is possible to reconfigure a crippled robotic system to achieve mission critical tasks can guide
Genetic algorithm-based design method for multilevel anisotropic diffraction gratings
NASA Astrophysics Data System (ADS)
Okamoto, Hiroyuki; Noda, Kohei; Sakamoto, Moritsugu; Sasaki, Tomoyuki; Wada, Yasuhiro; Kawatsuki, Nobuhiro; Ono, Hiroshi
2017-08-01
We developed a method for the design of multilevel anisotropic diffraction gratings based on a genetic algorithm. The method is used to design the multilevel anisotropic diffraction gratings based on input data that represent the output from the required grating. The validity of the proposed method was evaluated by designing a multilevel anisotropic diffraction grating using the outputs from an orthogonal circular polarization grating. The design results corresponded to the orthogonal circular polarization grating structures that were used to provide outputs to act as the input data for the process. Comparison with existing design methods shows that the proposed method can reduce the number of human processes that are required to design multilevel anisotropic diffraction gratings. Additionally, the method will be able to design complex structures without any requirement for subsequent examination by a human designer. The method can contribute to the development of optical elements by designing multilevel anisotropic diffraction gratings.
An Adaptive Defect Weighted Sampling Algorithm to Design Pseudoknotted RNA Secondary Structures.
Zandi, Kasra; Butler, Gregory; Kharma, Nawwaf
2016-01-01
Computational design of RNA sequences that fold into targeted secondary structures has many applications in biomedicine, nanotechnology and synthetic biology. An RNA molecule is made of different types of secondary structure elements and an important RNA element named pseudoknot plays a key role in stabilizing the functional form of the molecule. However, due to the computational complexities associated with characterizing pseudoknotted RNA structures, most of the existing RNA sequence designer algorithms generally ignore this important structural element and therefore limit their applications. In this paper we present a new algorithm to design RNA sequences for pseudoknotted secondary structures. We use NUPACK as the folding algorithm to compute the equilibrium characteristics of the pseudoknotted RNAs, and describe a new adaptive defect weighted sampling algorithm named Enzymer to design low ensemble defect RNA sequences for targeted secondary structures including pseudoknots. We used a biological data set of 201 pseudoknotted structures from the Pseudobase library to benchmark the performance of our algorithm. We compared the quality characteristics of the RNA sequences we designed by Enzymer with the results obtained from the state of the art MODENA and antaRNA. Our results show our method succeeds more frequently than MODENA and antaRNA do, and generates sequences that have lower ensemble defect, lower probability defect and higher thermostability. Finally by using Enzymer and by constraining the design to a naturally occurring and highly conserved Hammerhead motif, we designed 8 sequences for a pseudoknotted cis-acting Hammerhead ribozyme. Enzymer is available for download at https://bitbucket.org/casraz/enzymer.
An Adaptive Defect Weighted Sampling Algorithm to Design Pseudoknotted RNA Secondary Structures
Zandi, Kasra; Butler, Gregory; Kharma, Nawwaf
2016-01-01
Computational design of RNA sequences that fold into targeted secondary structures has many applications in biomedicine, nanotechnology and synthetic biology. An RNA molecule is made of different types of secondary structure elements and an important RNA element named pseudoknot plays a key role in stabilizing the functional form of the molecule. However, due to the computational complexities associated with characterizing pseudoknotted RNA structures, most of the existing RNA sequence designer algorithms generally ignore this important structural element and therefore limit their applications. In this paper we present a new algorithm to design RNA sequences for pseudoknotted secondary structures. We use NUPACK as the folding algorithm to compute the equilibrium characteristics of the pseudoknotted RNAs, and describe a new adaptive defect weighted sampling algorithm named Enzymer to design low ensemble defect RNA sequences for targeted secondary structures including pseudoknots. We used a biological data set of 201 pseudoknotted structures from the Pseudobase library to benchmark the performance of our algorithm. We compared the quality characteristics of the RNA sequences we designed by Enzymer with the results obtained from the state of the art MODENA and antaRNA. Our results show our method succeeds more frequently than MODENA and antaRNA do, and generates sequences that have lower ensemble defect, lower probability defect and higher thermostability. Finally by using Enzymer and by constraining the design to a naturally occurring and highly conserved Hammerhead motif, we designed 8 sequences for a pseudoknotted cis-acting Hammerhead ribozyme. Enzymer is available for download at https://bitbucket.org/casraz/enzymer. PMID:27499762
The Mechanization of Design and Manufacturing.
ERIC Educational Resources Information Center
Gunn, Thomas G.
1982-01-01
Describes changes in the design of products and in planning, managing, and coordinating their manufacture. Focuses on discrete-products manufacturing industries, encompassing the fabrication and assembly of automobiles, aircraft, computers and microelectric components of computers, furniture, appliances, foods, clothing, building materials, and…
The Mechanization of Design and Manufacturing.
ERIC Educational Resources Information Center
Gunn, Thomas G.
1982-01-01
Describes changes in the design of products and in planning, managing, and coordinating their manufacture. Focuses on discrete-products manufacturing industries, encompassing the fabrication and assembly of automobiles, aircraft, computers and microelectric components of computers, furniture, appliances, foods, clothing, building materials, and…
A new algorithm to design compact two-hidden-layer artificial neural networks.
Islam, M M; Murase, K
2001-11-01
This paper describes the cascade neural network design algorithm (CNNDA), a new algorithm for designing compact, two-hidden-layer artificial neural networks (ANNs). This algorithm determines an ANN's architecture with connection weights automatically. The design strategy used in the CNNDA was intended to optimize both the generalization ability and the training time of ANNs. In order to improve the generalization ability, the CNDDA uses a combination of constructive and pruning algorithms and bounded fan-ins of the hidden nodes. A new training approach, by which the input weights of a hidden node are temporarily frozen when its output does not change much after a few successive training cycles, was used in the CNNDA for reducing the computational cost and the training time. The CNNDA was tested on several benchmarks including the cancer, diabetes and character-recognition problems in ANNs. The experimental results show that the CNNDA can produce compact ANNs with good generalization ability and short training time in comparison with other algorithms.
NASA Astrophysics Data System (ADS)
Foudray, Angela Marie Klohs
Detecting, quantifying and visualizing biochemical mechanism in a living system without perturbing function is the goal of the instrument and algorithms designed in this thesis. Biochemical mechanisms of cells have long been known to be dependent on the signals they receive from their environment. Studying biological processes of cells in-vitro can vastly distort their function, since you are removing them from their natural chemical signaling environment. Mice have become the biological system of choice for various areas of biomedical research due to their genetic and physiological similarities with humans, the relatively low cost of their care, and their quick breeding cycle. Drug development and efficacy assessment along with disease detection, management, and mechanism research all have benefited from the use of small animal models of human disease. A high resolution, high sensitivity, three-dimensional (3D) positioning positron emission tomography (PET) detector system was designed through device characterization and Monte Carlo simulation. Position-sensitive avalanche photodiodes (PSAPDs) were characterized in various packaging configurations; coupled to various configurations of lutetium oxyorthosilicate (LSO) scintillation crystals. Forty novelly packaged final design devices were constructed and characterized, each providing characteristics superior to commercially available scintillation detectors used in small animal imaging systems: ˜1mm crystal identification, 14-15% of 511 keV energy resolution, and averaging 1.9 to 5.6 ns coincidence time resolution. A closed-cornered box-shaped detector configuration was found to provide optimal photon sensitivity (˜10.5% in the central plane) using dual LSO-PSAPD scintillation detector modules and Monte Carlo simulation. Standard figures of merit were used to determine optimal system acquisition parameters. A realistic model for constituent devices was developed for understanding the signals reported by the
Training the neural networks by electromagnetism-like mechanism based algorithm
NASA Astrophysics Data System (ADS)
Jalab, Hamid A.; Shaker, Khalid
2014-12-01
Recently, medical data mining has become one of the most popular topics in the data mining community. This is due to the societal importance of the field and also the particular computational challenges posed in this domain of data mining. Early researches concentrated on sequential heuristics and later moved to meta-heuristic approaches due to the ability of these approaches to generate better solutions. The aim of this paper is to introduce the basic principles of a new meta-heuristic algorithm called Electromagnetism-like Mechanism (EMag) for neural network training. EMag simulates the electromagnetism theory of physics by considering each data sample to be an electrical charge. For neural network, EMag simulates the attraction-repulsion mechanism of each weight connection as charge partials to move towards the optimum without being trapped into local minimum. The performance of the proposed algorithm is evaluated in 12 of benchmark classification problems, and the computational results show that the proposed algorithm performs better than the standard back propagation algorithm.
Perriñez, Phillip R.; Kennedy, Francis E.; Van Houten, Elijah E. W.; Weaver, John B.; Paulsen, Keith D.
2010-01-01
Magnetic Resonance Poroelastography (MRPE) is introduced as an alternative to single-phase model-based elastographic reconstruction methods. A three-dimensional (3D) finite element poroelastic inversion algorithm was developed to recover the mechanical properties of fluid-saturated tissues. The performance of this algorithm was assessed through a variety of numerical experiments, using synthetic data to probe its stability and sensitivity to the relevant model parameters. Preliminary results suggest the algorithm is robust in the presence of noise and capable of producing accurate assessments of the underlying mechanical properties in simulated phantoms. Further, a 3D time-harmonic motion field was recorded for a poroelastic phantom containing a single cylindrical inclusion and used to assess the feasibility of MRPE image reconstruction from experimental data. The elastograms obtained from the proposed poroelastic algorithm demonstrate significant improvement over linearly elastic MRE images generated using the same data. In addition, MRPE offers the opportunity to estimate the time-harmonic pressure field resulting from tissue excitation, highlighting the potential for its application in the diagnosis and monitoring of disease processes associated with changes in interstitial pressure. PMID:20199912
NASA Astrophysics Data System (ADS)
Hassan, Rania A.
In the design of complex large-scale spacecraft systems that involve a large number of components and subsystems, many specialized state-of-the-art design tools are employed to optimize the performance of various subsystems. However, there is no structured system-level concept-architecting process. Currently, spacecraft design is heavily based on the heritage of the industry. Old spacecraft designs are modified to adapt to new mission requirements, and feasible solutions---rather than optimal ones---are often all that is achieved. During the conceptual phase of the design, the choices available to designers are predominantly discrete variables describing major subsystems' technology options and redundancy levels. The complexity of spacecraft configurations makes the number of the system design variables that need to be traded off in an optimization process prohibitive when manual techniques are used. Such a discrete problem is well suited for solution with a Genetic Algorithm, which is a global search technique that performs optimization-like tasks. This research presents a systems engineering framework that places design requirements at the core of the design activities and transforms the design paradigm for spacecraft systems to a top-down approach rather than the current bottom-up approach. To facilitate decision-making in the early phases of the design process, the population-based search nature of the Genetic Algorithm is exploited to provide computationally inexpensive---compared to the state-of-the-practice---tools for both multi-objective design optimization and design optimization under uncertainty. In terms of computational cost, those tools are nearly on the same order of magnitude as that of standard single-objective deterministic Genetic Algorithm. The use of a multi-objective design approach provides system designers with a clear tradeoff optimization surface that allows them to understand the effect of their decisions on all the design objectives
Genetic algorithms in conceptual design of a light-weight, low-noise, tilt-rotor aircraft
NASA Technical Reports Server (NTRS)
Wells, Valana L.
1996-01-01
This report outlines research accomplishments in the area of using genetic algorithms (GA) for the design and optimization of rotorcraft. It discusses the genetic algorithm as a search and optimization tool, outlines a procedure for using the GA in the conceptual design of helicopters, and applies the GA method to the acoustic design of rotors.
Genetic algorithms in conceptual design of a light-weight, low-noise, tilt-rotor aircraft
NASA Technical Reports Server (NTRS)
Wells, Valana L.
1996-01-01
This report outlines research accomplishments in the area of using genetic algorithms (GA) for the design and optimization of rotorcraft. It discusses the genetic algorithm as a search and optimization tool, outlines a procedure for using the GA in the conceptual design of helicopters, and applies the GA method to the acoustic design of rotors.
Designing berthing mechanisms for international compatibility
NASA Technical Reports Server (NTRS)
Winch, John; Gonzalez-Vallejo, Juan J.
1991-01-01
The paper examines the technological issues regarding common berthing interfaces for the Space Station Freedom and pressurized modules from U.S., European, and Japanese space programs. The development of the common berthing mechanism (CBM) is based on common requirements concerning specifications, launch environments, and the unique requirements of ESA's Man-Tended Free Flyer. The berthing mechanism is composed of an active and a passive half, a remote manipulator system, 4 capture-latch assemblies, 16 structural bolts, and a pressure gage to verify equalization. Extensive graphic and verbal descriptions of each element are presented emphasizing the capture-latch motion and powered-bolt operation. The support systems to complete the interface are listed, and the manufacturing requirements for consistent fabrication are discussed to ensure effective international development.
Designing berthing mechanisms for international compatibility
NASA Technical Reports Server (NTRS)
Winch, John; Gonzalez-Vallejo, Juan J.
1991-01-01
The paper examines the technological issues regarding common berthing interfaces for the Space Station Freedom and pressurized modules from U.S., European, and Japanese space programs. The development of the common berthing mechanism (CBM) is based on common requirements concerning specifications, launch environments, and the unique requirements of ESA's Man-Tended Free Flyer. The berthing mechanism is composed of an active and a passive half, a remote manipulator system, 4 capture-latch assemblies, 16 structural bolts, and a pressure gage to verify equalization. Extensive graphic and verbal descriptions of each element are presented emphasizing the capture-latch motion and powered-bolt operation. The support systems to complete the interface are listed, and the manufacturing requirements for consistent fabrication are discussed to ensure effective international development.
Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm
NASA Astrophysics Data System (ADS)
Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven
2010-05-01
Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.
[In Silico Drug Design Using an Evolutionary Algorithm and Compound Database].
Kawai, Kentaro; Takahashi, Yoshimasa
2016-01-01
Computational drug design plays an important role in the discovery of new drugs. Recently, we proposed an algorithm for designing new drug-like molecules utilizing the structure of a known active molecule. To design molecules, three types of fragments (ring, linker, and side-chain fragments) were defined as building blocks, and a fragment library was prepared from molecules listed in G protein-coupled receptor (GPCR)-SARfari database. An evolutionary algorithm which executes evolutionary operations, such as crossover, mutation, and selection, was implemented to evolve the molecules. As a case study, some GPCRs were selected for computational experiments in which we tried to design ligands from simple seed fragments using the Tanimoto coefficient as a fitness function. The results showed that the algorithm could be used successfully to design new molecules with structural similarity, scaffold variety, and chemical validity. In addition, a docking study revealed that these designed molecules also exhibited shape complementarity with the binding site of the target protein. Therefore, this is expected to become a powerful tool for designing new drug-like molecules in drug discovery projects.
General parameter relations for the Shinnar-Le Roux pulse design algorithm.
Lee, Kuan J
2007-06-01
The magnetization ripple amplitudes from a pulse designed by the Shinnar-Le Roux algorithm are a non-linear function of the Shinnar-Le Roux A and B polynomial ripples. In this paper, the method of Pauly et al. [J. Pauly, P. Le Roux, D. Nishimura, A. Macovski, Parameter relations for the Shinnar-Le Roux selective excitation pulse design algorithm, IEEE Transactions on Medical Imaging 10 (1991) 56-65.] has been extended to derive more general parameter relations. These relations can be used for cases outside the five classes considered by Pauly et al., in particular excitation pulses for flip angles that are not small or 90 degrees. Use of the new relations, together with an iterative procedure to obtain polynomials with the specified ripples from the Parks-McClellan algorithm, are shown to give simulated slice profiles that have the desired ripple amplitudes.
Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Lee, Seungwon; vonAllmen, Paul; Fink, Wolfgang; Petropoulos, Anastassios; Terrile, Richard
2005-01-01
Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.
Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms
NASA Technical Reports Server (NTRS)
Lee, Seungwon; vonAllmen, Paul; Fink, Wolfgang; Petropoulos, Anastassios; Terrile, Richard
2005-01-01
Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.
Hardware-Software Co-design of QRD-RLS Algorithm with Microblaze Soft Core Processor
NASA Astrophysics Data System (ADS)
Lodha, Nupur; Rai, Nivesh; Dubey, Rahul; Venkataraman, Hrishikesh
This paper presents the implementation of QR Decomposition based Recursive Least Square (QRD-RLS) algorithm on Field Programmable Gate Arrays (FPGA). The design is based on hardware-software co-design. The hardware part consists of a custom peripheral that solves the part of the algorithm with higher computational costs and the software part consists of an embedded soft core processor that manages the control functions and rest of the algorithm. The use of Givens Rotation and Systolic Arrays make this architecture suitable for FPGA implementation. Moreover, the speed and flexibility of FPGAs render them viable for such computationally intensive application. The system has been implemented on Xilinx Spartan 3E FPGA with Microblaze soft core processor using Embedded Development Kit (EDK). The paper also presents the implementation results and their analysis.
Design and Analysis of Stimulated Raman Scattering-Aware Algorithm in RWA
NASA Astrophysics Data System (ADS)
Sim, Wai S.; Tan, Saw C.; Yusoff, Zulfadzli
2017-05-01
A stimulated Raman scattering (SRS)-aware routing and wavelength assignment (RWA) scheme, called assign minimum interference and shortest algorithm, is proposed to minimize the effect of SRS in network. The design parameter, the number of interference of routes in the proposed algorithm is investigated to analyze its capabilities of influence the network performance. The various setting of the parameter is tested in 15-nodes Mesh and 14-nodes National Science Foundation networks for analysis in order to provide useful guidelines for designing effective SRS-aware RWA scheme. The ultimate objective is to define the necessary and sufficient rules that must be followed in the proposed algorithm by identifying the necessary RWA parameters in order to minimize the effect of SRS in optical networks. The result shows that the smaller the number of interference of routes, the lower the blocking probability in the mentioned topologies.
NASA Astrophysics Data System (ADS)
Mandl, Christoph E.
1981-08-01
This paper presents a state of the art survey of network models and algorithms that can be used as planning tools in irrigation and wastewater systems. It is shown that the problem of designing or extending such systems basically leads to the same type of mathematical optimization model. The difficulty in solving this model lies mainly in the properties of the objective function. Trying to minimize construction and/or operating costs of a system typically results in a concave cost (objective) function due to economies of scale. A number of ways to attack such models are discussed and compared, including linear programing, integer programing, and specially designed exact and heuristic algorithms. The usefulness of each approach is evaluated in terms of the validity of the model, the computational complexity of the algorithm, the properties of the solution, the availability of software, and the capability for sensitivity analysis.
Mechanical Design Report DARPA BOSS Program
2008-03-21
incorporating them 5. Design and build prototype zoom systems utilizing GRIN optics to demonstrate the technology 6. Fly prototype systems on Unmanned Air...Vehicles (UAVs) to demonstrate GRIN technology and guide development by having a specific application defined. NRL code 6110 made contributions...that challenge existing optical zoom technology , and were expected to highlight the advantages of GRIN lenses. The planned test platform was the
Mechanism Design Principle for Optical-Precision, Deployable Instruments
NASA Technical Reports Server (NTRS)
Lake, Mark S.; Hachkowski, M. Roman
2000-01-01
The present paper is intended to be a guide for the design of 'microdynamically quiet' deployment mechanisms for optical-precision structures, such as deployable telescope mirrors and optical benches. Many of the guidelines included herein come directly from the field of optomechanical engineering, and are neither newly developed guidelines nor are they uniquely applicable to high-precision deployment mechanisms. However, the application of these guidelines to the design of deployment mechanisms is a rather new practice, so efforts are made herein to illustrate the process through the discussion of specific examples. The present paper summarizes a more extensive set of design guidelines for optical-precision mechanisms that are under development.
MECHANICAL DESIGN OF NSLS MINI - GAP UNDULATOR (MGU)
LYNCH,D.; RAKOWSKY,G.
2002-09-05
The mechanical design considerations are discussed with respect to the currently installed X-13 and future X-29 MGU. Comparisons to the previous 2 generations of variable small-gap undulator evolution in the NSLS X-ray ring are made and design improvements noted. The design requirements and mechanical difficulties for holding, positioning and driving the magnetic arrays are explored. Structural, thermal and electrical considerations which influenced the design are then analyzed. The mechanical performance of the MGU currently installed at X-13 is examined and future installations and enhancements are presented.
Design and mechanical properties of insect cuticle.
Vincent, Julian F V; Wegst, Ulrike G K
2004-07-01
Since nearly all adult insects fly, the cuticle has to provide a very efficient and lightweight skeleton. Information is available about the mechanical properties of cuticle-Young's modulus of resilin is about 1 MPa, of soft cuticles about 1 kPa to 50 MPa, of sclerotised cuticles 1-20 GPa; Vicker's Hardness of sclerotised cuticle ranges between 25 and 80 kgf mm(-2); density is 1-1.3 kg m(-3)-and one of its components, chitin nanofibres, the Young's modulus of which is more than 150 GPa. Experiments based on fracture mechanics have not been performed although the layered structure probably provides some toughening. The structural performance of wings and legs has been measured, but our understanding of the importance of buckling is lacking: it can stiffen the structure (by elastic postbuckling in wings, for example) or be a failure mode. We know nothing of fatigue properties (yet, for instance, the insect wing must undergo millions of cycles, flexing or buckling on each cycle). The remarkable mechanical performance and efficiency of cuticle can be analysed and compared with those of other materials using material property charts and material indices. Presented in this paper are four: Young's modulus-density (stiffness per unit weight), specific Young's modulus-specific strength (elastic hinges, elastic energy storage per unit weight), toughness-Young's modulus (fracture resistance under various loading conditions), and hardness (wear resistance). In conjunction with a structural analysis of cuticle these charts help to understand the relevance of microstructure (fibre orientation effects in tendons, joints and sense organs, for example) and shape (including surface structure) of this fibrous composite for a given function. With modern techniques for analysis of structure and material, and emphasis on nanocomposites and self-assembly, insect cuticle should be the archetype for composites at all levels of scale.
The Impact of Critical Thinking and Logico-Mathematical Intelligence on Algorithmic Design Skills
ERIC Educational Resources Information Center
Korkmaz, Ozgen
2012-01-01
The present study aims to reveal the impact of students' critical thinking and logico-mathematical intelligence levels of students on their algorithm design skills. This research was a descriptive study and carried out by survey methods. The sample consisted of 45 first-year educational faculty undergraduate students. The data was collected by…
Designing a binary Fourier-phase-only correlation filter using a simulated annealing algorithm
NASA Astrophysics Data System (ADS)
Nomura, Takanori; Nagase, Takamitsu; Itoh, Kazuyoshi; Ichioka, Yoshiki
1990-11-01
A method of designing a multiple-object recognition filter using a simulated annealing algorithm is presented. This filter has only binary phase information and is correlated with a binary Fourier-phase component of a test object. The filter is used in an incoherent-optical/digital-electric hybrid system. Computer simulations confirm the superior performance of this filter.
Optimal high speed CMOS inverter design using craziness based Particle Swarm Optimization Algorithm
NASA Astrophysics Data System (ADS)
De, Bishnu P.; Kar, Rajib; Mandal, Durbadal; Ghoshal, Sakti P.
2015-07-01
The inverter is the most fundamental logic gate that performs a Boolean operation on a single input variable. In this paper, an optimal design of CMOS inverter using an improved version of particle swarm optimization technique called Craziness based Particle Swarm Optimization (CRPSO) is proposed. CRPSO is very simple in concept, easy to implement and computationally efficient algorithm with two main advantages: it has fast, nearglobal convergence, and it uses nearly robust control parameters. The performance of PSO depends on its control parameters and may be influenced by premature convergence and stagnation problems. To overcome these problems the PSO algorithm has been modiffed to CRPSO in this paper and is used for CMOS inverter design. In birds' flocking or ffsh schooling, a bird or a ffsh often changes direction suddenly. In the proposed technique, the sudden change of velocity is modelled by a direction reversal factor associated with the previous velocity and a "craziness" velocity factor associated with another direction reversal factor. The second condition is introduced depending on a predeffned craziness probability to maintain the diversity of particles. The performance of CRPSO is compared with real code.gnetic algorithm (RGA), and conventional PSO reported in the recent literature. CRPSO based design results are also compared with the PSPICE based results. The simulation results show that the CRPSO is superior to the other algorithms for the examples considered and can be efficiently used for the CMOS inverter design.
The Impact of Critical Thinking and Logico-Mathematical Intelligence on Algorithmic Design Skills
ERIC Educational Resources Information Center
Korkmaz, Ozgen
2012-01-01
The present study aims to reveal the impact of students' critical thinking and logico-mathematical intelligence levels of students on their algorithm design skills. This research was a descriptive study and carried out by survey methods. The sample consisted of 45 first-year educational faculty undergraduate students. The data was collected by…
Kim, Hwi; Yang, Byungchoon; Lee, Byoungho
2004-12-01
There is a trade-off between uniformity and diffraction efficiency in the design of diffractive optical elements. It is caused by the inherent ill-posedness of the design problem itself. For the optimal design, the optimum trade-off needs to be obtained. The trade-off between uniformity and diffraction efficiency in the design of diffractive optical elements is theoretically investigated based on the Tikhonov regularization theory. A novel scheme of an iterative Fourier transform algorithm with regularization to obtain the optimum trade-off is proposed.
Multidisciplinary Design, Analysis, and Optimization Tool Development using a Genetic Algorithm
NASA Technical Reports Server (NTRS)
Pak, Chan-gi; Li, Wesley
2008-01-01
Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space A dministration Dryden Flight Research Center to automate analysis and design process by leveraging existing tools such as NASTRAN, ZAERO a nd CFD codes to enable true multidisciplinary optimization in the pr eliminary design stage of subsonic, transonic, supersonic, and hypers onic aircraft. This is a promising technology, but faces many challe nges in large-scale, real-world application. This paper describes cur rent approaches, recent results, and challenges for MDAO as demonstr ated by our experience with the Ikhana fire pod design.
Application of an evolutionary algorithm in the optimal design of micro-sensor.
Lu, Qibing; Wang, Pan; Guo, Sihai; Sheng, Buyun; Liu, Xingxing; Fan, Zhun
2015-01-01
This paper introduces an automatic bond graph design method based on genetic programming for the evolutionary design of micro-resonator. First, the system-level behavioral model is discussed, which based on genetic programming and bond graph. Then, the geometry parameters of components are automatically optimized, by using the genetic algorithm with constraints. To illustrate this approach, a typical device micro-resonator is designed as an example in biomedicine. This paper provides a new idea for the automatic optimization design of biomedical sensors by evolutionary calculation.
Design of binary diffractive microlenses with subwavelength structures using the genetic algorithm.
Shirakawa, Tatsuya; Ishikawa, Kenichi L; Suzuki, Shuichi; Yamada, Yasufumi; Takahashi, Hiroyuki
2010-04-12
We present a method to design binary diffractive microlenses with subwavelength structures, based on the finite-difference time-domain method and the genetic algorithm, also accounting for limitations on feature size and aspect ratio imposed by fabrication. The focusing efficiency of the microlens designed by this method is close to that of the convex lens and much higher than that of the binary Fresnel lens designed by a previous method. Although the optimized structure appears to be a binary Fresnel lens qualitatively, it is hard to quantitatively derive directly from the convex Fresnel lens. The design of a microlens with reduced chromatic aberration is also presented.
NASA Technical Reports Server (NTRS)
Collins, Emmanuel G., Jr.; Richter, Stephen
1990-01-01
One well known deficiency of LQG compensators is that they do not guarantee any measure of robustness. This deficiency is especially highlighted when considering control design for complex systems such as flexible structures. There has thus been a need to generalize LQG theory to incorporate robustness constraints. Here we describe the maximum entropy approach to robust control design for flexible structures, a generalization of LQG theory, pioneered by Hyland, which has proved useful in practice. The design equations consist of a set of coupled Riccati and Lyapunov equations. A homotopy algorithm that is used to solve these design equations is presented.
Cement design based on cement mechanical response
Thiercelin, M.J.; Dargaud, B.; Baret, J.F.; Rodriquez, W.J.
1998-12-01
The disappearance of cement bond log response as a result of variations of downhole conditions has been observed in numerous wells. This observation has led to concern about the loss of proper zonal isolation. Stresses induced in the cement, through deformation of the cemented casing resulting from the variation of downhole conditions, are the cause of this damage. The authors present an analysis of the mechanical response of set cement in a cased wellbore to quantify this damage and determine the key controlling parameters. The results show that the thermo-elastic properties of the casing, cement, and formation play a significant role. The type of failure, either cement debonding or cement cracking, is a function of the nature of the downhole condition variations. This analysis allows one to propose appropriate cement mechanical properties to avoid cement failure and debonding. The authors show that the use of high compressive strength cement is not always the best solution and, in some cases, flexible cements are preferred.
Data Sharing of Mechanical Design Formulas Using Semantic Web Technology
NASA Astrophysics Data System (ADS)
Zhou, Jun; Watanuki, Keiichi
Speed and efficiency are necessary in the field of mechanical design. CAD/CAM/CAE technologies have advanced and attention has also been paid to increasing the efficiency of data sharing and agent processes in the web environment. In this paper, Semantic Web technology is used to enable the sharing of metadata. The metadata consists of design documents and design formulas, with additional semantic information inserted. Mathematical information is expressed by adding metadata into conventional mechanical design formulas using a Resource Description Framework (RDF). The design formulas are later written in MathML (Mathematical Markup Language) for the sake of data sharing. In this way, data sharing and advanced searching is made easy, because the relevant information is made machine readable in the web environment. The calculation of design formulas is made possible using a mathematical processing system, thus increasing the efficiency of mechanical design.
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design.
Juang, Chia-Feng
2004-04-01
An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning algorithm is proposed in this paper. This new evolutionary learning algorithm is based on a hybrid of genetic algorithm (GA) and particle swarm optimization (PSO), and is thus called HGAPSO. In HGAPSO, individuals in a new generation are created, not only by crossover and mutation operation as in GA, but also by PSO. The concept of elite strategy is adopted in HGAPSO, where the upper-half of the best-performing individuals in a population are regarded as elites. However, instead of being reproduced directly to the next generation, these elites are first enhanced. The group constituted by the elites is regarded as a swarm, and each elite corresponds to a particle within it. In this regard, the elites are enhanced by PSO, an operation which mimics the maturing phenomenon in nature. These enhanced elites constitute half of the population in the new generation, whereas the other half is generated by performing crossover and mutation operation on these enhanced elites. HGAPSO is applied to recurrent neural/fuzzy network design as follows. For recurrent neural network, a fully connected recurrent neural network is designed and applied to a temporal sequence production problem. For recurrent fuzzy network design, a Takagi-Sugeno-Kang-type recurrent fuzzy network is designed and applied to dynamic plant control. The performance of HGAPSO is compared to both GA and PSO in these recurrent networks design problems, demonstrating its superiority.
Integrating Thermal Tools Into the Mechanical Design Process
NASA Technical Reports Server (NTRS)
Tsuyuki, Glenn T.; Siebes, Georg; Novak, Keith S.; Kinsella, Gary M.
