Optimization techniques in statistics
Rustagi, Jagdish S
1994-01-01
Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimiza
Dynamical optimization techniques for the calculation of electronic structure in solids
International Nuclear Information System (INIS)
Benedek, R.; Min, B.I.; Garner, J.
1989-01-01
The method of dynamical simulated annealing, recently introduced by Car and Parrinello, provides a new tool for electronic structure computation as well as for molecular dynamics simulation. In this paper, we explore an optimization technique that is complementary to dynamical simulated annealing, the method of steepest descents (SD). As an illustration, SD is applied to calculate the total energy of diamond-Si, a system previously treated by Car and Parrinello. The adaptation of SD to treat metallic systems is discussed and a numerical application is presented. (author) 18 refs., 3 figs
Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A
2012-07-02
Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of
Energy Technology Data Exchange (ETDEWEB)
Robar, James L., E-mail: james.robar@cdha.nshealth.ca [Department of Radiation Oncology, Dalhousie University, Halifax (Canada); Department of Physics and Atmospheric Science, Dalhousie University, Halifax (Canada); Thomas, Christopher [Department of Radiation Oncology, Dalhousie University, Halifax (Canada)
2012-01-01
This investigation focuses on possible dosimetric and efficiency advantages of HybridArc-a novel treatment planning approach combining optimized dynamic arcs with intensity-modulated radiation therapy (IMRT) beams. Application of this technique to two disparate sites, complex cranial tumors, and prostate was examined. HybridArc plans were compared with either dynamic conformal arc (DCA) or IMRT plans to determine whether HybridArc offers a synergy through combination of these 2 techniques. Plans were compared with regard to target volume dose conformity, target volume dose homogeneity, sparing of proximal organs at risk, normal tissue sparing, and monitor unit (MU) efficiency. For cranial cases, HybridArc produced significantly improved dose conformity compared with both DCA and IMRT but did not improve sparing of the brainstem or optic chiasm. For prostate cases, conformity was improved compared with DCA but not IMRT. Compared with IMRT, the dose homogeneity in the planning target volume was improved, and the maximum doses received by the bladder and rectum were reduced. Both arc-based techniques distribute peripheral dose over larger volumes of normal tissue compared with IMRT, whereas HybridArc involved slightly greater volumes of normal tissues compared with DCA. Compared with IMRT, cranial cases required 38% more MUs, whereas for prostate cases, MUs were reduced by 7%. For cranial cases, HybridArc improves dose conformity to the target. For prostate cases, dose conformity and homogeneity are improved compared with DCA and IMRT, respectively. Compared with IMRT, whether required MUs increase or decrease with HybridArc was site-dependent.
Zaleska, Anna; Bogaczyk, Krzysztof; Piotrowski, Tomasz
2017-01-01
The purpose of this study was to compare the values of integral dose, calculated for treatment plans of dynamic radiotherapy techniques prepared with two different optimization protocols. Delivering radiation by IMRT, VMAT and also HT techniques has an influence on the low dose deposition of large areas of the patient body. Delivery of low dose can induce injury of healthy cells. In this situation, a good solution would be to reduce the area, which receives a low dose, but with appropriate dose level for the target volume. To calculate integral dose values of plans structures, we used 90 external beam radiotherapy plans prepared for three techniques (intensity modulated radiotherapy, volumetric modulated arc therapy and helical tomotherapy). One technique includes three different geometry combinations. 45 plans were prepared with classic optimization protocol and 45 with rings optimization protocol which should reduce the low doses in the normal tissue. Differences in values of the integral dose depend on the geometry and technique of irradiation, as well as optimization protocol used in preparing treatment plans. The application of the rings optimization caused the value of normal tissue integral dose (NTID) to decrease. It is possible to limit the area of low dose irradiation and reduce NTID in dynamic techniques with the same clinical constraints for OAR and PTV volumes by using an optimization protocol other than the classic one.
Khusainov, R.; Klimchik, A.; Magid, E.
2017-01-01
The paper presents comparison analysis of two approaches in defining leg trajectories for biped locomotion. The first one operates only with kinematic limitations of leg joints and finds the maximum possible locomotion speed for given limits. The second approach defines leg trajectories from the dynamic stability point of view and utilizes ZMP criteria. We show that two methods give different trajectories and demonstrate that trajectories based on pure dynamic optimization cannot be realized due to joint limits. Kinematic optimization provides unstable solution which can be balanced by upper body movement.
A Dynamic Optimization Technique for Siting the NASA-Clark Atlanta Urban Rain Gauge Network (NCURN)
Shepherd, J. Marshall; Taylor, Layi
2003-01-01
NASA satellites and ground instruments have indicated that cities like Atlanta, Georgia may create or alter rainfall. Scientists speculate that the urban heat island caused by man-made surfaces in cities impact the heat and wind patterns that form clouds and rainfall. However, more conclusive evidence is required to substantiate findings from satellites. NASA, along with scientists at Clark Atlanta University, are implementing a dense, urban rain gauge network in the metropolitan Atlanta area to support a satellite validation program called Studies of PRecipitation Anomalies from Widespread Urban Landuse (SPRAWL). SPRAWL will be conducted during the summer of 2003 to further identify and understand the impact of urban Atlanta on precipitation variability. The paper provides an. overview of SPRAWL, which represents one of the more comprehensive efforts in recent years to focus exclusively on urban-impacted rainfall. The paper also introduces a novel technique for deploying rain gauges for SPRAWL. The deployment of the dense Atlanta network is unique because it utilizes Geographic Information Systems (GIS) and Decision Support Systems (DSS) to optimize deployment of the rain gauges. These computer aided systems consider access to roads, drainage systems, tree cover, and other factors in guiding the deployment of the gauge network. GIS and DSS also provide decision-makers with additional resources and flexibility to make informed decisions while considering numerous factors. Also, the new Atlanta network and SPRAWL provide a unique opportunity to merge the high-resolution, urban rain gauge network with satellite-derived rainfall products to understand how cities are changing rainfall patterns, and possibly climate.
Hu, Jingwen; Klinich, Kathleen D; Miller, Carl S; Nazmi, Giseli; Pearlman, Mark D; Schneider, Lawrence W; Rupp, Jonathan D
2009-11-13
Motor-vehicle crashes are the leading cause of fetal deaths resulting from maternal trauma in the United States, and placental abruption is the most common cause of these deaths. To minimize this injury, new assessment tools, such as crash-test dummies and computational models of pregnant women, are needed to evaluate vehicle restraint systems with respect to reducing the risk of placental abruption. Developing these models requires accurate material properties for tissues in the pregnant abdomen under dynamic loading conditions that can occur in crashes. A method has been developed for determining dynamic material properties of human soft tissues that combines results from uniaxial tensile tests, specimen-specific finite-element models based on laser scans that accurately capture non-uniform tissue-specimen geometry, and optimization techniques. The current study applies this method to characterizing material properties of placental tissue. For 21 placenta specimens tested at a strain rate of 12/s, the mean failure strain is 0.472+/-0.097 and the mean failure stress is 34.80+/-12.62 kPa. A first-order Ogden material model with ground-state shear modulus (mu) of 23.97+/-5.52 kPa and exponent (alpha(1)) of 3.66+/-1.90 best fits the test results. The new method provides a nearly 40% error reduction (p<0.001) compared to traditional curve-fitting methods by considering detailed specimen geometry, loading conditions, and dynamic effects from high-speed loading. The proposed method can be applied to determine mechanical properties of other soft biological tissues.
Simulation-based optimization parametric optimization techniques and reinforcement learning
Gosavi, Abhijit
2003-01-01
Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work. Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: *An accessible introduction to reinforcement learning and parametric-optimization techniques. *A step-by-step description of several algorithms of simulation-based optimization. *A clear and simple introduction to the methodology of neural networks. *A gentle introduction to converg...
OPTIMIZING HOTEL DYNAMIC PRICES
Directory of Open Access Journals (Sweden)
A. M. Bandalouski
2016-01-01
Full Text Available An approach to solvе a problem of determining optimal dynamic prices for hotel rooms is suggested. It includes selection of input parameters for the succeeding mathematical analysis, disaggregation of the demand into several categories, demand forecasting, simulation of demand- price relations, and a mathematical programming model for price optimization.
Optimal dynamic detection of explosives
Energy Technology Data Exchange (ETDEWEB)
Moore, David Steven [Los Alamos National Laboratory; Mcgrane, Shawn D [Los Alamos National Laboratory; Greenfield, Margo T [Los Alamos National Laboratory; Scharff, R J [Los Alamos National Laboratory; Rabitz, Herschel A [PRINCETON UNIV; Roslund, J [PRINCETON UNIV
2009-01-01
The detection of explosives is a notoriously difficult problem, especially at stand-off distances, due to their (generally) low vapor pressure, environmental and matrix interferences, and packaging. We are exploring optimal dynamic detection to exploit the best capabilities of recent advances in laser technology and recent discoveries in optimal shaping of laser pulses for control of molecular processes to significantly enhance the standoff detection of explosives. The core of the ODD-Ex technique is the introduction of optimally shaped laser pulses to simultaneously enhance sensitivity of explosives signatures while reducing the influence of noise and the signals from background interferents in the field (increase selectivity). These goals are being addressed by operating in an optimal nonlinear fashion, typically with a single shaped laser pulse inherently containing within it coherently locked control and probe sub-pulses. With sufficient bandwidth, the technique is capable of intrinsically providing orthogonal broad spectral information for data fusion, all from a single optimal pulse.
Optimization by record dynamics
DEFF Research Database (Denmark)
Barettin, Daniele; Sibani, Paolo
2014-01-01
Large dynamical changes in thermalizing glassy systems are triggered by trajectories crossing record sized barriers, a behavior revealing the presence of a hierarchical structure in configuration space. The observation is here turned into a novel local search optimization algorithm dubbed record...... dynamics optimization,or RDO. RDO uses the Metropolis rule to accept or reject candidate solutions depending on the value of a parameter akin to the temperature and minimizes the cost function of the problem at hand through cycles where its ‘temperature’ is raised and subsequently decreased in order...
Mechanical Design Optimization Using Advanced Optimization Techniques
Rao, R Venkata
2012-01-01
Mechanical design includes an optimization process in which designers always consider objectives such as strength, deflection, weight, wear, corrosion, etc. depending on the requirements. However, design optimization for a complete mechanical assembly leads to a complicated objective function with a large number of design variables. It is a good practice to apply optimization techniques for individual components or intermediate assemblies than a complete assembly. Analytical or numerical methods for calculating the extreme values of a function may perform well in many practical cases, but may fail in more complex design situations. In real design problems, the number of design parameters can be very large and their influence on the value to be optimized (the goal function) can be very complicated, having nonlinear character. In these complex cases, advanced optimization algorithms offer solutions to the problems, because they find a solution near to the global optimum within reasonable time and computational ...
Metaheuristics for Dynamic Optimization
Nakib, Amir; Siarry, Patrick
2013-01-01
This book is an updated effort in summarizing the trending topics and new hot research lines in solving dynamic problems using metaheuristics. An analysis of the present state in solving complex problems quickly draws a clear picture: problems that change in time, having noise and uncertainties in their definition are becoming very important. The tools to face these problems are still to be built, since existing techniques are either slow or inefficient in tracking the many global optima that those problems are presenting to the solver technique. Thus, this book is devoted to include several of the most important advances in solving dynamic problems. Metaheuristics are the more popular tools to this end, and then we can find in the book how to best use genetic algorithms, particle swarm, ant colonies, immune systems, variable neighborhood search, and many other bioinspired techniques. Also, neural network solutions are considered in this book. Both, theory and practice have been addressed in the chapters of t...
Xian, Guangming
2018-03-01
A method for predicting the optimal vibration field parameters by least square support vector machine (LS-SVM) is presented in this paper. One convenient and commonly used technique for characterizing the the vibration flow field of polymer melts films is small angle light scattering (SALS) in a visualized slit die of the electromagnetism dynamic extruder. The optimal value of vibration vibration frequency, vibration amplitude, and the maximum light intensity projection area can be obtained by using LS-SVM for prediction. For illustrating this method and show its validity, the flowing material is used with polypropylene (PP) and fifteen samples are tested at the rotation speed of screw at 36rpm. This paper first describes the apparatus of SALS to perform the experiments, then gives the theoretical basis of this new method, and detail the experimental results for parameter prediction of vibration flow field. It is demonstrated that it is possible to use the method of SALS and obtain detailed information on optimal parameter of vibration flow field of PP melts by LS-SVM.
Dynamic stochastic optimization
Ermoliev, Yuri; Pflug, Georg
2004-01-01
Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective an...