1999-01-01
The intent of mechanical design is to deliver a hardware product that meets or exceeds customer expectations, while reducing cycle time and cost. To this end, an integrated mechanical design process enables the idea of parallel development (concurrent engineering). This represents a shift from the traditional mechanical design process. With such a concurrent process, there are significant issues that have to be identified and addressed before re-engineering the mechanical design process to facilitate concurrent engineering. These issues also assist in the integration and re-engineering of the thermal design sub-process since it resides within the entire mechanical design process. With these issues in mind, a thermal design sub-process can be re-defined in a manner that has a higher probability of acceptance, thus enabling an integrated mechanical design process. However, the actual implementation is not always problem-free. Experience in applying the thermal design sub-process to actual situations provides the evidence for improvement, but more importantly, for judging the viability and feasibility of the sub-process.
Integrating Thermal Tools Into the Mechanical Design Process
NASA Technical Reports Server (NTRS)
Tsuyuki, Glenn T.; Siebes, Georg; Novak, Keith S.; Kinsella, Gary M.
1999-01-01
The intent of mechanical design is to deliver a hardware product that meets or exceeds customer expectations, while reducing cycle time and cost. To this end, an integrated mechanical design process enables the idea of parallel development (concurrent engineering). This represents a shift from the traditional mechanical design process. With such a concurrent process, there are significant issues that have to be identified and addressed before re-engineering the mechanical design process to facilitate concurrent engineering. These issues also assist in the integration and re-engineering of the thermal design sub-process since it resides within the entire mechanical design process. With these issues in mind, a thermal design sub-process can be re-defined in a manner that has a higher probability of acceptance, thus enabling an integrated mechanical design process. However, the actual implementation is not always problem-free. Experience in applying the thermal design sub-process to actual situations provides the evidence for improvement, but more importantly, for judging the viability and feasibility of the sub-process.
Mechanical design of submarine power cables for floating platforms
Bisplinghoff, R. L.; Libby, D. O.; Costantino, R. W.
1980-01-01
The process of mechanical design of submarine power cables employed by the Simplex Wire and Cable Company is described. The process commences with design criteria and proceeds through preliminary design, load and stress analyses and culminates in extreme value reliability and lifetime predictions. The analytical methods employed are emphasized and some representative numerical results are presented.
Preliminary Opto-Mechanical Design for the X2000 Transceiver
NASA Technical Reports Server (NTRS)
Hemmati, H.; Page, N. A.
2000-01-01
Preliminary optical design and mechanical conceptual design for a 30 cm aperture transceiver are described. A common aperture is used for both transmit and receive. Special attention was given to off-axis and scattered light rejection and isolation of the receive channel from the transmit channel. Requirements, details of the design and preliminary performance analysis of the transceiver are provided.
Application of hybrid evolutionary algorithms to low exhaust emission diesel engine design
NASA Astrophysics Data System (ADS)
Jeong, S.; Obayashi, S.; Minemura, Y.
2008-01-01
A hybrid evolutionary algorithm, consisting of a genetic algorithm (GA) and particle swarm optimization (PSO), is proposed. Generally, GAs maintain diverse solutions of good quality in multi-objective problems, while PSO shows fast convergence to the optimum solution. By coupling these algorithms, GA will compensate for the low diversity of PSO, while PSO will compensate for the high computational costs of GA. The hybrid algorithm was validated using standard test functions. The results showed that the hybrid algorithm has better performance than either a pure GA or pure PSO. The method was applied to an engineering design problem—the geometry of diesel engine combustion chamber reducing exhaust emissions such as NOx, soot and CO was optimized. The results demonstrated the usefulness of the present method to this engineering design problem. To identify the relation between exhaust emissions and combustion chamber geometry, data mining was performed with a self-organising map (SOM). The results indicate that the volume near the lower central part of the combustion chamber has a large effect on exhaust emissions and the optimum chamber geometry will vary depending on fuel injection angle.
2014-01-01
Background To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. Results This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Conclusions Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel
Lee, Wei-Po; Hsiao, Yu-Ting; Hwang, Wei-Che
2014-01-16
To improve the tedious task of reconstructing gene networks through testing experimentally the possible interactions between genes, it becomes a trend to adopt the automated reverse engineering procedure instead. Some evolutionary algorithms have been suggested for deriving network parameters. However, to infer large networks by the evolutionary algorithm, it is necessary to address two important issues: premature convergence and high computational cost. To tackle the former problem and to enhance the performance of traditional evolutionary algorithms, it is advisable to use parallel model evolutionary algorithms. To overcome the latter and to speed up the computation, it is advocated to adopt the mechanism of cloud computing as a promising solution: most popular is the method of MapReduce programming model, a fault-tolerant framework to implement parallel algorithms for inferring large gene networks. This work presents a practical framework to infer large gene networks, by developing and parallelizing a hybrid GA-PSO optimization method. Our parallel method is extended to work with the Hadoop MapReduce programming model and is executed in different cloud computing environments. To evaluate the proposed approach, we use a well-known open-source software GeneNetWeaver to create several yeast S. cerevisiae sub-networks and use them to produce gene profiles. Experiments have been conducted and the results have been analyzed. They show that our parallel approach can be successfully used to infer networks with desired behaviors and the computation time can be largely reduced. Parallel population-based algorithms can effectively determine network parameters and they perform better than the widely-used sequential algorithms in gene network inference. These parallel algorithms can be distributed to the cloud computing environment to speed up the computation. By coupling the parallel model population-based optimization method and the parallel computational framework, high
Mechanical Design of the LSST Camera
Nordby, Martin; Bowden, Gordon; Foss, Mike; Guiffre, Gary; Ku, John; Schindler, Rafe; /SLAC
2008-06-13
The LSST camera is a tightly packaged, hermetically-sealed system that is cantilevered into the main beam of the LSST telescope. It is comprised of three refractive lenses, on-board storage for five large filters, a high-precision shutter, and a cryostat that houses the 3.2 giga-pixel CCD focal plane along with its support electronics. The physically large optics and focal plane demand large structural elements to support them, but the overall size of the camera and its components must be minimized to reduce impact on the image stability. Also, focal plane and optics motions must be minimized to reduce systematic errors in image reconstruction. Design and analysis for the camera body and cryostat will be detailed.
Novel meta-surface design synthesis via nature-inspired optimization algorithms
NASA Astrophysics Data System (ADS)
Bayraktar, Zikri
Heuristic numerical optimization algorithms have been gaining interest over the years as the computational power of the digital computers increases at an unprecedented level every year. While mature techniques such as the Genetic Algorithm increase their application areas, researchers also try to come up with new algorithms by simply observing the highly tuned processes provided by the nature. In this dissertation, the well-known Genetic Algorithm (GA) will be utilized to tackle various novel electromagnetic optimization problems, along with parallel implementation of the Clonal Selection Algorithm (CLONALG) and newly introduced the Wind Driven Optimization (WDO) technique. The utility of the CLONALG parallelization and the efficiency of the WDO will be illustrated by applying them to multi-dimensional and multi-modal electromagnetics problems such as antenna design and metamaterial surface synthesis. One of the metamaterial application areas is the design synthesis of 90 degrees rotationally symmetric ultra-small unit cell artificial magnetic conducting (AMC) surfaces. AMCs are composite metallo-dielectric structures designed to behave as perfect magnetic conductors (PMC) over a certain frequency range, those exhibit a reflection coefficient magnitude of unity with an phase angle of zero degrees at the center of the band. The proposed designs consist of ultra small sized frequency selective surface (FSS) unit cells that are tightly packed and highly intertwined, yet achieve remarkable AMC band performance and field of view when compared to current state-of-the-art AMCs. In addition, planar double-sided AMC (DSAMC) structures are introduced and optimized as AMC ground planes for low profile antennas in composite platforms and separator slabs for vertical antenna applications. The proposed designs do not possess complete metallic ground planes, which makes them ideal for composite and multi-antenna systems. The versatility of the DSAMC slabs is also illustrated
Design and Implementation of the Automated Rendezvous Targeting Algorithms for Orion
NASA Technical Reports Server (NTRS)
DSouza, Christopher; Weeks, Michael
2010-01-01
The Orion vehicle will be designed to perform several rendezvous missions: rendezvous with the ISS in Low Earth Orbit (LEO), rendezvous with the EDS/Altair in LEO, a contingency rendezvous with the ascent stage of the Altair in Low Lunar Orbit (LLO) and a contingency rendezvous in LLO with the ascent and descent stage in the case of an aborted lunar landing. Therefore, it is not difficult to realize that each of these scenarios imposes different operational, timing, and performance constraints on the GNC system. To this end, a suite of on-board guidance and targeting algorithms have been designed to meet the requirement to perform the rendezvous independent of communications with the ground. This capability is particularly relevant for the lunar missions, some of which may occur on the far side of the moon. This paper will describe these algorithms which are designed to be structured and arranged in such a way so as to be flexible and able to safely perform a wide variety of rendezvous trajectories. The goal of the algorithms is not to merely fly one specific type of canned rendezvous profile. Conversely, it was designed from the start to be general enough such that any type of trajectory profile can be flown.(i.e. a coelliptic profile, a stable orbit rendezvous profile, and a expedited LLO rendezvous profile, etc) all using the same rendezvous suite of algorithms. Each of these profiles makes use of maneuver types which have been designed with dual goals of robustness and performance. They are designed to converge quickly under dispersed conditions and they are designed to perform many of the functions performed on the ground today. The targeting algorithms consist of a phasing maneuver (NC), an altitude adjust maneuver (NH), and plane change maneuver (NPC), a coelliptic maneuver (NSR), a Lambert targeted maneuver, and several multiple-burn targeted maneuvers which combine one of more of these algorithms. The derivation and implementation of each of these
Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design Processes
NASA Technical Reports Server (NTRS)
Rogers, James L.; McCulley, Collin M.; Bloebaum, Christina L.
1996-01-01
The design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.
DeMAID/GA USER'S GUIDE Design Manager's Aid for Intelligent Decomposition with a Genetic Algorithm
NASA Technical Reports Server (NTRS)
Rogers, James L.
1996-01-01
Many companies are looking for new tools and techniques to aid a design manager in making decisions that can reduce the time and cost of a design cycle. One tool that is available to aid in this decision making process is the Design Manager's Aid for Intelligent Decomposition (DeMAID). Since the initial release of DEMAID in 1989, numerous enhancements have been added to aid the design manager in saving both cost and time in a design cycle. The key enhancement is a genetic algorithm (GA) and the enhanced version is called DeMAID/GA. The GA orders the sequence of design processes to minimize the cost and time to converge to a solution. These enhancements as well as the existing features of the original version of DEMAID are described. Two sample problems are used to show how these enhancements can be applied to improve the design cycle. This report serves as a user's guide for DeMAID/GA.
Mechanical Designs for Inorganic Stretchable Circuits in Soft Electronics
Wang, Shuodao; Huang, Yonggang; Rogers, John A.
2016-01-01
Mechanical concepts and designs in inorganic circuits for different levels of stretchability are reviewed in this paper, through discussions of the underlying mechanics and material theories, fabrication procedures for the constituent microscale/nanoscale devices, and experimental characterization. All of the designs reported here adopt heterogeneous structures of rigid and brittle inorganic materials on soft and elastic elastomeric substrates, with mechanical design layouts that isolate large deformations to the elastomer, thereby avoiding potentially destructive plastic strains in the brittle materials. The overall stiffnesses of the electronics, their stretchability, and curvilinear shapes can be designed to match the mechanical properties of biological tissues. The result is a class of soft stretchable electronic systems that are compatible with traditional high-performance inorganic semiconductor technologies. These systems afford promising options for applications in portable biomedical and health-monitoring devices. Mechanics theories and modeling play a key role in understanding the underlining physics and optimization of these systems. PMID:27668126
An algorithm for control system design via parameter optimization. M.S. Thesis
NASA Technical Reports Server (NTRS)
Sinha, P. K.
1972-01-01
An algorithm for design via parameter optimization has been developed for linear-time-invariant control systems based on the model reference adaptive control concept. A cost functional is defined to evaluate the system response relative to nominal, which involves in general the error between the system and nominal response, its derivatives and the control signals. A program for the practical implementation of this algorithm has been developed, with the computational scheme for the evaluation of the performance index based on Lyapunov's theorem for stability of linear invariant systems.
Sizing of complex structure by the integration of several different optimal design algorithms
NASA Technical Reports Server (NTRS)
Sobieszczanski, J.
1974-01-01
Practical design of large-scale structures can be accomplished with the aid of the digital computer by bringing together in one computer program algorithms of nonlinear mathematical programing and optimality criteria with weight-strength and other so-called engineering methods. Applications of this approach to aviation structures are discussed with a detailed description of how the total problem of structural sizing can be broken down into subproblems for best utilization of each algorithm and for efficient organization of the program into iterative loops. Typical results are examined for a number of examples.
A firefly algorithm for solving competitive location-design problem: a case study
NASA Astrophysics Data System (ADS)
Sadjadi, Seyed Jafar; Ashtiani, Milad Gorji; Ramezanian, Reza; Makui, Ahmad
2016-07-01
This paper aims at determining the optimal number of new facilities besides specifying both the optimal location and design level of them under the budget constraint in a competitive environment by a novel hybrid continuous and discrete firefly algorithm. A real-world application of locating new chain stores in the city of Tehran, Iran, is used and the results are analyzed. In addition, several examples have been solved to evaluate the efficiency of the proposed model and algorithm. The results demonstrate that the performed method provides good-quality results for the test problems.
Sizing of complex structure by the integration of several different optimal design algorithms
NASA Technical Reports Server (NTRS)
Sobieszczanski, J.
1974-01-01
Practical design of large-scale structures can be accomplished with the aid of the digital computer by bringing together in one computer program algorithms of nonlinear mathematical programing and optimality criteria with weight-strength and other so-called engineering methods. Applications of this approach to aviation structures are discussed with a detailed description of how the total problem of structural sizing can be broken down into subproblems for best utilization of each algorithm and for efficient organization of the program into iterative loops. Typical results are examined for a number of examples.
Combining genetic algorithms and Lyapunov-based adaptation for online design of fuzzy controllers.
Giordano, Vincenzo; Naso, David; Turchiano, Biagio
2006-10-01
This paper proposes a hybrid approach for the design of adaptive fuzzy controllers (FCs) in which two learning algorithms with different characteristics are merged together to obtain an improved method. The approach combines a genetic algorithm (GA), devised to optimize all the configuration parameters of the FC, including the number of membership functions and rules, and a Lyapunov-based adaptation law performing a local tuning of the output singletons of the controller, and guaranteeing the stability of each new controller investigated by the GA. The effectiveness of the proposed method is confirmed using both numerical simulations on a known case study and experiments on a nonlinear hardware benchmark.
Homotopy Algorithm for Fixed Order Mixed H2/H(infinity) Design
NASA Technical Reports Server (NTRS)
Whorton, Mark; Buschek, Harald; Calise, Anthony J.
1996-01-01
Recent developments in the field of robust multivariable control have merged the theories of H-infinity and H-2 control. This mixed H-2/H-infinity compensator formulation allows design for nominal performance by H-2 norm minimization while guaranteeing robust stability to unstructured uncertainties by constraining the H-infinity norm. A key difficulty associated with mixed H-2/H-infinity compensation is compensator synthesis. A homotopy algorithm is presented for synthesis of fixed order mixed H-2/H-infinity compensators. Numerical results are presented for a four disk flexible structure to evaluate the efficiency of the algorithm.
Agricultural robot designed for seeding mechanism
NASA Astrophysics Data System (ADS)
Sunitha, K. A., Dr.; Suraj, G. S. G. S.; Sowrya, CH P. N.; Atchyut Sriram, G.; Shreyas, D.; Srinivas, T.