Optimal Resilient Dynamic Dictionaries
DEFF Research Database (Denmark)
Jørgensen, Allan Grønlund; Brodal, Gerth Stølting; Moruz, Gabriel
2007-01-01
updates in $O(\\log n+\\delta)$ amortized time. Our dynamic dictionary also supports range queries in $O(\\log n+\\delta+t)$ worst case time, where $t$ is the size of the output. Finally, we show that every resilient search tree (with some reasonable properties) must take~$\\Omega(\\log n + \\delta)$ worst...
Dynamic optimization and differential games
Friesz, Terry L
2010-01-01
Dynamic Optimization and Differential Games has been written to address the increasing number of Operations Research and Management Science problems that involve the explicit consideration of time and of gaming among multiple agents. With end-of-chapter exercises throughout, it is a book that can be used both as a reference and as a textbook. It will be useful as a guide to engineers, operations researchers, applied mathematicians and social scientists whose work involves both the theoretical and computational aspects of dynamic optimization and differential games. Included throughout the text are detailed explanations of several original dynamic and game-theoretic mathematical models which are of particular relevance in today's technologically-driven-global economy: revenue management, oligopoly pricing, production planning, supply chain management, dynamic traffic assignment and dynamic congestion pricing. The book emphasizes deterministic theory, computational tools and applications associated with the stu...
Optimal lag in dynamical investments
Serva, M.
1998-01-01
A portfolio of different stocks and a risk-less security whose composition is dynamically maintained stable by trading shares at any time step leads to a growth of the capital with a nonrandom rate. This is the key for the theory of optimal-growth investment formulated by Kelly. In presence of transaction costs, the optimal composition changes and, more important, it turns out that the frequency of transactions must be reduced. This simple observation leads to the definition of an optimal lag...
Cache Energy Optimization Techniques For Modern Processors
Energy Technology Data Exchange (ETDEWEB)
Mittal, Sparsh [ORNL
2013-01-01
newcomers and veterans in the field of cache power management. It will help graduate students, CAD tool developers and designers in understanding the need of energy efficiency in modern computing systems. Further, it will be useful for researchers in gaining insights into algorithms and techniques for micro-architectural and system-level energy optimization using dynamic cache reconfiguration. We sincerely believe that the ``food for thought'' presented in this book will inspire the readers to develop even better ideas for designing ``green'' processors of tomorrow.
Stochastic dynamics and combinatorial optimization
Ovchinnikov, Igor V.; Wang, Kang L.
2017-11-01
Natural dynamics is often dominated by sudden nonlinear processes such as neuroavalanches, gamma-ray bursts, solar flares, etc., that exhibit scale-free statistics much in the spirit of the logarithmic Ritcher scale for earthquake magnitudes. On phase diagrams, stochastic dynamical systems (DSs) exhibiting this type of dynamics belong to the finite-width phase (N-phase for brevity) that precedes ordinary chaotic behavior and that is known under such names as noise-induced chaos, self-organized criticality, dynamical complexity, etc. Within the recently proposed supersymmetric theory of stochastic dynamics, the N-phase can be roughly interpreted as the noise-induced “overlap” between integrable and chaotic deterministic dynamics. As a result, the N-phase dynamics inherits the properties of the both. Here, we analyze this unique set of properties and conclude that the N-phase DSs must naturally be the most efficient optimizers: on one hand, N-phase DSs have integrable flows with well-defined attractors that can be associated with candidate solutions and, on the other hand, the noise-induced attractor-to-attractor dynamics in the N-phase is effectively chaotic or aperiodic so that a DS must avoid revisiting solutions/attractors thus accelerating the search for the best solution. Based on this understanding, we propose a method for stochastic dynamical optimization using the N-phase DSs. This method can be viewed as a hybrid of the simulated and chaotic annealing methods. Our proposition can result in a new generation of hardware devices for efficient solution of various search and/or combinatorial optimization problems.
Polyhedral Techniques in Combinatorial Optimization
Aardal, K.I.; van Hoesel, S.
1995-01-01
Combinatorial optimization problems arise in several areas ranging from management to mathematics and graph theory. Most combinatorial optimization problems are compu- tationally hard due to the restriction that a subset of the variables have to take integral values. During the last two decades
Energy Technology Data Exchange (ETDEWEB)
Rilling, M [Département de physique, de génie physique et d’optique, Université Laval, Quebec City, QC (Canada); Centre de Recherche sur le Cancer, Hôtel-Dieu de Québec, Quebec City, QC (Canada); Département de radio-oncologie, CHU de Québec, Quebec City, QC (Canada); Center for Optics, Photonics and Lasers, Université Laval, Quebec City, QC, CA (Canada); Goulet, M [Département de radio-oncologie, CHU de Québec, Quebec City, QC (Canada); Thibault, S [Département de physique, de génie physique et d’optique, Université Laval, Quebec City, QC (Canada); Center for Optics, Photonics and Lasers, Université Laval, Quebec City, QC, CA (Canada); Archambault, L [Département de physique, de génie physique et d’optique, Université Laval, Quebec City, QC (Canada); Centre de Recherche sur le Cancer, Hôtel-Dieu de Québec, Quebec City, QC (Canada); Département de radio-oncologie, CHU de Québec, Quebec City, QC (Canada)
2015-06-15
Purpose: The purpose of this work is to simulate a multi-focus plenoptic camera used as the measuring device in a real-time three-dimensional scintillation dosimeter. Simulating and optimizing this realistic optical system will bridge the technological gap between concept validation and a clinically viable tool that can provide highly efficient, accurate and precise measurements for dynamic radiotherapy techniques. Methods: The experimental prototype, previously developed for proof of concept purposes, uses an off-the-shelf multi-focus plenoptic camera. With an array of interleaved microlenses of different focal lengths, this camera records spatial and angular information of light emitted by a plastic scintillator volume. The three distinct microlens focal lengths were determined experimentally for use as baseline parameters by measuring image-to-object magnification for different distances in object space. A simulated plenoptic system was implemented using the non-sequential ray tracing software Zemax: this tool allows complete simulation of multiple optical paths by modeling interactions at interfaces such as scatter, diffraction, reflection and refraction. The active sensor was modeled based on the camera manufacturer specifications by a 2048×2048, 5 µm-pixel pitch sensor. Planar light sources, simulating the plastic scintillator volume, were employed for ray tracing simulations. Results: The microlens focal lengths were determined to be 384, 327 and 290 µm. A realistic multi-focus plenoptic system, with independently defined and optimizable specifications, was fully simulated. A f/2.9 and 54 mm-focal length Double Gauss objective was modeled as the system’s main lens. A three-focal length hexagonal microlens array of 250-µm thickness was designed, acting as an image-relay system between the main lens and sensor. Conclusion: Simulation of a fully modeled multi-focus plenoptic camera enables the decoupled optimization of the main lens and microlens
Dynamic optimization in environmental economics
Energy Technology Data Exchange (ETDEWEB)
Moser, Elke; Tragler, Gernot; Veliov, Vladimir M. (eds.) [Vienna Univ. of Technology (Austria). Inst. of Mathematical Methods in Economics; Semmler, Willi [The New School for Social Research, New York, NY (United States). Dept. of Economics
2014-11-01
This book contains two chapters with the topics: 1. Chapter: INTERACTIONS BETWEEN ECONOMY AND CLIMATE: (a) Climate Change and Technical Progress: Impact of Informational Constraints. (b) Environmental Policy in a Dynamic Model with Heterogeneous Agents and Voting. (c) Optimal Environmental Policy in the Presence of Multiple Equilibria and Reversible Hysteresis. (d). Modeling the Dynamics of the Transition to a Green Economy. (e) One-Parameter GHG Emission Policy With R and D-Based Growth. (f) Pollution, Public Health Care, and Life Expectancy when Inequality Matters. (g) Uncertain Climate Policy and the Green Paradox. (h) Uniqueness Versus Indeterminacy in the Tragedy of the Commons - A ''Geometric'' Approach. 2. Chapter: OPTIMAL EXTRACTION OF RESOURCES: (j) Dynamic Behavior of Oil Importers and Exporters Under Uncertainty. (k) Robust Control of a Spatially Distributed Commercial Fishery. (l) On the Effect of Resource Exploitation on Growth: Domestic Innovation vs. Technological Diffusion Through Trade. (m) Forest Management and Biodiversity in Size-Structured Forests Under Climate Change. (n) Carbon Taxes and Comparison of Trading Regimes in Fossil Fuels. (o) Landowning, Status and Population Growth. (p) Optimal Harvesting of Size-Structured Biological Populations.
Dynamic optimization in environmental economics
International Nuclear Information System (INIS)
Moser, Elke; Tragler, Gernot; Veliov, Vladimir M.; Semmler, Willi
2014-01-01
This book contains two chapters with the topics: 1. Chapter: INTERACTIONS BETWEEN ECONOMY AND CLIMATE: (a) Climate Change and Technical Progress: Impact of Informational Constraints. (b) Environmental Policy in a Dynamic Model with Heterogeneous Agents and Voting. (c) Optimal Environmental Policy in the Presence of Multiple Equilibria and Reversible Hysteresis. (d). Modeling the Dynamics of the Transition to a Green Economy. (e) One-Parameter GHG Emission Policy With R and D-Based Growth. (f) Pollution, Public Health Care, and Life Expectancy when Inequality Matters. (g) Uncertain Climate Policy and the Green Paradox. (h) Uniqueness Versus Indeterminacy in the Tragedy of the Commons - A ''Geometric'' Approach. 2. Chapter: OPTIMAL EXTRACTION OF RESOURCES: (j) Dynamic Behavior of Oil Importers and Exporters Under Uncertainty. (k) Robust Control of a Spatially Distributed Commercial Fishery. (l) On the Effect of Resource Exploitation on Growth: Domestic Innovation vs. Technological Diffusion Through Trade. (m) Forest Management and Biodiversity in Size-Structured Forests Under Climate Change. (n) Carbon Taxes and Comparison of Trading Regimes in Fossil Fuels. (o) Landowning, Status and Population Growth. (p) Optimal Harvesting of Size-Structured Biological Populations.
On the manifold-mapping optimization technique
D. Echeverria (David); P.W. Hemker (Piet)
2006-01-01
textabstractIn this paper, we study in some detail the manifold-mapping optimization technique introduced in an earlier paper. Manifold mapping aims at accelerating optimal design procedures that otherwise require many evaluations of time-expensive cost functions. We give a proof of convergence for
Dynamic Optimization of Bytecode Instrumentation
Zheng Yudi; Bulej Lubomír; Zhang Cheng; Kell Stephen; Ansaloni Danilo; Binder Walter
2013-01-01
Accuracy completeness and performance are all major concerns in the context of dynamic program analysis. Emphasizing one of these factors may compromise the other factors. For example improving completeness of an analysis may seriously impair performance. In this paper we present an analysis model and a framework that enables reducing analysis overhead at runtime through adaptive instrumentation of the base program. Our approach targets analyses implemented with code instrumentation technique...
Optimal Formation Trajectory-Planning Using Parameter Optimization Technique
Directory of Open Access Journals (Sweden)
Hyung-Chul Lim
2004-09-01
Full Text Available Some methods have been presented to get optimal formation trajectories in the step of configuration or reconfiguration, which subject to constraints of collision avoidance and final configuration. In this study, a method for optimal formation trajectory-planning is introduced in view of fuel/time minimization using parameter optimization technique which has not been applied to optimal trajectory-planning for satellite formation flying. New constraints of nonlinear equality are derived for final configuration and constraints of nonlinear inequality are used for collision avoidance. The final configuration constraints are that three or more satellites should be placed in an equilateral polygon of the circular horizontal plane orbit. Several examples are given to get optimal trajectories based on the parameter optimization problem which subjects to constraints of collision avoidance and final configuration. They show that the introduced method for trajectory-planning is well suited to trajectory design problems of formation flying missions.
Dynamic optimization of human walking.
Anderson, F C; Pandy, M G
2001-10-01
A three-dimensional, neuromusculoskeletal model of the body was combined with dynamic optimization theory to simulate normal walking on level ground. The body was modeled as a 23 degree-of-freedom mechanical linkage, actuated by 54 muscles. The dynamic optimization problem was to calculate the muscle excitation histories, muscle forces, and limb motions subject to minimum metabolic energy expenditure per unit distance traveled. Muscle metabolic energy was calculated by slimming five terms: the basal or resting heat, activation heat, maintenance heat, shortening heat, and the mechanical work done by all the muscles in the model. The gait cycle was assumed to be symmetric; that is, the muscle excitations for the right and left legs and the initial and terminal states in the model were assumed to be equal. Importantly, a tracking problem was not solved. Rather only a set of terminal constraints was placed on the states of the model to enforce repeatability of the gait cycle. Quantitative comparisons of the model predictions with patterns of body-segmental displacements, ground-reaction forces, and muscle activations obtained from experiment show that the simulation reproduces the salient features of normal gait. The simulation results suggest that minimum metabolic energy per unit distance traveled is a valid measure of walking performance.