2017-05-01
In the field of agriculture, plantation begins with ploughing the land and sowing seeds. The old traditional method plough attached to an OX and tractors needs human involvement to carry the process. The driving force behind this work is to reduce the human interference in the field of agriculture and to make it cost effective. In this work, apart of the land is taken into consideration and the robot introduced localizes the path and can navigate itself without human action. For ploughing, this robot is provided with tentacles attached with saw blades. The sowing mechanism initiates with long toothed gears actuated with motors. The complete body is divided into two parts the tail part acts as a container for seeds. The successor holds on all the electronics used for automating and actuation. The locomotion is provided with wheels covered under conveyor belts. Gears at the back of the robot rotate in equal speed with respect to each other with the saw blades. For each rotation every tooth on gear will take seeds and will drop them on field. Camera at the front end tracks the path for every fixed distance and at the minimum distance it takes the path pre-programmed.
Mechanical design of the solar telescope GREGOR
NASA Astrophysics Data System (ADS)
Volkmer, R.; Eisenträger, P.; Emde, P.; Fischer, A.; von der Lühe, O.; Nicklas, H.; Soltau, D.; Schmidt, W.; Weis, U.
2012-11-01
The mechanical structure of the GREGOR telescope was installed at the Observatorio del Teide, Tenerife, in 2004. New concepts for mounting and cooling of the 1.5-meter primary mirror were introduced. GREGOR is an open telescope, therefore the dome is completely open during observations to allow for air flushing through the open, but stiff telescope structure. Backside cooling system of the primary mirror keeps the mirror surface close to ambient temperature to prevent mirror seeing. The large collecting area of the primary mirror results in high energy density at the field stop at the prime focus of the primary which needs to be removed. The optical elements are supported by precision alignment systems and should provide a stable solar image at the optical lab. The coudé train can be evacuated and serves as a natural barrier between the outer environmental conditions and the air-conditioned optical laboratory with its sensitive scientific instrumentation. The telescope was successfully commissioned and will start its nominal operation during 2013.
New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.
Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng
2016-05-16
The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.
Evolving spiking neural networks: a novel growth algorithm exhibits unintelligent design
NASA Astrophysics Data System (ADS)
Schaffer, J. David
2015-06-01
Spiking neural networks (SNNs) have drawn considerable excitement because of their computational properties, believed to be superior to conventional von Neumann machines, and sharing properties with living brains. Yet progress building these systems has been limited because we lack a design methodology. We present a gene-driven network growth algorithm that enables a genetic algorithm (evolutionary computation) to generate and test SNNs. The genome for this algorithm grows O(n) where n is the number of neurons; n is also evolved. The genome not only specifies the network topology, but all its parameters as well. Experiments show the algorithm producing SNNs that effectively produce a robust spike bursting behavior given tonic inputs, an application suitable for central pattern generators. Even though evolution did not include perturbations of the input spike trains, the evolved networks showed remarkable robustness to such perturbations. In addition, the output spike patterns retain evidence of the specific perturbation of the inputs, a feature that could be exploited by network additions that could use this information for refined decision making if required. On a second task, a sequence detector, a discriminating design was found that might be considered an example of "unintelligent design"; extra non-functional neurons were included that, while inefficient, did not hamper its proper functioning.
Design of multiple sequence alignment algorithms on parallel, distributed memory supercomputers.
Church, Philip C; Goscinski, Andrzej; Holt, Kathryn; Inouye, Michael; Ghoting, Amol; Makarychev, Konstantin; Reumann, Matthias
2011-01-01
The challenge of comparing two or more genomes that have undergone recombination and substantial amounts of segmental loss and gain has recently been addressed for small numbers of genomes. However, datasets of hundreds of genomes are now common and their sizes will only increase in the future. Multiple sequence alignment of hundreds of genomes remains an intractable problem due to quadratic increases in compute time and memory footprint. To date, most alignment algorithms are designed for commodity clusters without parallelism. Hence, we propose the design of a multiple sequence alignment algorithm on massively parallel, distributed memory supercomputers to enable research into comparative genomics on large data sets. Following the methodology of the sequential progressiveMauve algorithm, we design data structures including sequences and sorted k-mer lists on the IBM Blue Gene/P supercomputer (BG/P). Preliminary results show that we can reduce the memory footprint so that we can potentially align over 250 bacterial genomes on a single BG/P compute node. We verify our results on a dataset of E.coli, Shigella and S.pneumoniae genomes. Our implementation returns results matching those of the original algorithm but in 1/2 the time and with 1/4 the memory footprint for scaffold building. In this study, we have laid the basis for multiple sequence alignment of large-scale datasets on a massively parallel, distributed memory supercomputer, thus enabling comparison of hundreds instead of a few genome sequences within reasonable time.
Adjoint-Based Algorithms for Adaptation and Design Optimizations on Unstructured Grids
NASA Technical Reports Server (NTRS)
Nielsen, Eric J.
2006-01-01
Schemes based on discrete adjoint algorithms present several exciting opportunities for significantly advancing the current state of the art in computational fluid dynamics. Such methods provide an extremely efficient means for obtaining discretely consistent sensitivity information for hundreds of design variables, opening the door to rigorous, automated design optimization of complex aerospace configuration using the Navier-Stokes equation. Moreover, the discrete adjoint formulation provides a mathematically rigorous foundation for mesh adaptation and systematic reduction of spatial discretization error. Error estimates are also an inherent by-product of an adjoint-based approach, valuable information that is virtually non-existent in today's large-scale CFD simulations. An overview of the adjoint-based algorithm work at NASA Langley Research Center is presented, with examples demonstrating the potential impact on complex computational problems related to design optimization as well as mesh adaptation.
Design and Implementation of IIR Algorithms for Control of Longitudinal Coupled-Bunch Instabilities
Teytelman, Dmitry
2000-05-16
The recent installation of third-harmonic RF cavities at the Advanced Light Source has raised instability growth rates, and also caused tune shifts (coherent and incoherent) of more than an octave over the required range of beam currents and energies. The larger growth rates and tune shifts have rendered control by the original bandpass FIR feedback algorithms unreliable. In this paper the authors describe an implementation of an IIR feedback algorithm with more exible response tailoring. A cascade of up to 6 second-order IIR sections (12 poles and 12 zeros) was implemented in the DSPs of the longitudinal feedback system. Filter design has been formulated as an optimization problem and solved using constrained optimization methods. These IIR filters provided 2.4 times the control bandwidth as compared to the original FIR designs. Here the authors demonstrate the performance of the designed filters using transient diagnostic measurements from ALS and DAPNE.
A general design algorithm for low optical loss adiabatic connections in waveguides.
Chen, Tong; Lee, Hansuek; Li, Jiang; Vahala, Kerry J
2012-09-24
Single-mode waveguide designs frequently support higher order transverse modes, usually as a consequence of process limitations such as lithography. In these systems, it is important to minimize coupling to higher-order modes so that the system nonetheless behaves single mode. We propose a variational approach to design adiabatic waveguide connections with minimal intermodal coupling. An application of this algorithm in designing the "S-bend" of a whispering-gallery spiral waveguide is demonstrated with approximately 0.05 dB insertion loss. Compared to other approaches, our algorithm requires less fabrication resolution and is able to minimize the transition loss over a broadband spectrum. The method can be applied to a wide range of turns and connections and has the advantage of handling connections with arbitrary boundary conditions.
Design of adaptive fuzzy logic controller based on linguistic-hedge concepts and genetic algorithms.
Liu, B D; Chen, C Y; Tsao, J Y
2001-01-01
In this paper, we propose a novel fuzzy logic controller, called linguistic hedge fuzzy logic controller, to simplify the membership function constructions and the rule developments. The design methodology of linguistic hedge fuzzy logic controller is a hybrid model based on the concepts of the linguistic hedges and the genetic algorithms. The linguistic hedge operators are used to adjust the shape of the system membership functions dynamically, and ran speed up the control result to fit the system demand. The genetic algorithms are adopted to search the optimal linguistic hedge combination in the linguistic hedge module, According to the proposed methodology, the linguistic hedge fuzzy logic controller has the following advantages: 1) it needs only the simple-shape membership functions rather than the carefully designed ones for characterizing the related variables; 2) it is sufficient to adopt a fewer number of rules for inference; 3) the rules are developed intuitionally without heavily depending on the endeavor of experts; 4) the linguistic hedge module associated with the genetic algorithm enables it to be adaptive; 5) it performs better than the conventional fuzzy logic controllers do; and 6) it can be realized with low design complexity and small hardware overhead. Furthermore, the proposed approach has been applied to design three well-known nonlinear systems. The simulation and experimental results demonstrate the effectiveness of this design.
Designing Adiabatic Radio Frequency Pulses Using the Shinnar–Le Roux Algorithm
Balchandani, Priti; Pauly, John; Spielman, Daniel
2010-01-01
Adiabatic pulses are a special class of radio frequency (RF) pulses that may be used to achieve uniform flip angles in the presence of a nonuniform B1 field. In this work, we present a new, systematic method for designing high-bandwidth (BW), low-peak-amplitude adiabatic RF pulses that utilizes the Shinnar–Le Roux (SLR) algorithm for pulse design. Currently, the SLR algorithm is extensively employed to design nonadiabatic pulses for use in magnetic resonance imaging and spectroscopy. We have adapted the SLR algorithm to create RF pulses that also satisfy the adiabatic condition. By overlaying sufficient quadratic phase across the spectral profile before the inverse SLR transform, we generate RF pulses that exhibit the required spectral characteristics and adiabatic behavior. Application of quadratic phase also distributes the RF energy more uniformly, making it possible to obtain the same spectral BW with lower RF peak amplitude. The method enables the pulse designer to specify spectral profile parameters and the degree of quadratic phase before pulse generation. Simulations and phantom experiments demonstrate that RF pulses designed using this new method behave adiabatically. PMID:20806378
Computer graphics in small-scale mechanism design
Bailey, M.J.
1981-01-01
At a time when many small-scale mechanisms are being functionally replaced by logic circuits, some applications, because of strength and durability requirements, continue to require mechanical systems. Because of this, Sandia National Laboratories is moving to upgrade the capabilities and productivity of its mechanism design staff. The key to better design efficiency of these systems is to identify and alleviate real or potential problems prior to construction of any working test model. Productivity is gained when design iterations are performed on a numerical, instead of a phycial, model. The trick is to allow the engineer to interface to the numerical world in a manner that is accurate and natural.
NASA Astrophysics Data System (ADS)
Son, Min; Ko, Sangho; Koo, Jaye
2014-06-01
A genetic algorithm was used to develop optimal design methods for the regenerative cooled combustor and fuel-rich gas generator of a liquid rocket engine. For the combustor design, a chemical equilibrium analysis was applied, and the profile was calculated using Rao's method. One-dimensional heat transfer was assumed along the profile, and cooling channels were designed. For the gas-generator design, non-equilibrium properties were derived from a counterflow analysis, and a vaporization model for the fuel droplet was adopted to calculate residence time. Finally, a genetic algorithm was adopted to optimize the designs. The combustor and gas generator were optimally designed for 30-tonf, 75-tonf, and 150-tonf engines. The optimized combustors demonstrated superior design characteristics when compared with previous non-optimized results. Wall temperatures at the nozzle throat were optimized to satisfy the requirement of 800 K, and specific impulses were maximized. In addition, the target turbine power and a burned-gas temperature of 1000 K were obtained from the optimized gas-generator design.
NASA Astrophysics Data System (ADS)
Le-Duc, Thang; Ho-Huu, Vinh; Nguyen-Thoi, Trung; Nguyen-Quoc, Hung
2016-12-01
In recent years, various types of magnetorheological brakes (MRBs) have been proposed and optimized by different optimization algorithms that are integrated in commercial software such as ANSYS and Comsol Multiphysics. However, many of these optimization algorithms often possess some noteworthy shortcomings such as the trap of solutions at local extremes, or the limited number of design variables or the difficulty of dealing with discrete design variables. Thus, to overcome these limitations and develop an efficient computation tool for optimal design of the MRBs, an optimization procedure that combines differential evolution (DE), a gradient-free global optimization method with finite element analysis (FEA) is proposed in this paper. The proposed approach is then applied to the optimal design of MRBs with different configurations including conventional MRBs and MRBs with coils placed on the side housings. Moreover, to approach a real-life design, some necessary design variables of MRBs are considered as discrete variables in the optimization process. The obtained optimal design results are compared with those of available optimal designs in the literature. The results reveal that the proposed method outperforms some traditional approaches.
NASA Astrophysics Data System (ADS)
Yan, Bailu; Zhao, Zheng; Zhou, Yingcheng; Yuan, Wenyan; Li, Jian; Wu, Jun; Cheng, Daojian
2017-10-01
Swarm intelligence optimization algorithms are mainstream algorithms for solving complex optimization problems. Among these algorithms, the particle swarm optimization (PSO) algorithm has the advantages of fast computation speed and few parameters. However, PSO is prone to premature convergence. To solve this problem, we develop a new PSO algorithm (RPSOLF) by combining the characteristics of random learning mechanism and Levy flight. The RPSOLF algorithm increases the diversity of the population by learning from random particles and random walks in Levy flight. On the one hand, we carry out a large number of numerical experiments on benchmark test functions, and compare these results with the PSO algorithm with Levy flight (PSOLF) algorithm and other PSO variants in previous reports. The results show that the optimal solution can be found faster and more efficiently by the RPSOLF algorithm. On the other hand, the RPSOLF algorithm can also be applied to optimize the Lennard-Jones clusters, and the results indicate that the algorithm obtains the optimal structure (2-60 atoms) with an extraordinary high efficiency. In summary, RPSOLF algorithm proposed in our paper is proved to be an extremely effective tool for global optimization.
Design of a High Resolution Hexapod Positioning Mechanism
NASA Technical Reports Server (NTRS)
Britt, Jamie
2001-01-01
This paper describes the development of a high resolution, six-degree of freedom positioning mechanism. This mechanism, based on the Stewart platform concept, was designed for use with the Developmental Comparative Active Optics Telescope Testbed (DCATT), a ground-based technology testbed for the Next Generation Space Telescope (NGST). The mechanism provides active control to the DCATT telescope's segmented primary mirror. Emphasis is on design decisions and technical challenges. Significant issues include undesirable motion properties of PZT-inchworm actuators, testing difficulties, dimensional stability, and use of advanced composite materials. Supporting test data from prototype mechanisms is presented.
Design of a High Resolution Hexapod Positioning Mechanism
NASA Technical Reports Server (NTRS)
Britt, Jamie; Brodeur, Stephen J. (Technical Monitor)
2001-01-01
This paper describes the development of a high resolution, six-degree of freedom positioning mechanism. This mechanism, based on the Stewart platform concept, was designed for use with the Developmental Comparative Active Optics Telescope Testbed (DCATT), a ground-based technology testbed for the Next Generation Space Telescope (NGST). The mechanism provides active control to the DCATT telescope's segmented primary mirror. Emphasis is on design decisions and technical challenges. Significant issues include undesirable motion properties of PZT-inchworm actuators, testing difficulties, dimensional stability and use of advanced composite materials. Supporting test data from prototype mechanisms is presented.
Xue, Dingyü; Li, Tingxue
2017-04-27
The parameter optimization method for multivariable systems is extended to the controller design problems for multiple input multiple output (MIMO) square fractional-order plants. The algorithm can be applied to search for the optimal parameters of integer-order controllers for fractional-order plants with or without time delays. Two examples are given to present the controller design procedures for MIMO fractional-order systems. Simulation studies show that the integer-order controllers designed are robust to plant gain variations. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Popov, A.; Zolotarev, V.; Bychkov, S.
2016-11-01
This paper examines the results of experimental studies of a previously submitted combined algorithm designed to increase the reliability of information systems. The data that illustrates the organization and conduct of the studies is provided. Within the framework of a comparison of As a part of the study conducted, the comparison of the experimental data of simulation modeling and the data of the functioning of the real information system was made. The hypothesis of the homogeneity of the logical structure of the information systems was formulated, thus enabling to reconfigure the algorithm presented, - more specifically, to transform it into the model for the analysis and prediction of arbitrary information systems. The results presented can be used for further research in this direction. The data of the opportunity to predict the functioning of the information systems can be used for strategic and economic planning. The algorithm can be used as a means for providing information security.
A new iterative Fourier transform algorithm for optimal design in holographic optical tweezers
NASA Astrophysics Data System (ADS)
Memmolo, P.; Miccio, L.; Merola, F.; Ferraro, P.; Netti, P. A.
2012-06-01
We propose a new Iterative Fourier Transform Algorithm (IFTA) capable to suppress ghost traps and noise in Holographic Optical Tweezers (HOT), maintaining a high diffraction efficiency in a computational time comparable with the others iterative algorithms. The process consists in the planning of the suitable ideal target of optical tweezers as input of classical IFTA and we show we are able to design up to 4 real traps, in the field of view imaged by the microscope objective, using an IFTA built on fictitious phasors, located in strategic positions in the Fourier plane. The effectiveness of the proposed algorithm is evaluated both for numerical and optical reconstructions and compared with the other techniques known in literature.
Low-cost satellite mechanical design and construction
NASA Astrophysics Data System (ADS)
Boisjolie-Gair, Nathaniel; Straub, Jeremy
2017-05-01
This paper presents a discussion of techniques for low-cost design and construction of a CubeSat mechanical structure that can serve as a basis for academic programs and a starting point for government, military and commercial large-scale sensing networks, where the cost of each node must be minimized to facilitate system affordability and lower the cost and associated risk of losing any node. Spacecraft Design plays a large role in manufacturability. An intentionally simplified mechanical design is presented which reduces machining costs, as compared to more intricate designs that were considered. Several fabrication approaches are evaluated relative to the low-cost goal.
Design of 3D-Printed Titanium Compliant Mechanisms
NASA Technical Reports Server (NTRS)
Merriam, Ezekiel G.; Jones, Jonathan E.; Howell, Larry L.
2014-01-01
This paper describes 3D-printed titanium compliant mechanisms for aerospace applications. It is meant as a primer to help engineers design compliant, multi-axis, printed parts that exhibit high performance. Topics covered include brief introductions to both compliant mechanism design and 3D printing in titanium, material and geometry considerations for 3D printing, modeling techniques, and case studies of both successful and unsuccessful part geometries. Key findings include recommended flexure geometries, minimum thicknesses, and general design guidelines for compliant printed parts that may not be obvious to the first time designer.
High-Precision Orbital-Mechanics Computation Using the Parker-Sochaki Algorithm
NASA Astrophysics Data System (ADS)
Rudmin, Joseph W.
1997-04-01
This paper presents the first application of the Parker-Sochacki algorithm (G. Edgar Parker and James S. Sochacki, Neural, Parallel and Scientific Computations) 4 (1997) 97- 112. to the orbital mechanics of solar system. The Parker- Sochacki algorithm is a method of solving simultaneous differential equations, and is an extension of the Picard Iteration. It permits the generation of the coefficients of the MacLaurin Series quickly and to arbitrarily high order, limited only by the digital accuracy of the programming language. Each coefficient is calculated only once, with no later corrections being made. Taylor series coefficients can also be calculated by this method for the position and coordinates of the the center of mass and for the energy and angular momentum components. These coefficients show conservation to about one part in ten to the eighteenth for energy for a time step of 30 days.
The multi-disciplinary design study: A life cycle cost algorithm
NASA Technical Reports Server (NTRS)
Harding, R. R.; Pichi, F. J.
1988-01-01
The approach and results of a Life Cycle Cost (LCC) analysis of the Space Station Solar Dynamic Power Subsystem (SDPS) including gimbal pointing and power output performance are documented. The Multi-Discipline Design Tool (MDDT) computer program developed during the 1986 study has been modified to include the design, performance, and cost algorithms for the SDPS as described. As with the Space Station structural and control subsystems, the LCC of the SDPS can be computed within the MDDT program as a function of the engineering design variables. Two simple examples of MDDT's capability to evaluate cost sensitivity and design based on LCC are included. MDDT was designed to accept NASA's IMAT computer program data as input so that IMAT's detailed structural and controls design capability can be assessed with expected system LCC as computed by MDDT. No changes to IMAT were required. Detailed knowledge of IMAT is not required to perform the LCC analyses as the interface with IMAT is noninteractive.
SU-FF-T-668: A Simple Algorithm for Range Modulation Wheel Design in Proton Therapy
Nie, X; Nazaryan, Vahagn; Gueye, Paul; Keppel, Cynthia
2009-06-01
Purpose: To develop a simple algorithm in designing the range modulation wheel to generate a very smooth Spread-Out Bragg peak (SOBP) for proton therapy.Method and Materials: A simple algorithm has been developed to generate the weight factors in corresponding pristine Bragg peaks which composed a smooth SOBP in proton therapy. We used a modified analytical Bragg peak function based on Monte Carol simulation tool-kits of Geant4 as pristine Bragg peaks input in our algorithm. A simple METLAB(R) Quad Program was introduced to optimize the cost function in our algorithm. Results: We found out that the existed analytical function of Bragg peak can't directly use as pristine Bragg peak dose-depth profile input file in optimization of the weight factors since this model didn't take into account of the scattering factors introducing from the range shifts in modifying the proton beam energies. We have done Geant4 simulations for proton energy of 63.4 MeV with a 1.08 cm SOBP for variation of pristine Bragg peaks which composed this SOBP and modified the existed analytical Bragg peak functions for their peak heights, ranges of R{sub 0}, and Gaussian energies {sigma}{sub E}. We found out that 19 pristine Bragg peaks are enough to achieve a flatness of 1.5% of SOBP which is the best flatness in the publications. Conclusion: This work develops a simple algorithm to generate the weight factors which is used to design a range modulation wheel to generate a smooth SOBP in protonradiation therapy. We have found out that a medium number of pristine Bragg peaks are enough to generate a SOBP with flatness less than 2%. It is potential to generate data base to store in the treatment plan to produce a clinic acceptable SOBP by using our simple algorithm.
A quantum mechanics-based algorithm for vessel segmentation in retinal images
NASA Astrophysics Data System (ADS)
Youssry, Akram; El-Rafei, Ahmed; Elramly, Salwa
2016-06-01
Blood vessel segmentation is an important step in retinal image analysis. It is one of the steps required for computer-aided detection of ophthalmic diseases. In this paper, a novel quantum mechanics-based algorithm for retinal vessel segmentation is presented. The algorithm consists of three major steps. The first step is the preprocessing of the images to prepare the images for further processing. The second step is feature extraction where a set of four features is generated at each image pixel. These features are then combined using a nonlinear transformation for dimensionality reduction. The final step is applying a recently proposed quantum mechanics-based framework for image processing. In this step, pixels are mapped to quantum systems that are allowed to evolve from an initial state to a final state governed by Schrödinger's equation. The evolution is controlled by the Hamiltonian operator which is a function of the extracted features at each pixel. A measurement step is consequently performed to determine whether the pixel belongs to vessel or non-vessel classes. Many functional forms of the Hamiltonian are proposed, and the best performing form was selected. The algorithm is tested on the publicly available DRIVE database. The average results for sensitivity, specificity, and accuracy are 80.29, 97.34, and 95.83 %, respectively. These results are compared to some recently published techniques showing the superior performance of the proposed method. Finally, the implementation of the algorithm on a quantum computer and the challenges facing this implementation are introduced.
Validation and application of modeling algorithms for the design of molecularly imprinted polymers.
Liu, Bing; Ou, Lulu; Zhang, Fuyuan; Zhang, Zhijun; Li, Hongying; Zhu, Mengyu; Wang, Shuo
2014-12-01
In the study, four different semiempirical algorithms, modified neglect of diatomic overlap, a reparameterization of Austin Model 1, complete neglect of differential overlap and typed neglect of differential overlap, have been applied for the energy optimization of template, monomer, and template-monomer complexes of imprinted polymers. For phosmet-, estrone-, and metolcarb-imprinted polymers, the binding energies of template-monomer complexes were calculated and the docking configures were assessed in different molar ratio of template/monomer. It was found that two algorithms were not suitable for calculating the binding energy in template-monomers complex system. For the other algorithms, the obtained optimum molar ratio of template and monomers were consistent with the experimental results. Therefore, two algorithms have been selected and applied for the preparation of enrofloxacin-imprinted polymers. Meanwhile using a different molar ratio of template and monomer, we prepared imprinted polymers and nonimprinted polymers, and evaluated the adsorption to template. It was verified that the experimental results were in good agreement with the modeling results. As a result, the semiempirical algorithm had certain feasibility in designing the preparation of imprinted polymers.
Experimental designs for small randomised clinical trials: an algorithm for choice
2013-01-01
Background Small clinical trials are necessary when there are difficulties in recruiting enough patients for conventional frequentist statistical analyses to provide an appropriate answer. These trials are often necessary for the study of rare diseases as well as specific study populations e.g. children. It has been estimated that there are between 6,000 and 8,000 rare diseases that cover a broad range of diseases and patients. In the European Union these diseases affect up to 30 million people, with about 50% of those affected being children. Therapies for treating these rare diseases need their efficacy and safety evaluated but due to the small number of potential trial participants, a standard randomised controlled trial is often not feasible. There are a number of alternative trial designs to the usual parallel group design, each of which offers specific advantages, but they also have specific limitations. Thus the choice of the most appropriate design is not simple. Methods PubMed was searched to identify publications about the characteristics of different trial designs that can be used in randomised, comparative small clinical trials. In addition, the contents tables from 11 journals were hand-searched. An algorithm was developed using decision nodes based on the characteristics of the identified trial designs. Results We identified 75 publications that reported the characteristics of 12 randomised, comparative trial designs that can be used in for the evaluation of therapies in orphan diseases. The main characteristics and the advantages and limitations of these designs were summarised and used to develop an algorithm that may be used to help select an appropriate design for a given clinical situation. We used examples from publications of given disease-treatment-outcome situations, in which the investigators had used a particular trial design, to illustrate the use of the algorithm for the identification of possible alternative designs. Conclusions The
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.
Aspherical lens design using hybrid neural-genetic algorithm of contact lenses.
Yen, Chih-Ta; Ye, Jhe-Wen
2015-10-01
The design of complex contact lenses involves numerous uncertain variables. How to help an optical designer to first design the optimal contact lens to reduce discomfort when wearing a pair of glasses is an essential design concern. This study examined the impact of aberrations on contact lenses to optimize a contact lens design for myopic and astigmatic eyes. In general, two aspherical surfaces can be assembled in an optical system to reduce the overall volume size. However, this design reduces the spherical aberration (SA) values at wide contact radii. The proposed optimization algorithm with optical design can be corrected to improve the SA value and, thus, reduce coma aberration (TCO) values and enhance the modulation transfer function (MTF). This means integrating a modified genetic algorithm (GA) with a neural network (NN) to optimize multiple-quality characteristics, namely the SA, TCO, and MTF, of contact lenses. When the proposed optional weight NN-GA is implemented, the weight values of the fitness function can be varied to adjust system performance. The method simplifies the selection of parameters in the optimization of optical systems. Compared with the traditional CODE V built-in optimal scheme, the proposed scheme is more flexible and intuitive to improve SA, TCO, and MTF values by 50.03%, 45.78%, and 24.7%, respectively.
Iterative Fourier transform algorithm: different approaches to diffractive optical element design
NASA Astrophysics Data System (ADS)
Skeren, Marek; Richter, Ivan; Fiala, Pavel
2002-10-01
This contribution focuses on the study and comparison of different design approaches for designing phase-only diffractive optical elements (PDOEs) for different possible applications in laser beam shaping. Especially, new results and approaches, concerning the iterative Fourier transform algorithm, are analyzed, implemented, and compared. Namely, various approaches within the iterative Fourier transform algorithm (IFTA) are analyzed for the case of phase-only diffractive optical elements with quantizied phase levels (either binary or multilevel structures). First, the general scheme of the IFTA iterative approach with partial quantization is briefly presented and discussed. Then, the special assortment of the general IFTA scheme is given with respect to quantization constraint strategies. Based on such a special classification, the three practically interesting approaches are chosen, further-analyzed, and compared to eachother. The performance of these algorithms is compared in detail in terms of the signal-to-noise ratio characteristic developments with respect to the numberof iterations, for various input diffusive-type objects chose. Also, the performance is documented on the complex spectra developments for typical computer reconstruction results. The advantages and drawbacks of all approaches are discussed, and a brief guide on the choice of a particular approach for typical design tasks is given. Finally, the two ways of amplitude elimination within the design procedure are considered, namely the direct elimination and partial elimination of the amplitude of the complex hologram function.
Saha, S. K.; Dutta, R.; Choudhury, R.; Kar, R.; Mandal, D.; Ghoshal, S. P.
2013-01-01
In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems. PMID:23844390
Zhu, Wu; Fang, Jian-an; Tang, Yang; Zhang, Wenbing; Du, Wei
2012-01-01
Design of a digital infinite-impulse-response (IIR) filter is the process of synthesizing and implementing a recursive filter network so that a set of prescribed excitations results a set of desired responses. However, the error surface of IIR filters is usually non-linear and multi-modal. In order to find the global minimum indeed, an improved differential evolution (DE) is proposed for digital IIR filter design in this paper. The suggested algorithm is a kind of DE variants with a controllable probabilistic (CPDE) population size. It considers the convergence speed and the computational cost simultaneously by nonperiodic partial increasing or declining individuals according to fitness diversities. In addition, we discuss as well some important aspects for IIR filter design, such as the cost function value, the influence of (noise) perturbations, the convergence rate and successful percentage, the parameter measurement, etc. As to the simulation result, it shows that the presented algorithm is viable and comparable. Compared with six existing State-of-the-Art algorithms-based digital IIR filter design methods obtained by numerical experiments, CPDE is relatively more promising and competitive.
Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P
2013-01-01
In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.
Zhu, Wu; Fang, Jian-an; Tang, Yang; Zhang, Wenbing; Du, Wei
2012-01-01
Design of a digital infinite-impulse-response (IIR) filter is the process of synthesizing and implementing a recursive filter network so that a set of prescribed excitations results a set of desired responses. However, the error surface of IIR filters is usually non-linear and multi-modal. In order to find the global minimum indeed, an improved differential evolution (DE) is proposed for digital IIR filter design in this paper. The suggested algorithm is a kind of DE variants with a controllable probabilistic (CPDE) population size. It considers the convergence speed and the computational cost simultaneously by nonperiodic partial increasing or declining individuals according to fitness diversities. In addition, we discuss as well some important aspects for IIR filter design, such as the cost function value, the influence of (noise) perturbations, the convergence rate and successful percentage, the parameter measurement, etc. As to the simulation result, it shows that the presented algorithm is viable and comparable. Compared with six existing State-of-the-Art algorithms-based digital IIR filter design methods obtained by numerical experiments, CPDE is relatively more promising and competitive. PMID:22808191
Orion Guidance and Control Ascent Abort Algorithm Design and Performance Results
NASA Technical Reports Server (NTRS)
Proud, Ryan W.; Bendle, John R.; Tedesco, Mark B.; Hart, Jeremy J.
2009-01-01
During the ascent flight phase of NASA s Constellation Program, the Ares launch vehicle propels the Orion crew vehicle to an agreed to insertion target. If a failure occurs at any point in time during ascent then a system must be in place to abort the mission and return the crew to a safe landing with a high probability of success. To achieve continuous abort coverage one of two sets of effectors is used. Either the Launch Abort System (LAS), consisting of the Attitude Control Motor (ACM) and the Abort Motor (AM), or the Service Module (SM), consisting of SM Orion Main Engine (OME), Auxiliary (Aux) Jets, and Reaction Control System (RCS) jets, is used. The LAS effectors are used for aborts from liftoff through the first 30 seconds of second stage flight. The SM effectors are used from that point through Main Engine Cutoff (MECO). There are two distinct sets of Guidance and Control (G&C) algorithms that are designed to maximize the performance of these abort effectors. This paper will outline the necessary inputs to the G&C subsystem, the preliminary design of the G&C algorithms, the ability of the algorithms to predict what abort modes are achievable, and the resulting success of the abort system. Abort success will be measured against the Preliminary Design Review (PDR) abort performance metrics and overall performance will be reported. Finally, potential improvements to the G&C design will be discussed.