DEFF Research Database (Denmark)
Farahani, Saeed Davoudabadi; Andersen, Michael Skipper; de Zee, Mark
2012-01-01
derived from the detailed musculoskeletal analysis. The technique is demonstrated on a human model pedaling a bicycle. We use a physiology-based cost function expressing the mean square of all muscle activities over the cycle to predict a realistic motion pattern. Posture and motion prediction......, the parameters of these functions are optimized to produce an optimum posture or movement according to a user-defined cost function and constraints. The cost function and the constraints are typically express performance, comfort, injury risk, fatigue, muscle load, joint forces and other physiological properties...
Utilizing parallel optimization in computational fluid dynamics
Kokkolaras, Michael
1998-12-01
General problems of interest in computational fluid dynamics are investigated by means of optimization. Specifically, in the first part of the dissertation, a method of optimal incremental function approximation is developed for the adaptive solution of differential equations. Various concepts and ideas utilized by numerical techniques employed in computational mechanics and artificial neural networks (e.g. function approximation and error minimization, variational principles and weighted residuals, and adaptive grid optimization) are combined to formulate the proposed method. The basis functions and associated coefficients of a series expansion, representing the solution, are optimally selected by a parallel direct search technique at each step of the algorithm according to appropriate criteria; the solution is built sequentially. In this manner, the proposed method is adaptive in nature, although a grid is neither built nor adapted in the traditional sense using a-posteriori error estimates. Variational principles are utilized for the definition of the objective function to be extremized in the associated optimization problems, ensuring that the problem is well-posed. Complicated data structures and expensive remeshing algorithms and systems solvers are avoided. Computational efficiency is increased by using low-order basis functions and concurrent computing. Numerical results and convergence rates are reported for a range of steady-state problems, including linear and nonlinear differential equations associated with general boundary conditions, and illustrate the potential of the proposed method. Fluid dynamics applications are emphasized. Conclusions are drawn by discussing the method's limitations, advantages, and possible extensions. The second part of the dissertation is concerned with the optimization of the viscous-inviscid-interaction (VII) mechanism in an airfoil flow analysis code. The VII mechanism is based on the concept of a transpiration velocity
Efficient reanalysis techniques for robust topology optimization
DEFF Research Database (Denmark)
Amir, Oded; Sigmund, Ole; Lazarov, Boyan Stefanov
2012-01-01
The article focuses on the reduction of the computational effort involved in robust topology optimization procedures. The performance of structures designed by means of topology optimization may be seriously degraded due to fabrication errors. Robust formulations of the optimization problem were...... shown to yield optimized designs that are tolerant with respect to such manufacturing uncertainties. The main drawback of such procedures is the added computational cost associated with the need to evaluate a set of designs by performing multiple finite element analyses. In this article, we propose...... efficient robust topology optimization procedures based on reanalysis techniques. The approach is demonstrated on two compliant mechanism design problems where robust design is achieved by employing either a worst case formulation or a stochastic formulation. It is shown that the time spent on finite...
Design optimization applied in structural dynamics
Akcay-Perdahcioglu, Didem; de Boer, Andries; van der Hoogt, Peter; Tiskarna, T
2007-01-01
This paper introduces the design optimization strategies, especially for structures which have dynamic constraints. Design optimization involves first the modeling and then the optimization of the problem. Utilizing the Finite Element (FE) model of a structure directly in an optimization process
Evolutionary computation for dynamic optimization problems
Yao, Xin
2013-01-01
This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time. Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.
Dynamical System Approaches to Combinatorial Optimization
DEFF Research Database (Denmark)
Starke, Jens
2013-01-01
Several dynamical system approaches to combinatorial optimization problems are described and compared. These include dynamical systems derived from penalty methods; the approach of Hopfield and Tank; self-organizing maps, that is, Kohonen networks; coupled selection equations; and hybrid methods...
Numerical derivative techniques for trajectory optimization
Hallman, Wayne P.
1990-01-01
The adoption of robust numerical optimization techniques in trajectory simulation programs has resulted in powerful design and analysis tools. These trajectory simulation/optimization programs are widely used, and a representative list includes the GTS system, the POST program, and newer collocation methods such as OTIS and FONPAC. All of these programs rely on optimization algorithms which require objective function and constraint gradient data during the iteration process. However, most trajectory optimization problems lack simple analytical expressions for these derivatives. In the general case a function evaluation involves integrating aerodynamic, propulsive, and gravity forces over multiple trajectory phases with complex control models. With the newer collocation methods, the integration is replaced by defect constraints and cubic approximations for the state. While analytic gradient expressions can sometimes be derived for trajectory optimization problems, the derivation is cumbersome, time consuming, and prone to mistakes. Fortunately, an alternate method exists for the gradient evaluation, namely finite difference approximations. In this paper some finite difference gradient techniques developed for use with the GTS system are presented. These techniques include methods for computing first and second partial derivatives of single and multiple sets of functions. A key feature of these methods is an error control mechanism which automatically adjusts the perturbation size to obtain accurate derivative values.
Dynamic Optimization of UV Flash Processes
DEFF Research Database (Denmark)
Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp
2017-01-01
UV ash processes, also referred to as isoenergetic-isochoric ash processes, occur for dynamic simulation and optimization of vapor-liquid equilibrium processes. Dynamic optimization and nonlinear model predictive control of distillation columns, certain two-phase ow problems, as well as oil...
Fusion blanket design and optimization techniques
International Nuclear Information System (INIS)
Gohar, Y.
2005-01-01
In fusion reactors, the blanket design and its characteristics have a major impact on the reactor performance, size, and economics. The selection and arrangement of the blanket materials, dimensions of the different blanket zones, and different requirements of the selected materials for a satisfactory performance are the main parameters, which define the blanket performance. These parameters translate to a large number of variables and design constraints, which need to be simultaneously considered in the blanket design process. This represents a major design challenge because of the lack of a comprehensive design tool capable of considering all these variables to define the optimum blanket design and satisfying all the design constraints for the adopted figure of merit and the blanket design criteria. The blanket design techniques of the First Wall/Blanket/Shield Design and Optimization System (BSDOS) have been developed to overcome this difficulty and to provide the state-of-the-art techniques and tools for performing blanket design and analysis. This report describes some of the BSDOS techniques and demonstrates its use. In addition, the use of the optimization technique of the BSDOS can result in a significant blanket performance enhancement and cost saving for the reactor design under consideration. In this report, examples are presented, which utilize an earlier version of the ITER solid breeder blanket design and a high power density self-cooled lithium blanket design for demonstrating some of the BSDOS blanket design techniques
Optimal placement of FACTS devices using optimization techniques: A review
Gaur, Dipesh; Mathew, Lini
2018-03-01
Modern power system is dealt with overloading problem especially transmission network which works on their maximum limit. Today’s power system network tends to become unstable and prone to collapse due to disturbances. Flexible AC Transmission system (FACTS) provides solution to problems like line overloading, voltage stability, losses, power flow etc. FACTS can play important role in improving static and dynamic performance of power system. FACTS devices need high initial investment. Therefore, FACTS location, type and their rating are vital and should be optimized to place in the network for maximum benefit. In this paper, different optimization methods like Particle Swarm Optimization (PSO), Genetic Algorithm (GA) etc. are discussed and compared for optimal location, type and rating of devices. FACTS devices such as Thyristor Controlled Series Compensator (TCSC), Static Var Compensator (SVC) and Static Synchronous Compensator (STATCOM) are considered here. Mentioned FACTS controllers effects on different IEEE bus network parameters like generation cost, active power loss, voltage stability etc. have been analyzed and compared among the devices.
TRACKING CODE DEVELOPMENT FOR BEAM DYNAMICS OPTIMIZATION
Energy Technology Data Exchange (ETDEWEB)
Yang, L.
2011-03-28
Dynamic aperture (DA) optimization with direct particle tracking is a straight forward approach when the computing power is permitted. It can have various realistic errors included and is more close than theoretical estimations. In this approach, a fast and parallel tracking code could be very helpful. In this presentation, we describe an implementation of storage ring particle tracking code TESLA for beam dynamics optimization. It supports MPI based parallel computing and is robust as DA calculation engine. This code has been used in the NSLS-II dynamics optimizations and obtained promising performance.
Performance Evaluation of Dynamic Particle Swarm Optimization
Ms. Hemlata S. Urade; Rahila Patel
2012-01-01
In this paper the concept of dynamic particle swarmoptimization is introduced. The dynamic PSO is different fromthe existing PSO’s and some local version of PSO in terms ofswarm size and topology. Experiment conducted for benchmarkfunctions of single objective optimization problem, which showsthe better performance rather the basic PSO. The paper alsocontains the comparative analysis for Simple PSO and DynamicPSO which shows the better result for dynamic PSO rather thansimple PSO.
Sensitivity analysis in dynamic optimization
Evers, A.H.
1980-01-01
To find the optimal control of chemical processes, Pontryagin's minimum principle can be used. In practice, however, one is not only interested in the optimal solution, which satisfies the restrictions on the control, the initial and terminal conditions, and the process parameters. It is also
Emerging Dynamic Design Techniques for Mechanical and ...
Indian Academy of Sciences (India)
Emerging Dynamic Design Techniques for Mechanical and Structural Systems. Foreword. This special issue documents some of the contributed research papers discussed during the proceedings of IUTAM-IITD International Winter School on Optimum Dynamic Design using Modal Testing and Structural Dynamic ...
Machine Learning Techniques in Optimal Design
Cerbone, Giuseppe
1992-01-01
Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution
TECHNIQUE OF OPTIMAL AUDIT PLANNING FOR INFORMATION SECURITY MANAGEMENT SYSTEM
Directory of Open Access Journals (Sweden)
F. N. Shago
2014-03-01
Full Text Available Complication of information security management systems leads to the necessity of improving the scientific and methodological apparatus for these systems auditing. Planning is an important and determining part of information security management systems auditing. Efficiency of audit will be defined by the relation of the reached quality indicators to the spent resources. Thus, there is an important and urgent task of developing methods and techniques for optimization of the audit planning, making it possible to increase its effectiveness. The proposed technique gives the possibility to implement optimal distribution for planning time and material resources on audit stages on the basis of dynamics model for the ISMS quality. Special feature of the proposed approach is the usage of a priori data as well as a posteriori data for the initial audit planning, and also the plan adjustment after each audit event. This gives the possibility to optimize the usage of audit resources in accordance with the selected criteria. Application examples of the technique are given while planning audit information security management system of the organization. The result of computational experiment based on the proposed technique showed that the time (cost audit costs can be reduced by 10-15% and, consequently, quality assessments obtained through audit resources allocation can be improved with respect to well-known methods of audit planning.
Dynamic positioning configuration and its first-order optimization
Xue, Shuqiang; Yang, Yuanxi; Dang, Yamin; Chen, Wu
2014-02-01
symmetrical cone configuration and helical curve configuration are still D-optimal. It shows that the given total observation time determines the optimal frequency (repeatability) of moving known points and vice versa, and one way to improve the repeatability is to increase the rotational speed. Under the Newton's law of motion, the frequency of satellite motion determines the orbital altitude. Furthermore, we study three kinds of complex dynamic configurations, one of which is the combination of D-optimal cone configurations and a so-called Walker constellation composed of D-optimal helical configuration, the other is the nested cone configuration composed of n cones, and the last is the nested helical configuration composed of n orbital planes. It shows that an effective way to achieve high coverage is to employ the configuration composed of a certain number of moving known points instead of the simplex configuration (such as D-optimal helical configuration), and one can use the D-optimal simplex solutions or D-optimal complex configurations in any combination to achieve powerful configurations with flexile coverage and flexile repeatability. Alternately, how to optimally generate and assess the discrete configurations sampled from the continuous one is discussed. The proposed configuration optimization framework has taken the well-known regular polygons (such as equilateral triangle and quadrangular) in two-dimensional space and regular polyhedrons (regular tetrahedron, cube, regular octahedron, regular icosahedron, or regular dodecahedron) into account. It shows that the conclusions made by the proposed technique are more general and no longer limited by different sampling schemes. By the conditional equation of D-optimal nested helical configuration, the relevance issues of GNSS constellation optimization are solved and some examples are performed by GPS constellation to verify the validation of the newly proposed optimization technique. The proposed technique is
Evolutionary optimization technique for site layout planning
El Ansary, Ayman M.