Optimal fractional delay-IIR filter design using cuckoo search algorithm.
Kumar, Manjeet; Rawat, Tarun Kumar
2015-11-01
This paper applied a novel global meta-heuristic optimization algorithm, cuckoo search algorithm (CSA) to determine optimal coefficients of a fractional delay-infinite impulse response (FD-IIR) filter and trying to meet the ideal frequency response characteristics. Since fractional delay-IIR filter design is a multi-modal optimization problem, it cannot be computed efficiently using conventional gradient based optimization techniques. A weighted least square (WLS) based fitness function is used to improve the performance to a great extent. FD-IIR filters of different orders have been designed using the CSA. The simulation results of the proposed CSA based approach have been compared to those of well accepted evolutionary algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The performance of the CSA based FD-IIR filter is superior to those obtained by GA and PSO. The simulation and statistical results affirm that the proposed approach using CSA outperforms GA and PSO, not only in the convergence rate but also in optimal performance of the designed FD-IIR filter (i.e., smaller magnitude error, smaller phase error, higher percentage improvement in magnitude and phase error, fast convergence rate). The absolute magnitude and phase error obtained for the designed 5th order FD-IIR filter are as low as 0.0037 and 0.0046, respectively. The percentage improvement in magnitude error for CSA based 5th order FD-IIR design with respect to GA and PSO are 80.93% and 74.83% respectively, and phase error are 76.04% and 71.25%, respectively. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Thermal design of spiral heat exchangers and heat pipes through global best algorithm
NASA Astrophysics Data System (ADS)
Turgut, Oğuz Emrah; Çoban, Mustafa Turhan
2017-03-01
This study deals with global best algorithm based thermal design of spiral heat exchangers and heat pipes. Spiral heat exchangers are devices which are highly efficient in extremely dirty and fouling process duties. Spirals inherent in design maintain high heat transfer coefficients while avoiding hazardous effects of fouling and uneven fluid distribution in the channels. Heat pipes have wide usage in industry. Thanks to the two phase cycle which takes part in operation, they can transfer high amount of heat with a negligible temperature gradient. In this work, a new stochastic based optimization method global best algorithm is applied for multi objective optimization of spiral heat exchangers as well as single objective optimization for heat pipes. Global best algorithm is easy-to-implement, free of derivatives and it can be reliably applied to any optimization problem. Case studies taken from the literature approaches are solved by the proposed algorithm and results obtained from the literature approaches are compared with thosed acquired by GBA. Comparisons reveal that GBA attains better results than literature studies in terms of solution accuracy and efficiency.
Genetic algorithms for the design of looped irrigation water distribution networks
NASA Astrophysics Data System (ADS)
Reca, Juan; MartíNez, Juan
2006-05-01
A new computer model called Genetic Algorithm Pipe Network Optimization Model (GENOME) has been developed with the aim of optimizing the design of new looped irrigation water distribution networks. The model is based on a genetic algorithm method, although relevant modifications and improvements have been implemented to adapt the model to this specific problem. It makes use of the robust network solver EPANET. The model has been tested and validated by applying it to the least cost optimization of several benchmark networks reported in the literature. The results obtained with GENOME have been compared with those found in previous works, obtaining the same results as the best published in the literature to date. Once the model was validated, the optimization of a real complex irrigation network has been carried out to evaluate the potential of the genetic algorithm for the optimal design of large-scale networks. Although satisfactory results have been obtained, some adjustments would be desirable to improve the performance of genetic algorithms when the complexity of the network requires it.
Design and Validation of the Quantum Mechanics Conceptual Survey
ERIC Educational Resources Information Center
McKagan, S. B.; Perkins, K. K.; Wieman, C. E.
2010-01-01
The Quantum Mechanics Conceptual Survey (QMCS) is a 12-question survey of students' conceptual understanding of quantum mechanics. It is intended to be used to measure the relative effectiveness of different instructional methods in modern physics courses. In this paper, we describe the design and validation of the survey, a process that included…
Design and Validation of the Quantum Mechanics Conceptual Survey
ERIC Educational Resources Information Center
McKagan, S. B.; Perkins, K. K.; Wieman, C. E.
2010-01-01
The Quantum Mechanics Conceptual Survey (QMCS) is a 12-question survey of students' conceptual understanding of quantum mechanics. It is intended to be used to measure the relative effectiveness of different instructional methods in modern physics courses. In this paper, we describe the design and validation of the survey, a process that included…
NASA Astrophysics Data System (ADS)
Shen, Xin; Zhang, Jing; Yao, Huang
2015-12-01
Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.
Simple geometric algorithms to aid in clearance management for robotic mechanisms
NASA Technical Reports Server (NTRS)
Copeland, E. L.; Ray, L. D.; Peticolas, J. D.
1981-01-01
Global geometric shapes such as lines, planes, circles, spheres, cylinders, and the associated computational algorithms which provide relatively inexpensive estimates of minimum spatial clearance for safe operations were selected. The Space Shuttle, remote manipulator system, and the Power Extension Package are used as an example. Robotic mechanisms operate in quarters limited by external structures and the problem of clearance is often of considerable interest. Safe clearance management is simple and suited to real time calculation, whereas contact prediction requires more precision, sophistication, and computational overhead.
Design and verification of mechanisms for a large foldable antenna
NASA Technical Reports Server (NTRS)
Luhmann, Hans Jurgen; Etzler, Carl Christian; Wagner, Rudolf
1989-01-01
The characteristics of the Synthetic Aperture Radar (SAR) antenna aboard the ESA Remote Sensing Satellite (ERS-1) are presented. The antenna is folded into a dense package for launch and is deployed in orbit. The design requirements and constraints, their impact on the design, and the resulting features of the mechanisms are discussed.
Mechanical design of NASA Ames Research Center vertical motion simulator
NASA Technical Reports Server (NTRS)
Engelbert, D. F.; Bakke, A. P.; Chargin, M. K.; Vallotton, W. C.
1976-01-01
NASA has designed and is constructing a new flight simulator with large vertical travel. Several aspects of the mechanical design of this Vertical Motion Simulator (VMS) are discussed, including the multiple rack and pinion vertical drive, a pneumatic equilibration system, and the friction-damped rigid link catenaries used as cable supports.
Sampling-based algorithms for analysis and design of hybrid and embedded systems
NASA Astrophysics Data System (ADS)
Bhatia, Amit
linear hybrid systems and the applicability of the approach is shown using several examples. The proposed framework and the algorithms can be used for analysis and design of hybrid and embedded systems, including but not limited to, aerospace and robotic systems.
NASA Astrophysics Data System (ADS)
Sciandra, Vincent
performance of the algorithm generated sectors to the current sectors for a variety of configurations and scenarios, and comparing these results to those of the current sectors. The effect of dynamic airspace configurations will then be tested by observing the effects of update rate on the algorithm generated sector results. Finally, the algorithm will be used with simulated data, whose evaluation would show the ability of the sector design algorithm to meet the objectives of the NextGen system. Upon validation, the algorithm may be successfully incorporated into a larger Terminal Flow Algorithm, developed by our partners at Mosaic ATM, as the final step in the TDAC process.
Montgomery, Christopher J.; Yang, Chongguan; Parkinson, Alan R.; Chen, J.-Y.
2006-01-01
A genetic optimization algorithm has been applied to the selection of quasi-steady-state (QSS) species in reduced chemical kinetic mechanisms. The algorithm seeks to minimize the error between reduced and detailed chemistry for simple reactor calculations approximating conditions of interest for a computational fluid dynamics simulation. The genetic algorithm does not guarantee that the global optimum will be found, but much greater accuracy can be obtained than by choosing QSS species through a simple kinetic criterion or by human trial and error. The algorithm is demonstrated for methane-air combustion over a range of temperatures and stoichiometries and for homogeneous charge compression ignition engine combustion. The results are in excellent agreement with those predicted by the baseline mechanism. A factor of two reduction in the number of species was obtained for a skeletal mechanism that had already been greatly reduced from the parent detailed mechanism.
Schalkoff, R.J.; Shaaban, K.M.; Carver, A.E.
1996-12-31
The ARIES {number_sign}1 (Autonomous Robotic Inspection Experimental System) vision system is used to acquire drum surface images under controlled conditions and subsequently perform autonomous visual inspection leading to a classification as `acceptable` or `suspect`. Specific topics described include vision system design methodology, algorithmic structure,hardware processing structure, and image acquisition hardware. Most of these capabilities were demonstrated at the ARIES Phase II Demo held on Nov. 30, 1995. Finally, Phase III efforts are briefly addressed.
2007-08-01
Advanced non- linear control algorithms applied to design highly maneuverable Autonomous Underwater Vehicles (AUVs) Vladimir Djapic, Jay A. Farrell...hierarchical such that an ”inner loop” non- linear controller (outputs the appropriate thrust values) is the same for all mission scenarios while a...library of ”outer-loop” non- linear controllers are available to implement specific maneuvering scenarios. On top of the outer-loop is the mission planner
Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions
2014-05-01
reads are dashed lines , writes are solid lines . . . . . . . . . . . . . . 18 15 Performance of the cross-weave (a,b,c,d) and wavefront scan (e,f,g,h...Tools (E2AT) and Next Generation Wide Area Motion Imagery (WAMI). An initial implementation of the 3D spatiotemporal median filter for background...extended the integral histogram approach to design and implement an initial version of the 3D spatiotemporal median filter algorithm for fast motion
Kleinberg, J M
1999-01-01
Protein sequence design is a natural inverse problem to protein structure prediction: given a target structure in three dimensions, we wish to design an amino acid sequence that is likely fold to it. A model of Sun, Brem, Chan, and Dill casts this problem as an optimization on a space of sequences of hydrophobic (H) and polar (P) monomers; the goal is to find a sequence that achieves a dense hydrophobic core with few solvent-exposed hydrophobic residues. Sun et al. developed a heuristic method to search the space of sequences, without a guarantee of optimality or near-optimality; Hart subsequently raised the computational tractability of constructing an optimal sequence in this model as an open question. Here we resolve this question by providing an efficient algorithm to construct optimal sequences; our algorithm has a polynomial running time, and performs very efficiently in practice. We illustrate the implementation of our method on structures drawn from the Protein Data Bank. We also consider extensions of the model to larger amino acid alphabets, as a way to overcome the limitations of the binary H/P alphabet. We show that for a natural class of arbitrarily large alphabets, it remains possible to design optimal sequences efficiently. Finally, we analyze some of the consequences of this sequence design model for the study of evolutionary fitness landscapes. A given target structure may have many sequences that are optimal in the model of Sun et al.; following a notion raised by the work of J. Maynard Smith, we can ask whether these optimal sequences are "connected" by successive point mutations. We provide a polynomial-time algorithm to decide this connectedness property, relative to a given target structure. We develop the algorithm by first solving an analogous problem expressed in terms of submodular functions, a fundamental object of study in combinatorial optimization.
Zhang, Jie; Wang, Yuping; Feng, Junhong
2013-01-01
In association rule mining, evaluating an association rule needs to repeatedly scan database to compare the whole database with the antecedent, consequent of a rule and the whole rule. In order to decrease the number of comparisons and time consuming, we present an attribute index strategy. It only needs to scan database once to create the attribute index of each attribute. Then all metrics values to evaluate an association rule do not need to scan database any further, but acquire data only by means of the attribute indices. The paper visualizes association rule mining as a multiobjective problem rather than a single objective one. In order to make the acquired solutions scatter uniformly toward the Pareto frontier in the objective space, elitism policy and uniform design are introduced. The paper presents the algorithm of attribute index and uniform design based multiobjective association rule mining with evolutionary algorithm, abbreviated as IUARMMEA. It does not require the user-specified minimum support and minimum confidence anymore, but uses a simple attribute index. It uses a well-designed real encoding so as to extend its application scope. Experiments performed on several databases demonstrate that the proposed algorithm has excellent performance, and it can significantly reduce the number of comparisons and time consumption.
Efficient design of nanoplasmonic waveguide devices using the space mapping algorithm.
Dastmalchi, Pouya; Veronis, Georgios
2013-12-30
We show that the space mapping algorithm, originally developed for microwave circuit optimization, can enable the efficient design of nanoplasmonic waveguide devices which satisfy a set of desired specifications. Space mapping utilizes a physics-based coarse model to approximate a fine model accurately describing a device. Here the fine model is a full-wave finite-difference frequency-domain (FDFD) simulation of the device, while the coarse model is based on transmission line theory. We demonstrate that simply optimizing the transmission line model of the device is not enough to obtain a device which satisfies all the required design specifications. On the other hand, when the iterative space mapping algorithm is used, it converges fast to a design which meets all the specifications. In addition, full-wave FDFD simulations of only a few candidate structures are required before the iterative process is terminated. Use of the space mapping algorithm therefore results in large reductions in the required computation time when compared to any direct optimization method of the fine FDFD model.
Career Profiles- Aero-Mechanical Design- Operations Engineering Branch
2015-10-26
NASA Armstrong’s Aeromechanical Design Group provides mechanical design solutions ranging from research and development to ground support equipment. With an aerospace or mechanical engineering background, team members use the latest computer-aided design software to create one-of-kind parts, assemblies, and drawings, and aid in the design’s fabrication and integration. Reverse engineering and inspection of Armstrong’s fleet of aircraft is made possible by using state-of-the-art coordinate measuring machines and laser scanning equipment.
Process Improvement Through Tool Integration in Aero-Mechanical Design
NASA Technical Reports Server (NTRS)
Briggs, Clark
2010-01-01
Emerging capabilities in commercial design tools promise to significantly improve the multi-disciplinary and inter-disciplinary design and analysis coverage for aerospace mechanical engineers. This paper explores the analysis process for two example problems of a wing and flap mechanical drive system and an aircraft landing gear door panel. The examples begin with the design solid models and include various analysis disciplines such as structural stress and aerodynamic loads. Analytical methods include CFD, multi-body dynamics with flexible bodies and structural analysis. Elements of analysis data management, data visualization and collaboration are also included.
Process Improvement Through Tool Integration in Aero-Mechanical Design
NASA Technical Reports Server (NTRS)
Briggs, Clark
2010-01-01
Emerging capabilities in commercial design tools promise to significantly improve the multi-disciplinary and inter-disciplinary design and analysis coverage for aerospace mechanical engineers. This paper explores the analysis process for two example problems of a wing and flap mechanical drive system and an aircraft landing gear door panel. The examples begin with the design solid models and include various analysis disciplines such as structural stress and aerodynamic loads. Analytical methods include CFD, multi-body dynamics with flexible bodies and structural analysis. Elements of analysis data management, data visualization and collaboration are also included.
Design and optimization of a bend-and-sweep compliant mechanism
NASA Astrophysics Data System (ADS)
Tummala, Y.; Frecker, M. I.; Wissa, A. A.; Hubbard, J. E., Jr.