2014-02-01
Solving the site layout planning problem is a challenging task. It requires an iterative approach to satisfy design requirements (e.g. energy efficiency, skyview, daylight, roads network, visual privacy, and clear access to favorite views). These design requirements vary from one project to another based on location and client preferences. In the Gulf region, the most important socio-cultural factor is the visual privacy in indoor space. Hence, most of the residential houses in this region are surrounded by high fences to provide privacy, which has a direct impact on other requirements (e.g. daylight and direction to a favorite view). This paper introduces a novel technique to optimally locate and orient residential buildings to satisfy a set of design requirements. The developed technique is based on genetic algorithm which explores the search space for possible solutions. This study considers two dimensional site planning problems. However, it can be extended to solve three dimensional cases. A case study is presented to demonstrate the efficiency of this technique in solving the site layout planning of simple residential dwellings. © 2013 Elsevier B.V. All rights reserved.
Parallel halftoning technique using dot diffusion optimization
Molina-Garcia, Javier; Ponomaryov, Volodymyr I.; Reyes-Reyes, Rogelio; Cruz-Ramos, Clara
2017-05-01
In this paper, a novel approach for halftone images is proposed and implemented for images that are obtained by the Dot Diffusion (DD) method. Designed technique is based on an optimization of the so-called class matrix used in DD algorithm and it consists of generation new versions of class matrix, which has no baron and near-baron in order to minimize inconsistencies during the distribution of the error. Proposed class matrix has different properties and each is designed for two different applications: applications where the inverse-halftoning is necessary, and applications where this method is not required. The proposed method has been implemented in GPU (NVIDIA GeForce GTX 750 Ti), multicore processors (AMD FX(tm)-6300 Six-Core Processor and in Intel core i5-4200U), using CUDA and OpenCV over a PC with linux. Experimental results have shown that novel framework generates a good quality of the halftone images and the inverse halftone images obtained. The simulation results using parallel architectures have demonstrated the efficiency of the novel technique when it is implemented in real-time processing.
Dynamic optimization deterministic and stochastic models
Hinderer, Karl; Stieglitz, Michael
2016-01-01
This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.
Greenhouse Environmental Control Using Optimized MIMO PID Technique
Directory of Open Access Journals (Sweden)
Fateh BOUNAAMA
2011-10-01
Full Text Available Climate control for protected crops brings the added dimension of a biological system into a physical system control situation. The thermally dynamic nature of a greenhouse suggests that disturbance attenuation (load control of external temperature, humidity, and sunlight is far more important than is the case for controlling other types of buildings. This paper investigates the application of multi-inputs multi-outputs (MIMO PID controller to a MIMO greenhouse environmental model with actuation constraints. This method is based on decoupling the system at low frequency point. The optimal tuning values are determined using genetic algorithms optimization (GA. The inside outsides climate model of the environmental greenhouse, and the automatically collected data sets of Avignon, France are used to simulate and test this technique. The control objective is to maintain a highly coupled inside air temperature and relative humidity of strongly perturbed greenhouse, at specified set-points, by the ventilation/cooling and moisturizing operations.
Machine learning techniques for energy optimization in mobile embedded systems
Donohoo, Brad Kyoshi
Mobile smartphones and other portable battery operated embedded systems (PDAs, tablets) are pervasive computing devices that have emerged in recent years as essential instruments for communication, business, and social interactions. While performance, capabilities, and design are all important considerations when purchasing a mobile device, a long battery lifetime is one of the most desirable attributes. Battery technology and capacity has improved over the years, but it still cannot keep pace with the power consumption demands of today's mobile devices. This key limiter has led to a strong research emphasis on extending battery lifetime by minimizing energy consumption, primarily using software optimizations. This thesis presents two strategies that attempt to optimize mobile device energy consumption with negligible impact on user perception and quality of service (QoS). The first strategy proposes an application and user interaction aware middleware framework that takes advantage of user idle time between interaction events of the foreground application to optimize CPU and screen backlight energy consumption. The framework dynamically classifies mobile device applications based on their received interaction patterns, then invokes a number of different power management algorithms to adjust processor frequency and screen backlight levels accordingly. The second strategy proposes the usage of machine learning techniques to learn a user's mobile device usage pattern pertaining to spatiotemporal and device contexts, and then predict energy-optimal data and location interface configurations. By learning where and when a mobile device user uses certain power-hungry interfaces (3G, WiFi, and GPS), the techniques, which include variants of linear discriminant analysis, linear logistic regression, non-linear logistic regression, and k-nearest neighbor, are able to dynamically turn off unnecessary interfaces at runtime in order to save energy.
Optimal Control of Isometric Muscle Dynamics
Directory of Open Access Journals (Sweden)
Robert Rockenfeller
2015-03-01
Full Text Available We use an indirect optimal control approach to calculate the optimal neural stimulation needed to obtain measured isometric muscle forces. The neural stimulation of the nerve system is hereby considered to be a control function (input of the system ’muscle’ that solely determines the muscle force (output. We use a well-established muscle model and experimental data of isometric contractions. The model consists of coupled activation and contraction dynamics described by ordinary differential equations. To validate our results, we perform a comparison with commercial optimal control software.
Stochastic dynamic programming model for optimal resource ...
Indian Academy of Sciences (India)
M Bhuvaneswari
2018-04-11
Apr 11, 2018 ... containers, doctors, nurses, cash and stocks. Similarly, the uncertainty may have different characterizations in these applications. An approximate stochastic dynamic programming (SDP) [3] allows nodes with a number of possible actions with clear strategies for devising an effective decision on optimal ...
Learning and Anticipation in Online Dynamic Optimization
P.A.N. Bosman (Peter); S. Yang; Y.S. Ong; Y. Jin
2007-01-01
htmlabstractIn this chapter we focus on the importance of the use of learning and anticipation in (online) dynamic optimization. To this end we point out an important source of problem-difficulty that has so far received significantly less attention than the traditional shifting of optima.
Three-dimensional dynamic range reduction techniques
Harding, Kevin G.; Qian, Xiaoping
2004-02-01
A significant limitation of the application of 3D structured light systems has been the large dynamic range of reflectivity of typical parts such as machined parts. The advent of digital cameras have helped this problem to some extent by providing a larger dynamic range of detection, but often parts must still be coated with white paint or powder to get a good enough return for 3D measurement techniques such as structured light. This paper will present an overview of methods that have been used to minimize the range of light reflections from many parts including polarization, multiple exposure, multiple viewing and masking techniques. Also presented will be methods of analysis such as phase analysis techniques which can provide improved robustness. Finally, we will discuss the pros and cons of these options as applied to the application of 3D structured light techniques to machined metal parts.
Optimal BLS: Optimizing transit-signal detection for Keplerian dynamics
Ofir, Aviv
2015-08-01
Transit surveys, both ground- and space-based, have already accumulated a large number of light curves that span several years. We optimize the search for transit signals for both detection and computational efficiencies by assuming that the searched systems can be described by Keplerian, and propagating the effects of different system parameters to the detection parameters. Importnantly, we mainly consider the information content of the transit signal and not any specific algorithm - and use BLS (Kovács, Zucker, & Mazeh 2002) just as a specific example.We show that the frequency information content of the light curve is primarily determined by the duty cycle of the transit signal, and thus the optimal frequency sampling is found to be cubic and not linear. Further optimization is achieved by considering duty-cycle dependent binning of the phased light curve. By using the (standard) BLS, one is either fairly insensitive to long-period planets or less sensitive to short-period planets and computationally slower by a significant factor of ~330 (for a 3 yr long dataset). We also show how the physical system parameters, such as the host star's size and mass, directly affect transit detection. This understanding can then be used to optimize the search for every star individually.By considering Keplerian dynamics explicitly rather than implicitly one can optimally search the transit signal parameter space. The presented Optimal BLS enhances the detectability of both very short and very long period planets, while allowing such searches to be done with much reduced resources and time. The Matlab/Octave source code for Optimal BLS is made available.
Shape optimization for maximum stability and dynamic stiffness
Szyszkowski, W.
1990-01-01
Any optimization of structures for maximum stability or for maximum dynamic stiffness deals with an eigenvalue problem. The goal of this optimization is to raise the lowest eigenvalue (or eigenvalues) of the problem to its highest (optimal) level at a constant volume of the structure. Likely the lowest eigenvalue may be either inherently multi-modal or it can become multi-modal as a result of the optimization process. The multimodeness introduces some ambiguity to the eigenvalue problem and make the optimization difficult to handle. Thus far, only the simplest cases of multi-modal structures have been effectively optimized using rather elaborate analytical methods. Numerous publications report design of a minimum volume structure with different eigenvalues constraints, in which, however, the modality of the problem is assumed a priori. The method presented here utilizes a multi-modal optimality criteria and allows for inclusion of an arbitrary number of buckling or vibrations modes which might influence the optimization process. The real multi-modality of the problem, that is the number of modes participating in the final optimal design is determined iteratively. Because of a natural use of the FEM technique the method is easy to program and might be helpful in design of large flexible space structures.
Advanced Aerostructural Optimization Techniques for Aircraft Design
Directory of Open Access Journals (Sweden)
Yingtao Zuo
2015-01-01
Full Text Available Traditional coupled aerostructural design optimization (ASDO of aircraft based on high-fidelity models is computationally expensive and inefficient. To improve the efficiency, the key is to predict aerostructural performance of the aircraft efficiently. The cruise shape of the aircraft is parameterized and optimized in this paper, and a methodology named reverse iteration of structural model (RISM is adopted to get the aerostructural performance of cruise shape efficiently. A new mathematical explanation of RISM is presented in this paper. The efficiency of RISM can be improved by four times compared with traditional static aeroelastic analysis. General purpose computing on graphical processing units (GPGPU is adopted to accelerate the RISM further, and GPU-accelerated RISM is constructed. The efficiency of GPU-accelerated RISM can be raised by about 239 times compared with that of the loosely coupled aeroelastic analysis. Test shows that the fidelity of GPU-accelerated RISM is high enough for optimization. Optimization framework based on Kriging model is constructed. The efficiency of the proposed optimization system can be improved greatly with the aid of GPU-accelerated RISM. An unmanned aerial vehicle (UAV is optimized using this framework and the range is improved by 4.67% after optimization, which shows effectiveness and efficiency of this framework.
Pareto optimization in algebraic dynamic programming.
Saule, Cédric; Giegerich, Robert
2015-01-01
Pareto optimization combines independent objectives by computing the Pareto front of its search space, defined as the set of all solutions for which no other candidate solution scores better under all objectives. This gives, in a precise sense, better information than an artificial amalgamation of different scores into a single objective, but is more costly to compute. Pareto optimization naturally occurs with genetic algorithms, albeit in a heuristic fashion. Non-heuristic Pareto optimization so far has been used only with a few applications in bioinformatics. We study exact Pareto optimization for two objectives in a dynamic programming framework. We define a binary Pareto product operator [Formula: see text] on arbitrary scoring schemes. Independent of a particular algorithm, we prove that for two scoring schemes A and B used in dynamic programming, the scoring scheme [Formula: see text] correctly performs Pareto optimization over the same search space. We study different implementations of the Pareto operator with respect to their asymptotic and empirical efficiency. Without artificial amalgamation of objectives, and with no heuristics involved, Pareto optimization is faster than computing the same number of answers separately for each objective. For RNA structure prediction under the minimum free energy versus the maximum expected accuracy model, we show that the empirical size of the Pareto front remains within reasonable bounds. Pareto optimization lends itself to the comparative investigation of the behavior of two alternative scoring schemes for the same purpose. For the above scoring schemes, we observe that the Pareto front can be seen as a composition of a few macrostates, each consisting of several microstates that differ in the same limited way. We also study the relationship between abstract shape analysis and the Pareto front, and find that they extract information of a different nature from the folding space and can be meaningfully combined.
Sreekanta Murthy, T.
1992-01-01
Results of the investigation of formal nonlinear programming-based numerical optimization techniques of helicopter airframe vibration reduction are summarized. The objective and constraint function and the sensitivity expressions used in the formulation of airframe vibration optimization problems are presented and discussed. Implementation of a new computational procedure based on MSC/NASTRAN and CONMIN in a computer program system called DYNOPT for optimizing airframes subject to strength, frequency, dynamic response, and dynamic stress constraints is described. An optimization methodology is proposed which is thought to provide a new way of applying formal optimization techniques during the various phases of the airframe design process. Numerical results obtained from the application of the DYNOPT optimization code to a helicopter airframe are discussed.
Optimization techniques using MODFLOW-GWM
Grava, Anna; Feinstein, Daniel T.; Barlow, Paul M.; Bonomi, Tullia; Buarne, Fabiola; Dunning, Charles; Hunt, Randall J.
2015-01-01
An important application of optimization codes such as MODFLOW-GWM is to maximize water supply from unconfined aquifers subject to constraints involving surface-water depletion and drawdown. In optimizing pumping for a fish hatchery in a bedrock aquifer system overlain by glacial deposits in eastern Wisconsin, various features of the GWM-2000 code were used to overcome difficulties associated with: 1) Non-linear response matrices caused by unconfined conditions and head-dependent boundaries; 2) Efficient selection of candidate well and drawdown constraint locations; and 3) Optimizing against water-level constraints inside pumping wells. Features of GWM-2000 were harnessed to test the effects of systematically varying the decision variables and constraints on the optimized solution for managing withdrawals. An important lesson of the procedure, similar to lessons learned in model calibration, is that the optimized outcome is non-unique, and depends on a range of choices open to the user. The modeler must balance the complexity of the numerical flow model used to represent the groundwater-flow system against the range of options (decision variables, objective functions, constraints) available for optimizing the model.
Markdown Optimization via Approximate Dynamic Programming
Directory of Open Access Journals (Sweden)
Cos?gun
2013-02-01
Full Text Available We consider the markdown optimization problem faced by the leading apparel retail chain. Because of substitution among products the markdown policy of one product affects the sales of other products. Therefore, markdown policies for product groups having a significant crossprice elasticity among each other should be jointly determined. Since the state space of the problem is very huge, we use Approximate Dynamic Programming. Finally, we provide insights on the behavior of how each product price affects the markdown policy.
National Research Council Canada - National Science Library
Berns, Eric
2002-01-01
The technical objectives of this study are to determine optimum techniques for a flat-panel Cesium- iodide silicon-diode full-field digital mammography system and to compare those optimized techniques...
National Research Council Canada - National Science Library
Berns, Eric
2001-01-01
The technical objectives of this study are to determine optimum techniques for a flat-panel Cesium-iodide silicon-diode full-field digital mammography system and to compare those optimized techniques...
Airfoil shape optimization using non-traditional optimization technique and its validation
Directory of Open Access Journals (Sweden)
R. Mukesh
2014-07-01
Full Text Available Computational fluid dynamics (CFD is one of the computer-based solution methods which is more widely employed in aerospace engineering. The computational power and time required to carry out the analysis increase as the fidelity of the analysis increases. Aerodynamic shape optimization has become a vital part of aircraft design in the recent years. Generally if we want to optimize an airfoil we have to describe the airfoil and for that, we need to have at least hundred points of x and y co-ordinates. It is really difficult to optimize airfoils with this large number of co-ordinates. Nowadays many different schemes of parameter sets are used to describe general airfoil such as B-spline, and PARSEC. The main goal of these parameterization schemes is to reduce the number of needed parameters as few as possible while controlling the important aerodynamic features effectively. Here the work has been done on the PARSEC geometry representation method. The objective of this work is to introduce the knowledge of describing general airfoil using twelve parameters by representing its shape as a polynomial function. And also we have introduced the concept of Genetic Algorithm to optimize the aerodynamic characteristics of a general airfoil for specific conditions. A MATLAB program has been developed to implement PARSEC, Panel Technique, and Genetic Algorithm. This program has been tested for a standard NACA 2411 airfoil and optimized to improve its coefficient of lift. Pressure distribution and co-efficient of lift for airfoil geometries have been calculated using the Panel method. The optimized airfoil has improved co-efficient of lift compared to the original one. The optimized airfoil is validated using wind tunnel data.
Power system design optimization using Lagrange multiplier techniques
Yu, Y.; Lee, F. C.
1981-01-01
An optimization technique using the Lagrange Multiplier Method is proposed to facilitate design of switching power converter systems. The essence of the optimization is to identify the optimal battery voltage level and switching frequency along with the detailed converter design so that the total system weight including the battery and the packaged converter is minimized, and concurrently all specified power circuit performances are satisfied.
9th International Conference on Optimization : Techniques and Applications
Wang, Song; Wu, Soon-Yi
2015-01-01
This book presents the latest research findings and state-of-the-art solutions on optimization techniques and provides new research direction and developments. Both the theoretical and practical aspects of the book will be much beneficial to experts and students in optimization and operation research community. It selects high quality papers from The International Conference on Optimization: Techniques and Applications (ICOTA2013). The conference is an official conference series of POP (The Pacific Optimization Research Activity Group; there are over 500 active members). These state-of-the-art works in this book authored by recognized experts will make contributions to the development of optimization with its applications.
Query Optimization Techniques in Microsoft SQL Server
Directory of Open Access Journals (Sweden)
Costel Gabriel CORLATAN
2014-09-01
Full Text Available Microsoft SQL Server is a relational database management system, having MS-SQL and Transact-SQL as primary structured programming languages. They rely on relational algebra which is mainly used for data insertion, modifying, deletion and retrieval, as well as for data access controlling. The problem with getting the expected results is handled by the management system which has the purpose of finding the best execution plan, this process being called optimization. The most frequently used queries are those of data retrieval through SELECT command. We have to take into consideration that not only the select queries need optimization, but also other objects, such as: index, view or statistics.
Polyhredral techniques in combinatorial optimization I: theory
Aardal, K.; Hoesel, S. van
1995-01-01
Combinatorial optimization problems appear in many disciplines ranging from management and logistics to mathematics, physics, and chemistry. These problems are usually relatively easy to formulate mathematically, but most of them are computationally hard due to the restriction that a subset of
Computational optimization techniques applied to microgrids planning
DEFF Research Database (Denmark)
Gamarra, Carlos; Guerrero, Josep M.
2015-01-01
), their planning process must be addressed to economic feasibility, as a long-term stability guarantee. Planning a microgrid is a complex process due to existing alternatives, goals, constraints and uncertainties. Usually planning goals conflict each other and, as a consequence, different optimization problems...
Optimization of Technique Factors for Conventional Mammography
National Research Council Canada - National Science Library
Hendrick, R
1997-01-01
.... Methods of evaluating film, processing, and technique factor selection for screen-film mammography were applied to approximately one dozen clinical sites involved in the Colorado Mammography Advocacy Project (CMAP...
Kleijnen, J.P.C.
1995-01-01
This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for
Simple techniques for optimal smile modification.
Romano, Rafi
2008-05-01
Orthodontics is no longer a treatment modality for moderate or severe malocclusion. Patients of all age groups seek help in tooth repositioning. Esthetic demands are extremely high and clinicians need to be more creative and more open to alternative techniques that will suit the demand for invisible treatment, at reasonable costs, maximum accuracy, and with relative comfort. A few simple techniques are described for very common orthodontic problems.
Constraint Embedding Technique for Multibody System Dynamics
Woo, Simon S.; Cheng, Michael K.
2011-01-01
Multibody dynamics play a critical role in simulation testbeds for space missions. There has been a considerable interest in the development of efficient computational algorithms for solving the dynamics of multibody systems. Mass matrix factorization and inversion techniques and the O(N) class of forward dynamics algorithms developed using a spatial operator algebra stand out as important breakthrough on this front. Techniques such as these provide the efficient algorithms and methods for the application and implementation of such multibody dynamics models. However, these methods are limited only to tree-topology multibody systems. Closed-chain topology systems require different techniques that are not as efficient or as broad as those for tree-topology systems. The closed-chain forward dynamics approach consists of treating the closed-chain topology as a tree-topology system subject to additional closure constraints. The resulting forward dynamics solution consists of: (a) ignoring the closure constraints and using the O(N) algorithm to solve for the free unconstrained accelerations for the system; (b) using the tree-topology solution to compute a correction force to enforce the closure constraints; and (c) correcting the unconstrained accelerations with correction accelerations resulting from the correction forces. This constraint-embedding technique shows how to use direct embedding to eliminate local closure-loops in the system and effectively convert the system back to a tree-topology system. At this point, standard tree-topology techniques can be brought to bear on the problem. The approach uses a spatial operator algebra approach to formulating the equations of motion. The operators are block-partitioned around the local body subgroups to convert them into aggregate bodies. Mass matrix operator factorization and inversion techniques are applied to the reformulated tree-topology system. Thus in essence, the new technique allows conversion of a system with
Optimization of multi-response dynamic systems integrating multiple ...
African Journals Online (AJOL)
Optimization of multi-response dynamic systems integrating multiple regression and Taguchi's dynamic signal-to-noise ratio concept. ... Assuming a linear association exists between the response and signal variables, Taguchi offered a two-stage route for optimizing a dynamic system: maximize the dynamic signal-to noise ...
A novel technique for active vibration control, based on optimal
Indian Academy of Sciences (India)
In the last few decades, researchers have proposed many control techniques to suppress unwanted vibrations in a structure. In this work, a novel and simple technique is proposed for the active vibration control. In this technique, an optimal tracking control is employed to suppress vibrations in a structure by simultaneously ...
Dynamic portfolio optimization across hidden market regimes
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2017-01-01
Regime-based asset allocation has been shown to add value over rebalancing to static weights and, in particular, reduce potential drawdowns by reacting to changes in market conditions. The predominant approach in previous studies has been to specify in advance a static decision rule for changing...... the allocation based on the state of financial markets or the economy. In this article, model predictive control (MPC) is used to dynamically optimize a portfolio based on forecasts of the mean and variance of financial returns from a hidden Markov model with time-varying parameters. There are computational...... advantages to using MPC when estimates of future returns are updated every time a new observation becomes available, since the optimal control actions are reconsidered anyway. MPC outperforms a static decision rule for changing the allocation and realizes both a higher return and a significantly lower risk...
optimal assembly line balancing using simulation techniques
African Journals Online (AJOL)
user
The typical problems facing with garment manufacturing are: short product cycle for fashion articles, long production lead time, bottlenecking, and low productivity. To alleviate the problems, different types of line balancing techniques have been used for many years in the garment industry. However, garment industries ...
Complex energy system management using optimization techniques
Energy Technology Data Exchange (ETDEWEB)
Bridgeman, Stuart; Hurdowar-Castro, Diana; Allen, Rick; Olason, Tryggvi; Welt, Francois
2010-09-15
Modern energy systems are often very complex with respect to the mix of generation sources, energy storage, transmission, and avenues to market. Historically, power was provided by government organizations to load centers, and pricing was provided in a regulatory manner. In recent years, this process has been displaced by the independent system operator (ISO). This complexity makes the operation of these systems very difficult, since the components of the system are interdependent. Consequently, computer-based large-scale simulation and optimization methods like Decision Support Systems are now being used. This paper discusses the application of a DSS to operations and planning systems.
Optimized Bayesian dynamic advising theory and algorithms
Karny, Miroslav
2006-01-01
Written by one of the world's leading groups in the area of Bayesian identification, control, and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. Starting from abstract ideas and formulations, and culminating in detailed algorithms, the book comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modelling by dynamic mixture models
Optimal dynamic remapping of data parallel computations
Nicol, David M.; Reynolds, Paul F., Jr.
1990-01-01
A large class of data parallel computations is characterized by a sequence of phases, with phase changes occurring unpredictably. Dynamic remapping of the workload to processors may be required to maintain good performance. The problem considered, for which the utility of remapping and the future behavior of the workload are uncertain, arises when phases exhibit stable execution requirements during a given phase, but requirements change radically between phases. For these situations, a workload assignment generated for one phase may hinder performance during the next phase. This problem is treated formally for a probabilistic model of computation with at most two phases. The authors address the fundamental problem of balancing the expected remapping performance gain against the delay cost, and they derive the optimal remapping decision policy. The promise of the approach is shown by application to multiprocessor implementations of an adaptive gridding fluid dynamics program and to a battlefield simulation program.
A Monarch Butterfly Optimization for the Dynamic Vehicle Routing Problem
Directory of Open Access Journals (Sweden)
Shifeng Chen
2017-09-01
Full Text Available The dynamic vehicle routing problem (DVRP is a variant of the Vehicle Routing Problem (VRP in which customers appear dynamically. The objective is to determine a set of routes that minimizes the total travel distance. In this paper, we propose a monarch butterfly optimization (MBO algorithm to solve DVRPs, utilizing a greedy strategy. Both migration operation and the butterfly adjusting operator only accept the offspring of butterfly individuals that have better fitness than their parents. To improve performance, a later perturbation procedure is implemented, to maintain a balance between global diversification and local intensification. The computational results indicate that the proposed technique outperforms the existing approaches in the literature for average performance by at least 9.38%. In addition, 12 new best solutions were found. This shows that this proposed technique consistently produces high-quality solutions and outperforms other published heuristics for the DVRP.
Hybrid Techniques for Optimizing Complex Systems
2009-12-01
probabilistic faults is fundamentally different from existing testing techniques. Probabilistic testing requires a multiset (a set with repetitions) of test...vector sensitivity information computed in the previous section to generate compact multisets of test vectors for detecting transient faults. Test...testing for soft errors, tests may have to be repeated to increase the probability of fault detection, therefore multisets of tests are selected
Advanced memory optimization techniques for low-power embedded processors
Verma, Manish
2007-01-01
The complete application, including data variables and code segments, is optimizedComprehensive architecture-level exploration for real-life applicationsDemonstration of architecture-aware compilation techniques.