2013-09-01
A novel contact aided compliant mechanism called bend-and-sweep compliant mechanism is presented in this paper. This mechanism has nonlinear stiffness properties in two orthogonal directions. An angled compliant joint (ACJ) is the fundamental element of this mechanism. Geometric parameters of ACJs determine the stiffness of the compliant mechanism. This paper presents the design and optimization of bend-and-sweep compliant mechanism. A multi-objective optimization problem was formulated for design optimization of the bend-and-sweep compliant mechanism. The objectives of the optimization problem were to maximize or minimize the bending and sweep displacements, depending on the situation, while minimizing the von Mises stress and mass of each mechanism. This optimization problem was solved using NSGA-II (a genetic algorithm). The results of this optimization for a single ACJ during upstroke and downstroke are presented in this paper. Results of two different loading conditions used during optimization of a single ACJ for upstroke are presented. Finally, optimization results comparing the performance of compliant mechanisms with one and two ACJs are also presented. It can be inferred from these results that the number of ACJs and the design of each ACJ determines the stiffness of the bend-and-sweep compliant mechanism. These mechanisms can be used in various applications. The goal of this research is to improve the performance of ornithopters by passively morphing their wings. In order to achieve a bio-inspired wing gait called continuous vortex gait, the wings of the ornithopter need to bend, and sweep simultaneously. This can be achieved by inserting the bend-and-sweep compliant mechanism into the leading edge wing spar of the ornithopters.
[Bone biopsy needles: mechanical properties, needle design and specimen quality].
Keulers, A; Cunha-Cruz, V C; Bruners, P; Penzkofer, T; Braunschweig, T; Schmitz-Rode, T; Mahnken, A
2011-03-01
To quantitatively analyze differences in mechanical properties, needle design including signs of wear, subjective handling and specimen quality of bone biopsy needles. In this study 19 different bone biopsy systems (total 38; 2 /type) were examined. With each biopsy needle five consecutive samples were obtained from vertebral bodies of swine. During puncture a force-torques sensor measured the mechanical properties and subjective handling was assessed. Before and after each biopsy the needles were investigated using a profile projector and signs of wear were recorded. Afterwards, a pathologist semi-quantitatively examined the specimen regarding sample quality. The overall evaluation considered mechanical properties, needle wear, subjective handling and sample quality. Differences were assessed for statistical significance using ANOVA and t-test. Needle diameter (p = 0.003) as well as needle design (p = 0.008) affect the mechanical properties significantly. Franseen design is significantly superior to other needle designs. Besides, length reduction recorded by the profile projector, as a quality criterion showed notable distinctions in between the needle designs. Bone biopsy needles vary significantly in performance. Needle design has an important influence on mechanical properties, handling and specimen quality. Detailed knowledge of those parameters would improve selecting the appropriate bone biopsy needle. © Georg Thieme Verlag KG Stuttgart · New York.
Design methodology of microstructures for enhanced mechanical reliability
NASA Astrophysics Data System (ADS)
Wittler, Olaf; Walter, Hans; Vogel, Dietmar; Keller, Juergen; Michel, Bernd
2005-04-01
The achievement of reliability is a major task during the design process of microsystems (i.e. MEMS: mechanical-electrical microsystems). In this respect CAD (computer aided design) simulation methods play a major role in the dimensioning of mechanical structures. It can be observed that a pure CAD approach becomes difficult because of the complexity of these systems, which originates from the large variety of integrated materials and thus a diversity of the resulting failure mechanisms. Therefore strategies dealing with these uncertainties in reliability estimates need to be incorporated in the design process. The approach presented in this paper is based on the application of simulation and advanced deformation measurement methods named microDAC (micro deformation analysis by means of grey scale correlation) and nanoDAC. It is exemplified on different detail levels of the reliability assessment, with an emphasis on fracture. The first stage consists of a parametric simulation approach, which helps to develop design guidelines for the geometry. For a more absolute quantitative analysis and for material selection in a new design the mechanical properties need to be specified and evaluated with respect to reliability. Besides, the described systematics of reliability assessment needs a profound knowledge of the failure behavior, which is analyzed by the application of microDAC/nanoDAC techniques. In the prescribed way, it becomes possible to tackle mechanical reliability problems in early design phases.
Accurate Design of Low Backscattering Metasurface Using Iterative Fourier Transform Algorithm.
Wang, Dan; Liu, Zhen Guo; Zhao, Jie; Cheng, Qiang; Cui, Tie Jun
2017-09-12
An accurate method is proposed to design low-backscattering metasurfaces efficiently using an iterative Fourier transform algorithm, which avoids the large amount of time-consuming numerical simulations of complicated electromagnetic problems and provides satisfactory performance to reduce the backward scattering. As an example of the application, a broadband low-backscattering metasurface is designed, fabricated, and characterized. Both full-wave simulation and measured results reveal that the proposed method offers a rapid and efficient tool to manipulate the scattering behaviors of the metasurface, and thus realizes significant scattering reductions.
Design tool for multiprocessor scheduling and evaluation of iterative dataflow algorithms
NASA Technical Reports Server (NTRS)
Jones, Robert L., III
1995-01-01
A graph-theoretic design process and software tool is defined for selecting a multiprocessing scheduling solution for a class of computational problems. The problems of interest are those that can be described with a dataflow graph and are intended to be executed repetitively on a set of identical processors. Typical applications include signal processing and control law problems. Graph-search algorithms and analysis techniques are introduced and shown to effectively determine performance bounds, scheduling constraints, and resource requirements. The software tool applies the design process to a given problem and includes performance optimization through the inclusion of additional precedence constraints among the schedulable tasks.
An algorithm to design finite field multipliers using a self-dual normal basis
NASA Technical Reports Server (NTRS)
Wang, Charles C.
1989-01-01
The concept of using a self-dual normal basis to design the Massey-Omura finite-field multiplier is presented. An algorithm is given to locate a self-dual normal basis for GF(2m) for odd m. A method to construct the product function for designing the Massey-Omura multiplier is developed. It is shown that the construction of the product function based on a self-dual basis is simpler than that based on an arbitrary normal basis.
Bieniawski, Z.T.
1996-04-01
A good designer needs not only knowledge for designing (technical know-how that is used to generate alternative design solutions) but also must have knowledge about designing (appropriate principles and systematic methodology to follow). Concepts such as {open_quotes}design for manufacture{close_quotes} or {open_quotes}concurrent engineering{close_quotes} are widely used in the industry. In the field of rock engineering, only limited attention has been paid to the design process because design of structures in rock masses presents unique challenges to the designers as a result of the uncertainties inherent in characterization of geologic media. However, a stage has now been reached where we are be able to sufficiently characterize rock masses for engineering purposes and identify the rock mechanics issues involved but are still lacking engineering design principles and methodology to maximize our design performance. This paper discusses the principles and methodology of the engineering design process directed to integrating site characterization activities with design, construction and performance of an underground repository. Using the latest information from the Yucca Mountain Project on geology, rock mechanics and starter tunnel design, the current lack of integration is pointed out and it is shown how rock mechanics issues can be effectively interwoven with repository design through a systematic design process methodology leading to improved repository performance. In essence, the design process is seen as the use of design principles within an integrating design methodology, leading to innovative problem solving. In particular, a new concept of {open_quotes}Design for Constructibility and Performance{close_quotes} is introduced. This is discussed with respect to ten rock mechanics issues identified for repository design and performance.
Designing an Algorithm to Preserve Privacy for Medical Record Linkage With Error-Prone Data
Pal, Doyel; Chen, Tingting; Khethavath, Praveen
2014-01-01
Background Linking medical records across different medical service providers is important to the enhancement of health care quality and public health surveillance. In records linkage, protecting the patients’ privacy is a primary requirement. In real-world health care databases, records may well contain errors due to various reasons such as typos. Linking the error-prone data and preserving data privacy at the same time are very difficult. Existing privacy preserving solutions for this problem are only restricted to textual data. Objective To enable different medical service providers to link their error-prone data in a private way, our aim was to provide a holistic solution by designing and developing a medical record linkage system for medical service providers. Methods To initiate a record linkage, one provider selects one of its collaborators in the Connection Management Module, chooses some attributes of the database to be matched, and establishes the connection with the collaborator after the negotiation. In the Data Matching Module, for error-free data, our solution offered two different choices for cryptographic schemes. For error-prone numerical data, we proposed a newly designed privacy preserving linking algorithm named the Error-Tolerant Linking Algorithm, that allows the error-prone data to be correctly matched if the distance between the two records is below a threshold. Results We designed and developed a comprehensive and user-friendly software system that provides privacy preserving record linkage functions for medical service providers, which meets the regulation of Health Insurance Portability and Accountability Act. It does not require a third party and it is secure in that neither entity can learn the records in the other’s database. Moreover, our novel Error-Tolerant Linking Algorithm implemented in this software can work well with error-prone numerical data. We theoretically proved the correctness and security of our Error
Ishida, Toshimasa; Nishimura, Ikuya; Tanino, Hiromasa; Higa, Masaru; Ito, Hiroshi; Mitamura, Yoshinori
2011-04-01
There are many designs of the femoral stem of a cemented total hip arthroplasty, and mechanical failure of the stem is caused by several factors related to the cement, such as failure of the cement. Optimization of the shape of the stem, especially multiobjective optimization, is required to solve these design problems because a cement fracture is caused by multiple factors. The objective of this study was to determine a stem geometry considering multiple factors at the same time. A three-dimensional finite element model of the proximal femur was developed from a composite femur. A total of four objective functions--two objective functions, the largest maximum principal stress of proximal and distal sections in the cement mantle, for each of the two boundary conditions, walking and stair climbing--were used. The neighborhood cultivation genetic algorithm was introduced to minimize these objective functions. The results showed that the geometry that leads to a decrease in the proximal cement stress and the geometry that leads to a decrease in the distal cement stress were not the same. However, the results of the walking and the stair climbing conditions matched. Five dominant stem designs were considered to be the Pareto solution, and one design was identified as the "better design" for all objective functions. It was shown that multiobjective optimization using a genetic algorithm may be used for optimizing the shape of the femoral stem in order to avoid cement fracture. © 2011, Copyright the Authors. Artificial Organs © 2011, International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.
Transportation Network with Fluctuating Input/Output Designed by the Bio-Inspired Physarum Algorithm
Watanabe, Shin; Takamatsu, Atsuko
2014-01-01
In this paper, we propose designing transportation network topology and traffic distribution under fluctuating conditions using a bio-inspired algorithm. The algorithm is inspired by the adaptive behavior observed in an amoeba-like organism, plasmodial slime mold, more formally known as plasmodium of Physarum plycephalum. This organism forms a transportation network to distribute its protoplasm, the fluidic contents of its cell, throughout its large cell body. In this process, the diameter of the transportation tubes adapts to the flux of the protoplasm. The Physarum algorithm, which mimics this adaptive behavior, has been widely applied to complex problems, such as maze solving and designing the topology of railroad grids, under static conditions. However, in most situations, environmental conditions fluctuate; for example, in power grids, the consumption of electric power shows daily, weekly, and annual periodicity depending on the lifestyles or the business needs of the individual consumers. This paper studies the design of network topology and traffic distribution with oscillatory input and output traffic flows. The network topology proposed by the Physarum algorithm is controlled by a parameter of the adaptation process of the tubes. We observe various rich topologies such as complete mesh, partial mesh, Y-shaped, and V-shaped networks depending on this adaptation parameter and evaluate them on the basis of three performance functions: loss, cost, and vulnerability. Our results indicate that consideration of the oscillatory conditions and the phase-lags in the multiple outputs of the network is important: The building and/or maintenance cost of the network can be reduced by introducing the oscillating condition, and when the phase-lag among the outputs is large, the transportation loss can also be reduced. We use stability analysis to reveal how the system exhibits various topologies depending on the parameter. PMID:24586616
Embedded EMD algorithm within an FPGA-based design to classify nonlinear SDOF systems
NASA Astrophysics Data System (ADS)
Jones, Jonathan D.; Pei, Jin-Song; Wright, Joseph P.; Tull, Monte P.
2010-04-01
Compared with traditional microprocessor-based systems, rapidly advancing field-programmable gate array (FPGA) technology offers a more powerful, efficient and flexible hardware platform. An FPGA and microprocessor (i.e., hardware and software) co-design is developed to classify three types of nonlinearities (including linear, hardening and softening) of a single-degree-of-freedom (SDOF) system subjected to free vibration. This significantly advances the team's previous work on using FPGAs for wireless structural health monitoring. The classification is achieved by embedding two important algorithms - empirical mode decomposition (EMD) and backbone curve analysis. Design considerations to embed EMD in FPGA and microprocessor are discussed. In particular, the implementation of cubic spline fitting and the challenges encountered using both hardware and software environments are discussed. The backbone curve technique is fully implemented within the FPGA hardware and used to extract instantaneous characteristics from the uniformly distributed data sets produced by the EMD algorithm as presented in a previous SPIE conference by the team. An off-the-shelf high-level abstraction tool along with the MATLAB/Simulink environment is utilized to manage the overall FPGA and microprocessor co-design. Given the limited computational resources of an embedded system, we strive for a balance between the maximization of computational efficiency and minimization of resource utilization. The value of this study lies well beyond merely programming existing algorithms in hardware and software. Among others, extensive and intensive judgment is exercised involving experiences and insights with these algorithms, which renders processed instantaneous characteristics of the signals that are well-suited for wireless transmission.
Watanabe, Shin; Takamatsu, Atsuko
2014-01-01
In this paper, we propose designing transportation network topology and traffic distribution under fluctuating conditions using a bio-inspired algorithm. The algorithm is inspired by the adaptive behavior observed in an amoeba-like organism, plasmodial slime mold, more formally known as plasmodium of Physarum plycephalum. This organism forms a transportation network to distribute its protoplasm, the fluidic contents of its cell, throughout its large cell body. In this process, the diameter of the transportation tubes adapts to the flux of the protoplasm. The Physarum algorithm, which mimics this adaptive behavior, has been widely applied to complex problems, such as maze solving and designing the topology of railroad grids, under static conditions. However, in most situations, environmental conditions fluctuate; for example, in power grids, the consumption of electric power shows daily, weekly, and annual periodicity depending on the lifestyles or the business needs of the individual consumers. This paper studies the design of network topology and traffic distribution with oscillatory input and output traffic flows. The network topology proposed by the Physarum algorithm is controlled by a parameter of the adaptation process of the tubes. We observe various rich topologies such as complete mesh, partial mesh, Y-shaped, and V-shaped networks depending on this adaptation parameter and evaluate them on the basis of three performance functions: loss, cost, and vulnerability. Our results indicate that consideration of the oscillatory conditions and the phase-lags in the multiple outputs of the network is important: The building and/or maintenance cost of the network can be reduced by introducing the oscillating condition, and when the phase-lag among the outputs is large, the transportation loss can also be reduced. We use stability analysis to reveal how the system exhibits various topologies depending on the parameter.
Regularizing common spatial patterns to improve BCI designs: unified theory and new algorithms.
Lotte, Fabien; Guan, Cuntai
2011-02-01
One of the most popular feature extraction algorithms for brain-computer interfaces (BCI) is common spatial patterns (CSPs). Despite its known efficiency and widespread use, CSP is also known to be very sensitive to noise and prone to overfitting. To address this issue, it has been recently proposed to regularize CSP. In this paper, we present a simple and unifying theoretical framework to design such a regularized CSP (RCSP). We then present a review of existing RCSP algorithms and describe how to cast them in this framework. We also propose four new RCSP algorithms. Finally, we compare the performances of 11 different RCSP (including the four new ones and the original CSP), on electroencephalography data from 17 subjects, from BCI competition datasets. Results showed that the best RCSP methods can outperform CSP by nearly 10% in median classification accuracy and lead to more neurophysiologically relevant spatial filters. They also enable us to perform efficient subject-to-subject transfer. Overall, the best RCSP algorithms were CSP with Tikhonov regularization and weighted Tikhonov regularization, both proposed in this paper.
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.