Acceleration techniques in the univariate Lipschitz global optimization
Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.; De Franco, Angela
2016-10-01
Univariate box-constrained Lipschitz global optimization problems are considered in this contribution. Geometric and information statistical approaches are presented. The novel powerful local tuning and local improvement techniques are described in the contribution as well as the traditional ways to estimate the Lipschitz constant. The advantages of the presented local tuning and local improvement techniques are demonstrated using the operational characteristics approach for comparing deterministic global optimization algorithms on the class of 100 widely used test functions.
A GIS-Based Optimization Technique for Spatial Location of ...
African Journals Online (AJOL)
GIS)-based package; TransCAD v. 5.0 was used to determine the optimal locations of one to ten waste bins. This optimization technique requires less computational time and the output of ten computer runs showed that partial service coverage ...
Manifold mapping: a two-level optimization technique
Echeverría, D.; Hemker, P.W.
2008-01-01
In this paper, we analyze in some detail the manifold-mapping optimization technique introduced recently [Echeverría and Hemker in space mapping and defect correction. Comput Methods Appl Math 5(2): 107--136, 2005]. Manifold mapping aims at accelerating optimal design procedures that otherwise
Manifold mapping: a two-level optimization technique
D. Echeverria (David); P.W. Hemker (Piet)
2008-01-01
textabstractIn this paper, we analyze in some detail the manifold-mapping optimization technique introduced recently [Echeverría and Hemker in space mapping and defect correction. Comput Methods Appl Math 5(2): 107-–136, 2005]. Manifold mapping aims at accelerating optimal design procedures
COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U
Energy Technology Data Exchange (ETDEWEB)
Sun, Y.; Borland, Michael
2017-06-25
Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.
Morphing-Based Shape Optimization in Computational Fluid Dynamics
Rousseau, Yannick; Men'Shov, Igor; Nakamura, Yoshiaki
In this paper, a Morphing-based Shape Optimization (MbSO) technique is presented for solving Optimum-Shape Design (OSD) problems in Computational Fluid Dynamics (CFD). The proposed method couples Free-Form Deformation (FFD) and Evolutionary Computation, and, as its name suggests, relies on the morphing of shape and computational domain, rather than direct shape parameterization. Advantages of the FFD approach compared to traditional parameterization are first discussed. Then, examples of shape and grid deformations by FFD are presented. Finally, the MbSO approach is illustrated and applied through an example: the design of an airfoil for a future Mars exploration airplane.
Optimization using surrogate models - by the space mapping technique
DEFF Research Database (Denmark)
Søndergaard, Jacob
2003-01-01
Surrogate modelling and optimization techniques are intended for engineering design in the case where an expensive physical model is involved. This thesis provides a literature overview of the field of surrogate modelling and optimization. The space mapping technique is one such method for constr......Surrogate modelling and optimization techniques are intended for engineering design in the case where an expensive physical model is involved. This thesis provides a literature overview of the field of surrogate modelling and optimization. The space mapping technique is one such method...... conditions are satisfied. So hybrid methods, combining the space mapping technique with classical optimization methods, should be used if convergence to high accuracy is wanted. Approximation abilities of the space mapping surrogate are compared with those of a Taylor model of the expensive model. The space...... mapping surrogate has a lower approximation error for long steps. For short steps, however, the Taylor model of the expensive model is best, due to exact interpolation at the model origin. Five algorithms for space mapping optimization are presented and the numerical performance is evaluated. Three...
Tabu search, a versatile technique for the functions optimization
International Nuclear Information System (INIS)
Castillo M, J.A.
2003-01-01
The basic elements of the Tabu search technique are presented, putting emphasis in the qualities that it has in comparison with the traditional methods of optimization known as in descending pass. Later on some modifications are sketched that have been implemented in the technique along the time, so that this it is but robust. Finally they are given to know some areas where this technique has been applied, obtaining successful results. (Author)
OPTIMIZATION OF GRANULATION TECHNIQUES FOR DEVELOPMENT OF TABLET DOSAGE FORM
V. B. Khot*, D.A. Bhagwat, J. I. D'Souza, S. S. Shelake, S. V. Patil
2017-01-01
The purpose of this study was to optimize the best granulation techniques for development of tablet dosage form. The present study explains comparative study of different wet granulation techniques including Planetary mixer granulation, Rapid mixer granulation, Fluid bed granulation with Direct compression method. Similar formulations were used to evaluate Planetary mixer granulation, Rapid mixer granulation and Fluid bed granulation method. The granules prepared by different techniques were ...
Viscosity measurement techniques in Dissipative Particle Dynamics
Boromand, Arman; Jamali, Safa; Maia, Joao M.
2015-11-01
In this study two main groups of viscosity measurement techniques are used to measure the viscosity of a simple fluid using Dissipative Particle Dynamics, DPD. In the first method, a microscopic definition of the pressure tensor is used in equilibrium and out of equilibrium to measure the zero-shear viscosity and shear viscosity, respectively. In the second method, a periodic Poiseuille flow and start-up transient shear flow is used and the shear viscosity is obtained from the velocity profiles by a numerical fitting procedure. Using the standard Lees-Edward boundary condition for DPD will result in incorrect velocity profiles at high values of the dissipative parameter. Although this issue was partially addressed in Chatterjee (2007), in this work we present further modifications (Lagrangian approach) to the original LE boundary condition (Eulerian approach) that will fix the deviation from the desired shear rate at high values of the dissipative parameter and decrease the noise to signal ratios in stress measurement while increases the accessible low shear rate window. Also, the thermostat effect of the dissipative and random forces is coupled to the dynamic response of the system and affects the transport properties like the viscosity and diffusion coefficient. We investigated thoroughly the dependency of viscosity measured by both Eulerian and Lagrangian methodologies, as well as numerical fitting procedures and found that all the methods are in quantitative agreement.
A Modified Particle Swarm Optimization Technique for Finding Optimal Designs for Mixture Models
Wong, Weng Kee; Chen, Ray-Bing; Huang, Chien-Chih; Wang, Weichung
2015-01-01
Particle Swarm Optimization (PSO) is a meta-heuristic algorithm that has been shown to be successful in solving a wide variety of real and complicated optimization problems in engineering and computer science. This paper introduces a projection based PSO technique, named ProjPSO, to efficiently find different types of optimal designs, or nearly optimal designs, for mixture models with and without constraints on the components, and also for related models, like the log contrast models. We also compare the modified PSO performance with Fedorov's algorithm, a popular algorithm used to generate optimal designs, Cocktail algorithm, and the recent algorithm proposed by [1]. PMID:26091237
Hip joint contact forces calculated using different muscle optimization techniques
Wesseling, M.; Derikx, L.C.; de Groote, F.; Bartels, W.; Meyer, C.; Verdonschot, Nicolaas Jacobus Joseph; Jonkers, I.
2013-01-01
The goal of this study was to calculate muscle forces using different optimization techniques and investigate their effect on hip joint contact forces in gait and sit to stand. These contact forces were compared to measured hip contact forces [3]. The results showed that contact forces were overestimated, especially when muscle forces were calculated using computed muscle control. For static optimization, results were closest to measured contact forces. Also, differences between measured and ...
Chaotic dynamics in optimal monetary policy
Gomes, O.; Mendes, V. M.; Mendes, D. A.; Sousa Ramos, J.
2007-05-01
There is by now a large consensus in modern monetary policy. This consensus has been built upon a dynamic general equilibrium model of optimal monetary policy as developed by, e.g., Goodfriend and King [ NBER Macroeconomics Annual 1997 edited by B. Bernanke and J. Rotemberg (Cambridge, Mass.: MIT Press, 1997), pp. 231 282], Clarida et al. [J. Econ. Lit. 37, 1661 (1999)], Svensson [J. Mon. Econ. 43, 607 (1999)] and Woodford [ Interest and Prices: Foundations of a Theory of Monetary Policy (Princeton, New Jersey, Princeton University Press, 2003)]. In this paper we extend the standard optimal monetary policy model by introducing nonlinearity into the Phillips curve. Under the specific form of nonlinearity proposed in our paper (which allows for convexity and concavity and secures closed form solutions), we show that the introduction of a nonlinear Phillips curve into the structure of the standard model in a discrete time and deterministic framework produces radical changes to the major conclusions regarding stability and the efficiency of monetary policy. We emphasize the following main results: (i) instead of a unique fixed point we end up with multiple equilibria; (ii) instead of saddle-path stability, for different sets of parameter values we may have saddle stability, totally unstable equilibria and chaotic attractors; (iii) for certain degrees of convexity and/or concavity of the Phillips curve, where endogenous fluctuations arise, one is able to encounter various results that seem intuitively correct. Firstly, when the Central Bank pays attention essentially to inflation targeting, the inflation rate has a lower mean and is less volatile; secondly, when the degree of price stickiness is high, the inflation rate displays a larger mean and higher volatility (but this is sensitive to the values given to the parameters of the model); and thirdly, the higher the target value of the output gap chosen by the Central Bank, the higher is the inflation rate and its
Operation optimization of distributed generation using artificial intelligent techniques
Directory of Open Access Journals (Sweden)
Mahmoud H. Elkazaz
2016-06-01
Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.
Dynamic optimization the calculus of variations and optimal control in economics and management
Kamien, Morton I
2012-01-01
Since its initial publication, this text has defined courses in dynamic optimization taught to economics and management science students. The two-part treatment covers the calculus of variations and optimal control. 1998 edition.
Information integration and red queen dynamics in coevolutionary optimization
Pagie, L.; Hogeweg, P.
2001-01-01
Abstract- Coevolution has been used as optimization technique both successfully and unsuccessfully. Successful optimization shows integration of information at the individual level over many fitness evaluation events and over many generations. Alternative outcomes of the evolutionary process,
Emerging Dynamic Design Techniques for Mechanical and ...
Indian Academy of Sciences (India)
through this school to bring about an awareness of the state-of-art of the software and hardware in various tools of dynamic design, namely dynamic testing, identification, modi- fication and model updating. Dynamic design aims at obtaining the desired dynamic characteristics in products, equipment, systems and structures ...
Studies Regarding Design and Optimization of Mechanisms Using Modern Techniques of CAD and CAE
Directory of Open Access Journals (Sweden)
Marius Tufoi
2010-01-01
Full Text Available The paper presents applications of modern techniques of CAD (Computer Aided Design and CAE (Computer Aided Engineering to design and optimize the mechanisms used in mechanical engineering. The use exemplification of these techniques was achieved by designing and optimizing parts of a drawing installation for horizontal continuous casting of metals. By applying these design methods and using finite element method at simulations on designed mechanisms results a number of advantages over traditional methods of drawing and design: speed in drawing, design and optimization of parts and mechanisms, kinematic analysis option, kinetostatic and dynamic through simulation, without requiring physical realization of the part or mechanism, the determination by finite element method of tension, elongations, travel and safety factor and the possibility of optimization for these sizes to ensure the mechanical strength of each piece separately. Achieving these studies was possible using SolidWorks 2009 software suite.
An adaptive dual-optimal path-planning technique for unmanned air vehicles
Directory of Open Access Journals (Sweden)
Whitfield Clifford A.
2016-01-01
Full Text Available A multi-objective technique for unmanned air vehicle path-planning generation through task allocation has been developed. The dual-optimal path-planning technique generates real-time adaptive flight paths based on available flight windows and environmental influenced objectives. The environmentally-influenced flight condition determines the aircraft optimal orientation within a downstream virtual window of possible vehicle destinations that is based on the vehicle’s kinematics. The intermittent results are then pursued by a dynamic optimization technique to determine the flight path. This path-planning technique is a multi-objective optimization procedure consisting of two goals that do not require additional information to combine the conflicting objectives into a single-objective. The technique was applied to solar-regenerative high altitude long endurance flight which can benefit significantly from an adaptive real-time path-planning technique. The objectives were to determine the minimum power required flight paths while maintaining maximum solar power for continual surveillance over an area of interest (AOI. The simulated path generation technique prolonged the flight duration over a sustained turn loiter flight path by approximately 2 months for a year of flight. The potential for prolonged solar powered flight was consistent for all latitude locations, including 2 months of available flight at 60° latitude, where sustained turn flight was no longer capable.
Hip joint contact forces calculated using different muscle optimization techniques
Wesseling, M.; Derikx, L.C.; de Groote, F.; Bartels, W.; Meyer, C.; Verdonschot, Nicolaas Jacobus Joseph; Jonkers, I.
2013-01-01
The goal of this study was to calculate muscle forces using different optimization techniques and investigate their effect on hip joint contact forces in gait and sit to stand. These contact forces were compared to measured hip contact forces [3]. The results showed that contact forces were
Techniques applied in design optimization of parallel manipulators
CSIR Research Space (South Africa)
Modungwa, D
2011-11-01
Full Text Available the process of optimization a cumbersome and time-consuming endeavour, especially when the variables are diverse and objective functions are excessively complex. Thus, several techniques devised by researchers to solve the problem are reviewed in this paper....