Design and simulation of imaging algorithm for Fresnel telescopy imaging system
NASA Astrophysics Data System (ADS)
Lv, Xiao-yu; Liu, Li-ren; Yan, Ai-min; Sun, Jian-feng; Dai, En-wen; Li, Bing
2011-06-01
Fresnel telescopy (short for Fresnel telescopy full-aperture synthesized imaging ladar) is a new high resolution active laser imaging technique. This technique is a variant of Fourier telescopy and optical scanning holography, which uses Fresnel zone plates to scan target. Compare with synthetic aperture imaging ladar(SAIL), Fresnel telescopy avoids problem of time synchronization and space synchronization, which decreasing technical difficulty. In one-dimensional (1D) scanning operational mode for moving target, after time-to-space transformation, spatial distribution of sampling data is non-uniform because of the relative motion between target and scanning beam. However, as we use fast Fourier transform (FFT) in the following imaging algorithm of matched filtering, distribution of data should be regular and uniform. We use resampling interpolation to transform the data into two-dimensional (2D) uniform distribution, and accuracy of resampling interpolation process mainly affects the reconstruction results. Imaging algorithms with different resampling interpolation algorithms have been analysis and computer simulation are also given. We get good reconstruction results of the target, which proves that the designed imaging algorithm for Fresnel telescopy imaging system is effective. This work is found to have substantial practical value and offers significant benefit for high resolution imaging system of Fresnel telescopy laser imaging ladar.
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.
NASA Astrophysics Data System (ADS)
Raghavan, Ajay; Saha, Bhaskar
2013-03-01
Photo enforcement devices for traffic rules such as red lights, toll, stops, and speed limits are increasingly being deployed in cities and counties around the world to ensure smooth traffic flow and public safety. These are typically unattended fielded systems, and so it is important to periodically check them for potential image/video quality problems that might interfere with their intended functionality. There is interest in automating such checks to reduce the operational overhead and human error involved in manually checking large camera device fleets. Examples of problems affecting such camera devices include exposure issues, focus drifts, obstructions, misalignment, download errors, and motion blur. Furthermore, in some cases, in addition to the sub-algorithms for individual problems, one also has to carefully design the overall algorithm and logic to check for and accurately classifying these individual problems. Some of these issues can occur in tandem or have the potential to be confused for each other by automated algorithms. Examples include camera misalignment that can cause some scene elements to go out of focus for wide-area scenes or download errors that can be misinterpreted as an obstruction. Therefore, the sequence in which the sub-algorithms are utilized is also important. This paper presents an overview of these problems along with no-reference and reduced reference image and video quality solutions to detect and classify such faults.
The design and hardware implementation of a low-power real-time seizure detection algorithm.
Raghunathan, Shriram; Gupta, Sumeet K; Ward, Matthew P; Worth, Robert M; Roy, Kaushik; Irazoqui, Pedro P
2009-10-01
Epilepsy affects more than 1% of the world's population. Responsive neurostimulation is emerging as an alternative therapy for the 30% of the epileptic patient population that does not benefit from pharmacological treatment. Efficient seizure detection algorithms will enable closed-loop epilepsy prostheses by stimulating the epileptogenic focus within an early onset window. Critically, this is expected to reduce neuronal desensitization over time and lead to longer-term device efficacy. This work presents a novel event-based seizure detection algorithm along with a low-power digital circuit implementation. Hippocampal depth-electrode recordings from six kainate-treated rats are used to validate the algorithm and hardware performance in this preliminary study. The design process illustrates crucial trade-offs in translating mathematical models into hardware implementations and validates statistical optimizations made with empirical data analyses on results obtained using a real-time functioning hardware prototype. Using quantitatively predicted thresholds from the depth-electrode recordings, the auto-updating algorithm performs with an average sensitivity and selectivity of 95.3 +/- 0.02% and 88.9 +/- 0.01% (mean +/- SE(alpha = 0.05)), respectively, on untrained data with a detection delay of 8.5 s [5.97, 11.04] from electrographic onset. The hardware implementation is shown feasible using CMOS circuits consuming under 350 nW of power from a 250 mV supply voltage from simulations on the MIT 180 nm SOI process.
NASA Astrophysics Data System (ADS)
Hessburg, Thomas; Lee, Michael; Takagi, Hideyuki; Tomizuka, Masayoshi
1993-12-01
A method of tuning a fuzzy logic controller (FLC) by a genetic algorithm (GA) is proposed for lane following maneuvers in an automated highway system. The GA simultaneously determines the shape of membership functions, number of rules, and consequent parameters of the FLC. The GA approach operates on binary representations of FLCs and uses an expression for a fitness score to be maximized, which takes into account the tracking error, yaw rate error, lateral acceleration error, rate of lateral acceleration, front wheel steering angle, and rate of front wheel steering angle, to find an optimal controller. Apriori knowledge about both the physical application and FLCs is incorporated into the design method to increase the performance of the design method and the resulting controller. The controllers designed by this method are compared in simulation to a conventional PID controller, a frequency shaped linear quadratic controller, and previously designed FLCs tuned manually.
An algorithm to design finite field multipliers using a self-dual normal basis
NASA Technical Reports Server (NTRS)
Wang, C. C.
1987-01-01
Finite field multiplication is central in the implementation of some error-correcting coders. Massey and Omura have presented a revolutionary design for multiplication in a finite field. In their design, a normal base is utilized to represent the elements of the field. The concept of using a self-dual normal basis to design the Massey-Omura finite field multiplier is presented. Presented first is an algorithm to locate a self-dual normal basis for GF(2 sup m) for odd m. Then a method to construct the product function for designing the Massey-Omura multiplier is developed. It is shown that the construction of the product function base on a self-dual basis is simpler than that based on an arbitrary normal base.
Genetic algorithm based design optimization of a permanent magnet brushless dc motor
NASA Astrophysics Data System (ADS)
Upadhyay, P. R.; Rajagopal, K. R.
2005-05-01
Genetic algorithm (GA) based design optimization of a permanent magnet brushless dc motor is presented in this paper. A 70 W, 350 rpm, ceiling fan motor with radial-filed configuration is designed by considering the efficiency as the objective function. Temperature-rise and motor weight are the constraints and the slot electric loading, magnet-fraction, slot-fraction, airgap, and airgap flux density are the design variables. The efficiency and the phase-inductance of the motor designed using the developed CAD program are improved by using the GA based optimization technique; from 84.75% and 5.55 mH to 86.06% and 2.4 mH, respectively.
An Optimal Design Methodology of Tapered Roller Bearings Using Genetic Algorithms
NASA Astrophysics Data System (ADS)
Tiwari, Rajiv; Sunil, Kumar K.; Reddy, R. S.
2012-03-01
In the design of tapered roller bearings, long life is the one of the most important criterion. The design of bearings has to satisfy constraints of geometry and strength, while operating at its rated speed. An optimal design methodology is needed to achieve this objective (i.e., the maximization of the fatigue life). The fatigue life is directly proportional to the dynamic capacity; hence, for the present case, the latter has been chosen as the objective function. It has been optimized by using a constrained nonlinear formulation with real-coded genetic algorithms. Design variables for the bearing include four geometrical parameters: the bearing pitch diameter, the diameter of the roller, the effective length of the roller, and the number of rollers. These directly affect the dynamic capacity of tapered roller bearings. In addition to these, another five design constraint constants are included, which indirectly affect the basic dynamic capacity of tapered roller bearings. The five design constraint constants have been given bounds based on the parametric studies through initial optimization runs. There is good agreement between the optimized and standard bearings in respect to the basic dynamic capacity. A convergence study has been carried out to ensure the global optimum point in the design. A sensitivity analysis of various design parameters, using the Monte Carlo simulation method, has been performed to see changes in the dynamic capacity. Illustrations show that none of the geometric design parameters have adverse affect on the dynamic capacity.
A Design Problem of Assembly Line Systems using Genetic Algorithm under the BTO Environment
NASA Astrophysics Data System (ADS)
Abe, Kazuaki; Yamada, Tetsuo; Matsui, Masayuki
Under the BTO environment, stochastic assembly lines require design methods which shorten not only the production lead time but also the ready time for the line design. We propose a design method for Assembly Line Systems (ALS) in Yamada et al. (2001) by using Genetic Algorithm (GA) and Adam-Eve GA, in which all design variables are determined in consideration of constraints such as line length related to the production lead time. First, an ALS model with a line length constraint is introduced, and an optimal design problem is set to maximize the net reward under shorter lead time. Next, a simulation optimization method is developed using Adam-Eve GA and traditional GA. Finally, an optimal design example is shown and discussed by comparing the 2-stage design by Yamada et al. (2001) and both the GA designs. It is shown that the Adam-Eve GA is superior to the traditional GA design in terms of computational time though there is only a slight difference in terms of net reward.
2014-01-01
Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. PMID:25431584
Chen, Tinggui; Xiao, Renbin
2014-01-01
Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.
Parametric Design and Mechanical Analysis of Beams based on SINOVATION
NASA Astrophysics Data System (ADS)
Xu, Z. G.; Shen, W. D.; Yang, D. Y.; Liu, W. M.
2017-07-01
In engineering practice, engineer needs to carry out complicated calculation when the loads on the beam are complex. The processes of analysis and calculation take a lot of time and the results are unreliable. So VS2005 and ADK are used to develop a software for beams design based on the 3D CAD software SINOVATION with C ++ programming language. The software can realize the mechanical analysis and parameterized design of various types of beams and output the report of design in HTML format. Efficiency and reliability of design of beams are improved.
SNL Mechanical Computer Aided Design (MCAD) guide 2007.
Moore, Brandon; Pollice, Stephanie L.; Martinez, Jack R.
2007-12-01
This document is considered a mechanical design best-practice guide to new and experienced designers alike. The contents consist of topics related to using Computer Aided Design (CAD) software, performing basic analyses, and using configuration management. The details specific to a particular topic have been leveraged against existing Product Realization Standard (PRS) and Technical Business Practice (TBP) requirements while maintaining alignment with sound engineering and design practices. This document is to be considered dynamic in that subsequent updates will be reflected in the main title, and each update will be published on an annual basis.
Multiaxial pedicle screw designs: static and dynamic mechanical testing.
Stanford, Ralph Edward; Loefler, Andreas Herman; Stanford, Philip Mark; Walsh, William R
2004-02-15
Randomized investigation of multiaxial pedicle screw mechanical properties. Measure static yield and ultimate strengths, yield stiffness, and fatigue resistance according to an established model. Compare these measured properties with expected loads in vivo. Multiaxial pedicle screws provide surgical versatility, but the complexity of their design may reduce their strength and fatigue resistance. There is no published data on the mechanical properties of such screws. Screws were assembled according to a vertebrectomy model for destructive mechanical testing. Groups of five assemblies were tested in static tension and compression and subject to three cyclical loads. Modes of failure, yield, and ultimate strength, yield stiffness, and cycles to failure were determined for six designs of screw. Static compression yield loads ranged from 217.1 to 388.0 N and yield stiffness from 23.7 to 38.0 N/mm. Cycles to failure ranged from 42 x 10(3) to 4,719 x 10(3) at 75% of static ultimate load. There were significant differences between designs in all modes of testing. Failure occurred at the multiaxial link in static and cyclical compression. Bending yield strengths just exceeded loads expected in vivo. Multiaxial designs had lower static bending yield strength than fixed screw designs. Five out of six multiaxial screw designs achieved one million cycles at 200 N in compression bending. "Ball-in-cup" multiaxial locking mechanisms were vulnerable to fatigue failure. Smooth surfaces and thicker material appeared to be protective against fatigue failure.
A high precision position sensor design and its signal processing algorithm for a maglev train.
Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen
2012-01-01
High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.
A High Precision Position Sensor Design and Its Signal Processing Algorithm for a Maglev Train
Xue, Song; Long, Zhiqiang; He, Ning; Chang, Wensen
2012-01-01
High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run. PMID:22778582
A Genetic Algorithm for the Bi-Level Topological Design of Local Area Networks.
Camacho-Vallejo, José-Fernando; Mar-Ortiz, Julio; López-Ramos, Francisco; Rodríguez, Ricardo Pedraza
2015-01-01
Local access networks (LAN) are commonly used as communication infrastructures which meet the demand of a set of users in the local environment. Usually these networks consist of several LAN segments connected by bridges. The topological LAN design bi-level problem consists on assigning users to clusters and the union of clusters by bridges in order to obtain a minimum response time network with minimum connection cost. Therefore, the decision of optimally assigning users to clusters will be made by the leader and the follower will make the decision of connecting all the clusters while forming a spanning tree. In this paper, we propose a genetic algorithm for solving the bi-level topological design of a Local Access Network. Our solution method considers the Stackelberg equilibrium to solve the bi-level problem. The Stackelberg-Genetic algorithm procedure deals with the fact that the follower's problem cannot be optimally solved in a straightforward manner. The computational results obtained from two different sets of instances show that the performance of the developed algorithm is efficient and that it is more suitable for solving the bi-level problem than a previous Nash-Genetic approach.
A new stochastic algorithm for proton exchange membrane fuel cell stack design optimization
NASA Astrophysics Data System (ADS)
Chakraborty, Uttara
2012-10-01
This paper develops a new stochastic heuristic for proton exchange membrane fuel cell stack design optimization. The problem involves finding the optimal size and configuration of stand-alone, fuel-cell-based power supply systems: the stack is to be configured so that it delivers the maximum power output at the load's operating voltage. The problem apparently looks straightforward but is analytically intractable and computationally hard. No exact solution can be found, nor is it easy to find the exact number of local optima; we, therefore, are forced to settle with approximate or near-optimal solutions. This real-world problem, first reported in Journal of Power Sources 131, poses both engineering challenges and computational challenges and is representative of many of today's open problems in fuel cell design involving a mix of discrete and continuous parameters. The new algorithm is compared against genetic algorithm, simulated annealing, and (1+1)-EA. Statistical tests of significance show that the results produced by our method are better than the best-known solutions for this problem published in the literature. A finite Markov chain analysis of the new algorithm establishes an upper bound on the expected time to find the optimum solution.
A Genetic Algorithm for the Bi-Level Topological Design of Local Area Networks
Camacho-Vallejo, José-Fernando; Mar-Ortiz, Julio; López-Ramos, Francisco; Rodríguez, Ricardo Pedraza
2015-01-01
Local access networks (LAN) are commonly used as communication infrastructures which meet the demand of a set of users in the local environment. Usually these networks consist of several LAN segments connected by bridges. The topological LAN design bi-level problem consists on assigning users to clusters and the union of clusters by bridges in order to obtain a minimum response time network with minimum connection cost. Therefore, the decision of optimally assigning users to clusters will be made by the leader and the follower will make the decision of connecting all the clusters while forming a spanning tree. In this paper, we propose a genetic algorithm for solving the bi-level topological design of a Local Access Network. Our solution method considers the Stackelberg equilibrium to solve the bi-level problem. The Stackelberg-Genetic algorithm procedure deals with the fact that the follower’s problem cannot be optimally solved in a straightforward manner. The computational results obtained from two different sets of instances show that the performance of the developed algorithm is efficient and that it is more suitable for solving the bi-level problem than a previous Nash-Genetic approach. PMID:26102502
A proteomics search algorithm specifically designed for high-resolution tandem mass spectra.
Wenger, Craig D; Coon, Joshua J
2013-03-01
The acquisition of high-resolution tandem mass spectra (MS/MS) is becoming more prevalent in proteomics, but most researchers employ peptide identification algorithms that were designed prior to this development. Here, we demonstrate new software, Morpheus, designed specifically for high-mass accuracy data, based on a simple score that is little more than the number of matching products. For a diverse collection of data sets from a variety of organisms (E. coli, yeast, human) acquired on a variety of instruments (quadrupole-time-of-flight, ion trap-orbitrap, and quadrupole-orbitrap) in different laboratories, Morpheus gives more spectrum, peptide, and protein identifications at a 1% false discovery rate (FDR) than Mascot, Open Mass Spectrometry Search Algorithm (OMSSA), and Sequest. Additionally, Morpheus is 1.5 to 4.6 times faster, depending on the data set, than the next fastest algorithm, OMSSA. Morpheus was developed in C# .NET and is available free and open source under a permissive license.