Optimal control of HIV/AIDS dynamic: Education and treatment
Sule, Amiru; Abdullah, Farah Aini
2014-07-01
A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.
Optimal Design of DC Electromagnets Based on Imposed Dynamic Characteristics
Directory of Open Access Journals (Sweden)
Sergiu Ivas
2016-10-01
Full Text Available In this paper is proposed a method for computing of optimal geometric dimensions of a DC electromagnet, based on the imposed dynamical characteristics. For obtaining the optimal design, it is built the criterion function in an analytic form that may be optimized in the order to find the constructive solution. Numerical simulations performed in Matlab software confirm the proposed work. The presented method can be extended to other electromagnetic devices which frequently operate in dynamic regime.
Investigations of auroral dynamics: techniques and results
International Nuclear Information System (INIS)
Steen, Aa.
1988-10-01
This study is an experimental investigation of the dynamics of the aurora, describing both the systems developed for the optical measurements and the results obtained. It is found that during a auroral arc deformation, a fold travelling eastward along the arc is associated with an enhanced F-region ion temperature of 2700 K, measured by EISCAT, indicative of enhanced ionspheric electric fields. It is shown that for an auroral break-up, the large-scale westward travelling surge (WTS) is the last developed spiral in a sequence of spiral formations. It is proposed that the Kelvin-Helmholtz instability is the responsible process. In another event it is shown that large-amplitude long-lasting pulsations, observed both in ground-based magnetic field and photometer recordings, correspond to strong modulations of the particle intensity at the equatorial orbit (6.6 Re). In this event a gradual transition occurs between pulses classified as Ps6/auroral torches toward pulses with characteristics of substorms. The observations are explained by the Kelvin-Helmholtz instability in a magnetospheric boundary layer. The meridional neutral wind, at about 240 km altitude, is found to be reduced prior to or at the onset of auroral activity. These findings are suggestive of large-scale reconfigurations of the ionspheric electric fields prior to auroral onsets. A new real time triangulation technique developed to determine the altitude of auroral arcs is presented, and an alternative method to analyze incoherent scatter data is discussed. (With 46 refs.) (author)
Yang, Y.; Özgen, S.
2017-06-01
During the last few decades, CFD (Computational Fluid Dynamics) has developed greatly and has become a more reliable tool for the conceptual phase of aircraft design. This tool is generally combined with an optimization algorithm. In the optimization phase, the need for regenerating the computational mesh might become cumbersome, especially when the number of design parameters is high. For this reason, several mesh generation and deformation techniques have been developed in the past decades. One of the most widely used techniques is the Spring Analogy. There are numerous spring analogy related techniques reported in the literature: linear spring analogy, torsional spring analogy, semitorsional spring analogy, and ball vertex spring analogy. This paper gives the explanation of linear spring analogy method and angle inclusion in the spring analogy method. In the latter case, two di¨erent solution methods are proposed. The best feasible method will later be used for two-dimensional (2D) Airfoil Design Optimization with objective function being to minimize sectional drag for a required lift coe©cient at di¨erent speeds. Design variables used in the optimization include camber and thickness distribution of the airfoil. SU2 CFD is chosen as the §ow solver during the optimization procedure. The optimization is done by using Phoenix ModelCenter Optimization Tool.
Dynamic speckle analysis using multivariate techniques
International Nuclear Information System (INIS)
López-Alonso, José M; Alda, Javier; Rabal, Héctor; Grumel, Eduardo; Trivi, Marcelo
2015-01-01
In this work we use principal components analysis to characterize dynamic speckle patterns. This analysis quantitatively identifies different dynamics that could be associated to physical phenomena occurring in the sample. We also found the contribution explained by each principal component, or by a group of them. The method analyzes the paint drying process over a hidden topography. It can be used for fast screening and identification of different dynamics in biological or industrial samples by means of dynamic speckle interferometry. (paper)
Optimal Control Techniques for ResistiveWall Modes in Tokamaks
Clement, Mitchell Dobbs Pearson
Tokamaks can excite kink modes that can lock or nearly lock to the vacuum vessel wall, and whose rotation frequencies and growth rates vary in time but are generally inversely proportional to the magnetic flux diffusion time of the vacuum vessel wall. This magnetohydrodynamic (MHD) instability is pressure limiting in tokamaks and is called the Resistive Wall Mode (RWM). Future tokamaks that are expected to operate as fusion reactors will be required to maximize plasma pressure in order to maximize fusion performance. The DIII-D tokamak is equipped with electromagnetic control coils, both inside and outside of its vacuum vessel, which create magnetic fields that are small by comparison to the machine's equilibrium field but are able to dynamically counteract the RWM. Presently for RWM feedback, DIII-D uses its interior control coils using a classical proportional gain only controller to achieve high plasma pressure. Future advanced tokamak designs will not likely have the luxury of interior control coils and a proportional gain algorithm is not expected to be effective with external control coils. The computer code VALEN was designed to calculate the performance of an MHD feedback control system in an arbitrary geometry. VALEN models the perturbed magnetic field from a single MHD instability and its interaction with surrounding conducting structures using a finite element approach. A linear quadratic gaussian (LQG) control, or H 2 optimal control, algorithm based on the VALEN model for RWM feedback was developed for use with DIII-D's external control coil set. The algorithm is implemented on a platform that combines a graphics processing unit (GPU) for real-time control computation with low latency digital input/output control hardware and operates in parallel with the DIII-D Plasma Control System (PCS). Simulations and experiments showed that modern control techniques performed better, using 77% less current, than classical techniques when using coils external to
An Image Morphing Technique Based on Optimal Mass Preserving Mapping
Zhu, Lei; Yang, Yan; Haker, Steven; Tannenbaum, Allen
2013-01-01
Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The L2 mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods. PMID:17547128
Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles
Morelli, Eugene A.; Klein, Vladislav
1990-01-01
A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.
Optimization of Hydraulic Machinery Bladings by Multilevel CFD Techniques
Directory of Open Access Journals (Sweden)
Thum Susanne
2005-01-01
Full Text Available The numerical design optimization for complex hydraulic machinery bladings requires a high number of design parameters and the use of a precise CFD solver yielding high computational costs. To reduce the CPU time needed, a multilevel CFD method has been developed. First of all, the 3D blade geometry is parametrized by means of a geometric design tool to reduce the number of design parameters. To keep geometric accuracy, a special B-spline modification technique has been developed. On the first optimization level, a quasi-3D Euler code (EQ3D is applied. To guarantee a sufficiently accurate result, the code is calibrated by a Navier-Stokes recalculation of the initial design and can be recalibrated after a number of optimization steps by another Navier-Stokes computation. After having got a convergent solution, the optimization process is repeated on the second level using a full 3D Euler code yielding a more accurate flow prediction. Finally, a 3D Navier-Stokes code is applied on the third level to search for the optimum optimorum by means of a fine-tuning of the geometrical parameters. To show the potential of the developed optimization system, the runner blading of a water turbine having a specific speed n q = 41 1 / min was optimized applying the multilevel approach.
Fitting Nonlinear Curves by use of Optimization Techniques
Hill, Scott A.
2005-01-01
MULTIVAR is a FORTRAN 77 computer program that fits one of the members of a set of six multivariable mathematical models (five of which are nonlinear) to a multivariable set of data. The inputs to MULTIVAR include the data for the independent and dependent variables plus the user s choice of one of the models, one of the three optimization engines, and convergence criteria. By use of the chosen optimization engine, MULTIVAR finds values for the parameters of the chosen model so as to minimize the sum of squares of the residuals. One of the optimization engines implements a routine, developed in 1982, that utilizes the Broydon-Fletcher-Goldfarb-Shanno (BFGS) variable-metric method for unconstrained minimization in conjunction with a one-dimensional search technique that finds the minimum of an unconstrained function by polynomial interpolation and extrapolation without first finding bounds on the solution. The second optimization engine is a faster and more robust commercially available code, denoted Design Optimization Tool, that also uses the BFGS method. The third optimization engine is a robust and relatively fast routine that implements the Levenberg-Marquardt algorithm.
Directory of Open Access Journals (Sweden)
Banaja Mohanty
2016-05-01
Full Text Available DGs are placed for the purpose of real power loss minimization and voltage improvement in distribution network system. This paper presents a recent optimization technique, i.e. teaching learning based optimization (TLBO technique for finding the optimal size and location of Distributed generation (DG in radial distribution system (RDS. The optimal location and size of DG is analyzed considering voltage stability index as an objective function. The superiority of the proposed approach has been shown by comparing the results with GA and PSO methods in RDS. The comparison is done using system performances such as the real power loss and voltage profile of RDS. In this paper, performance analysis is carried out considering IEEE 33 bus and 69 buses as the test system.
Parameters control in GAs for dynamic optimization
Directory of Open Access Journals (Sweden)
Khalid Jebari
2013-02-01
Full Text Available The Control of Genetic Algorithms parameters allows to optimize the search process and improves the performance of the algorithm. Moreover it releases the user to dive into a game process of trial and failure to find the optimal parameters.
The Generalized Direct Optimization Technique for Printed Reflectarrays
DEFF Research Database (Denmark)
Zhou, Min; Sørensen, Stig Busk; Kim, Oleksiy S.
2014-01-01
A generalized direct optimization technique (GDOT) for the design of printed reflectarrays using arbitrarily shaped elements with irregular orientation and position is presented. The GDOT is based on the spectral domain method of moments (SDMoM) assuming local periodicity (LP) and a minimax...... designed: a broadband design, a circularly polarized design using the variable rotation technique, and a design with irregularly positioned array elements. The latter has been manufactured and measured at the DTU-ESA Spherical Near-Field Antenna Test Facility. An very good agreement between simulated...
Material saving by means of CWR technology using optimization techniques
Pérez, Iñaki; Ambrosio, Cristina
2017-10-01
Material saving is currently a must for the forging companies, as material costs sum up to 50% for parts made of steel and up to 90% in other materials like titanium. For long products, cross wedge rolling (CWR) technology can be used to obtain forging preforms with a suitable distribution of the material along its own axis. However, defining the correct preform dimensions is not an easy task and it could need an intensive trial-and-error campaign. To speed up the preform definition, it is necessary to apply optimization techniques on Finite Element Models (FEM) able to reproduce the material behaviour when being rolled. Meta-models Assisted Evolution Strategies (MAES), that combine evolutionary algorithms with Kriging meta-models, are implemented in FORGE® software and they allow reducing optimization computation costs in a relevant way. The paper shows the application of these optimization techniques to the definition of the right preform for a shaft from a vehicle of the agricultural sector. First, the current forging process, based on obtaining the forging preform by means of an open die forging operation, is showed. Then, the CWR preform optimization is developed by using the above mentioned optimization techniques. The objective is to reduce, as much as possible, the initial billet weight, so that a calculation of flash weight reduction due to the use of the proposed preform is stated. Finally, a simulation of CWR process for the defined preform is carried out to check that most common failures (necking, spirals,..) in CWR do not appear in this case.
Bunfield, Dennis H.; Trimble, Darian E.; Fronckowiak, Thomas, Jr.; Ballard, Gary; Morris, Joesph
2008-04-01
AMRDEC has developed and implemented new techniques for rendering real-time 32-bit floating point energy-conserved dynamic scenes using commercial-off-the-shelf (COTS) Personal Computer (PC) based hardware and high performance nVidia Graphics Processing Units (GPU). The AMRDEC IGStudio rendering framework with the real-time Joint Scientific Image Generator (JSIG) core has been integrated into numerous AMRDEC Hardware-in-the-loop (HWIL) facilities, successfully replacing the lower fidelity legacy SGI hardware and software. JSIG uses high dynamic range unnormalized radiometric 32-bit floating point rendering through the use of GPU frame buffer objects (FBOs). A high performance nested zoom anti-aliasing (NZAA) technique was developed to address performance and geometric errors of past zoom anti-aliasing (ZAA) implementations. The NZAA capability for multi-object and occluded object representations includes: cluster ZAA, object ZAA, sub-object ZAA, and point source generation for unresolved objects. This technique has an optimal 128x128 pixel asymmetrical field-of-view zoom. The current NZAA capability supports up to 8 objects in real-time with a near future capability of increasing to a theoretical 128 objects in real-time. JSIG performs other dynamic entity effects which are applied in vertex and fragment shaders. These effects include floating point dynamic signature application, dynamic model ablation heating models, and per-material thermal emissivity rolloff interpolated on a per-pixel zoomed window basis. JSIG additionally performs full scene per-pixel effects in a post render process. These effects include real-time convolutions, optical scene corrections, per-frame calibrations, and energy distribution blur used to compensate for projector element energy limitations.
New electrical stimulation techniques in dynamic myopasty
Zonnevylle, Erik Dirk Hendrik
2002-01-01
It has become common practice in reconstructive surgery to transpose or transplant a variety of autologous tissues to fill defects at a recipient site. Using muscle tissue, it becomes possible to dynamically assist or replace an impaired or lost function. For these procedures the term dynamic
Design Optimization of a Speed Reducer Using Deterministic Techniques
Lin, Ming-Hua; Tsai, Jung-Fa; Hu, Nian-Ze; Chang, Shu-Chuan
2013-01-01
The optimal design problem of minimizing the total weight of a speed reducer under constraints is a generalized geometric programming problem. Since the metaheuristic approaches cannot guarantee to find the global optimum of a generalized geometric programming problem, this paper applies an efficient deterministic approach to globally solve speed reducer design problems. The original problem is converted by variable transformations and piecewise linearization techniques. The reformulated prob...
Novel optimization technique of isolated microgrid with hydrogen energy storage.
Directory of Open Access Journals (Sweden)
Eman Hassan Beshr
Full Text Available This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs, Diesel Generator (DG, a Wind Turbine Generator (WTG, Photovoltaic (PV arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.
Novel optimization technique of isolated microgrid with hydrogen energy storage.
Beshr, Eman Hassan; Abdelghany, Hazem; Eteiba, Mahmoud
2018-01-01
This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm.
Novel optimization technique of isolated microgrid with hydrogen energy storage
Abdelghany, Hazem; Eteiba, Mahmoud
2018-01-01
This paper presents a novel optimization technique for energy management studies of an isolated microgrid. The system is supplied by various Distributed Energy Resources (DERs), Diesel Generator (DG), a Wind Turbine Generator (WTG), Photovoltaic (PV) arrays and supported by fuel cell/electrolyzer Hydrogen storage system for short term storage. Multi-objective optimization is used through non-dominated sorting genetic algorithm to suit the load requirements under the given constraints. A novel multi-objective flower pollination algorithm is utilized to check the results. The Pros and cons of the two optimization techniques are compared and evaluated. An isolated microgrid is modelled using MATLAB software package, dispatch of active/reactive power, optimal load flow analysis with slack bus selection are carried out to be able to minimize fuel cost and line losses under realistic constraints. The performance of the system is studied and analyzed during both summer and winter conditions and three case studies are presented for each condition. The modified IEEE 15 bus system is used to validate the proposed algorithm. PMID:29466433
Dynamic systems of regional economy management optimization
Trofimov, S.; Kudzh, S.
directions of an industrial policy of region. The situational-analytical centers (SAC) of regional administration The major component of SAC is dynamic modeling, analysis, forecasting and optimization systems, based on modern intellectual information technologies. Spheres of SAC are not only financial streams management and investments optimization, but also strategic forecasting functions, which provide an optimum choice, "aiming", search of optimum ways of regional development and corresponding investments. It is expedient to consider an opportunity of formation of the uniform organizational-methodical center of an industrial policy of region. This organization can be directly connected to the scheduled-analytical services of the largest economic structures, local authorities, the ministries and departments. Such "direct communication" is capable to provide an effective regional development strategic management. Anyway, the output on foreign markets demands concentration of resources and support of authorities. Offered measures are capable to provide a necessary coordination of efforts of a various level economic structures. For maintenance of a regional industrial policy an attraction of all newest methods of strategic planning and management is necessary. Their activity should be constructed on the basis of modern approaches of economic systems management, cause the essence of an industrial policy is finally reduced to an effective regional and corporate economic activities control centers formation. Opportunities of optimum regional economy planning and management as uniform system Approaches to planning regional economic systems can be different. We will consider some most effective methods of planning and control over a regional facilities condition. All of them are compact and evident, that allows to put them into the group of average complexity technologies. At the decision of problems of a regional resource management is rather perspective the so
Screening technique for loading pattern optimization by simulated annealing
International Nuclear Information System (INIS)
Park, Tong Kyu; Kim, Chang Hyo; Lee, Hyun Chul; Joo, Hyung Kook
2005-01-01
Lots of efforts have been devoted to developing the fuel assembly (FA) loading pattern (LP) optimization code using various optimization algorithms. Among them the simulated annealing (SA) algorithm appears very promising because of its robustness in the optimization calculations. However, SA algorithm has a major drawback of long computing time because it requires the neutronics evaluation of several tens of thousands of the trial LPs in the course of the optimization. In order to reduce computing time, a simple two-dimensional (2D) neutronics evaluation model has been used. Unfortunately, however, the final LP obtained from the 2D SA calculation often turns out to be unsatisfactory when it was evaluated by 3D neutronics evaluation model. A simple and straightforward way of resolving this problem would be to adopt 3D evaluation model instead of 2D model during the optimization procedure but this would take a long computing time. In this paper we propose a screening technique based on 2D evaluation model aimed at reducing computing time in SA calculation with 3D neutronics evaluation model
Directory of Open Access Journals (Sweden)
Weixing Su
2017-03-01
Full Text Available There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases. This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment. This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff. The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell’s pattern search method, life-cycle, and crossover-based social learning strategy. The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks. Furthermore, the proposed algorithm is applied to a real-world application of dynamic RFID network optimization. Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.
An Optimization Framework for Dynamic, Distributed Real-Time Systems
Eckert, Klaus; Juedes, David; Welch, Lonnie; Chelberg, David; Bruggerman, Carl; Drews, Frank; Fleeman, David; Parrott, David; Pfarr, Barbara
2003-01-01
Abstract. This paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems .that operate in dynamic environments. Interesting aspects of the model include dynamic environments, utility and service levels, which provide a means for graceful degradation in resource-constrained situations and support optimization of the allocation of resources. The paper also provides an allocation algorithm that illustrates how to use the model for producing feasible, optimal resource allocations.
First principles molecular dynamics without self-consistent field optimization
International Nuclear Information System (INIS)
Souvatzis, Petros; Niklasson, Anders M. N.
2014-01-01
We present a first principles molecular dynamics approach that is based on time-reversible extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The optimization-free dynamics keeps the computational cost to a minimum and typically provides molecular trajectories that closely follow the exact Born-Oppenheimer potential energy surface. Only one single diagonalization and Hamiltonian (or Fockian) construction are required in each integration time step. The proposed dynamics is derived for a general free-energy potential surface valid at finite electronic temperatures within hybrid density functional theory. Even in the event of irregular functional behavior that may cause a dynamical instability, the optimization-free limit represents a natural starting guess for force calculations that may require a more elaborate iterative electronic ground state optimization. Our optimization-free dynamics thus represents a flexible theoretical framework for a broad and general class of ab initio molecular dynamics simulations
Optimal Operation of Radial Distribution Systems Using Extended Dynamic Programming
DEFF Research Database (Denmark)
Lopez, Juan Camilo; Vergara, Pedro P.; Lyra, Christiano
2018-01-01
An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation...... approach is illustrated using real-scale systems and comparisons with commercial programming solvers. Finally, generalizations to consider other EDS operation problems are also discussed....
Review of dynamic optimization methods in renewable natural resource management
Williams, B.K.
1989-01-01
In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. The applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.
Optimized dynamical control of state transfer through noisy spin chains
Zwick, Analia; Álvarez, Gonzalo A.; Bensky, Guy; Kurizki, Gershon
2014-06-01
We propose a method of optimally controlling the tradeoff of speed and fidelity of state transfer through a noisy quantum channel (spin-chain). This process is treated as qubit state-transfer through a fermionic bath. We show that dynamical modulation of the boundary-qubits levels can ensure state transfer with the best tradeoff of speed and fidelity. This is achievable by dynamically optimizing the transmission spectrum of the channel. The resulting optimal control is robust against both static and fluctuating noise in the channel's spin-spin couplings. It may also facilitate transfer in the presence of diagonal disorder (on site energy noise) in the channel.
Notes on Static and Dynamic Optimization
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui
1981-01-01
This book pretends to be a unified presentation of the main theoretical and numerical results on optimization, and at the same time it provides an outlook to the many areas of application. It contains what I believe is the minimum knowledge required for a serious use of normative mathematical mod...
Structural optimization for nonlinear dynamic response
DEFF Research Database (Denmark)
Dou, Suguang; Strachan, B. Scott; Shaw, Steven W.
2015-01-01
resonant behaviour is being used for a variety of applications in sensing and signal conditioning. In this work, we describe a computational method that provides a systematic means for manipulating and optimizing features of nonlinear resonant responses of mechanical structures that are described...
Optimization Techniques for 3D Graphics Deployment on Mobile Devices
Koskela, Timo; Vatjus-Anttila, Jarkko
2015-03-01
3D Internet technologies are becoming essential enablers in many application areas including games, education, collaboration, navigation and social networking. The use of 3D Internet applications with mobile devices provides location-independent access and richer use context, but also performance issues. Therefore, one of the important challenges facing 3D Internet applications is the deployment of 3D graphics on mobile devices. In this article, we present an extensive survey on optimization techniques for 3D graphics deployment on mobile devices and qualitatively analyze the applicability of each technique from the standpoints of visual quality, performance and energy consumption. The analysis focuses on optimization techniques related to data-driven 3D graphics deployment, because it supports off-line use, multi-user interaction, user-created 3D graphics and creation of arbitrary 3D graphics. The outcome of the analysis facilitates the development and deployment of 3D Internet applications on mobile devices and provides guidelines for future research.
Dynamic Programming Strategies on the Decision Tree Hidden behind the Optimizing Problems
Zoltan KATAI
2007-01-01
The aim of the paper is to present the characteristics of certain dynamic programming strategies on the decision tree hidden behind the optimizing problems and thus to offer such a clear tool for their study and classification which can help in the comprehension of the essence of this programming technique.
Optimal control of molecular motion expressed through quantum fluid dynamics
Dey, Bijoy K.; Rabitz, Herschel; Askar, Attila
2000-04-01
A quantum fluid-dynamic (QFD) control formulation is presented for optimally manipulating atomic and molecular systems. In QFD the control quantum system is expressed in terms of the probability density ρ and the quantum current j. This choice of variables is motivated by the generally expected slowly varying spatial-temporal dependence of the fluid-dynamical variables. The QFD approach is illustrated for manipulation of the ground electronic state dynamics of HCl induced by an external electric field.
Evaluating Dynamic Analysis Techniques for Program Comprehension
Cornelissen, S.G.M.
2009-01-01
Program comprehension is an essential part of software development and software maintenance, as software must be sufficiently understood before it can be properly modified. One of the common approaches in getting to understand a program is the study of its execution, also known as dynamic analysis.
Bridging developmental systems theory and evolutionary psychology using dynamic optimization.
Frankenhuis, Willem E; Panchanathan, Karthik; Clark Barrett, H
2013-07-01
Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists' focus on dynamics and contingency with the 'design stance' of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach. © 2013 Blackwell Publishing Ltd.
Optimizing Technology-Oriented Constructional Paramour's of complex dynamic systems
International Nuclear Information System (INIS)
Novak, S.M.
1998-01-01
Creating optimal vibro systems requires sequential solving of a few problems: selecting the basic pattern of dynamic actions, synthesizing the dynamic active systems, optimizing technological, technical, economic and design parameters. This approach is illustrated by an example of a high-efficiency vibro system synthesized for forming building structure components. When using only one single source to excite oscillations, resonance oscillations are imparted to the product to be formed in the horizontal and vertical planes. In order to obtain versatile and dynamically optimized parameters, a factor is introduced into the differential equations of the motion, accounting for the relationship between the parameters, which determine the frequency characteristics of the system and the parameter variation range. This results in obtaining non-sophisticated mathematical models of the system under investigation, convenient for optimization and for engineering design and calculations as well
Gradient-based optimization in nonlinear structural dynamics
DEFF Research Database (Denmark)
Dou, Suguang
, frequency stabilization, and disk resonator gyroscope. For advanced design of these structures, it is of considerable value to extend current optimization in linear structural dynamics into nonlinear structural dynamics. In this thesis, we present a framework for modelling, analysis, characterization......The intrinsic nonlinearity of mechanical structures can give rise to rich nonlinear dynamics. Recently, nonlinear dynamics of micro-mechanical structures have contributed to developing new Micro-Electro-Mechanical Systems (MEMS), for example, atomic force microscope, passive frequency divider...... coefficients are calculated directly from a nonlinear finite element model. Based on the analysis and the characterization, a new class of optimization problems is studied. In the optimization, design sensitivity analysis is performed by using the adjoint method which is suitable for large-scale structural...
Optimal Portfolios Under Dynamic Shortfall Constraints | Akume ...
African Journals Online (AJOL)
industry standard with regulatory authorities enforcing its use in risk measurement and management. Despite its widespread acceptance, VaR is not coherent. Tail Conditional Expectation (TCE), on the other hand, for an underlying continuous distribution, is a coherent risk measures. Our focus in this paper is the dynamic ...
Optimal Portfolios Under Dynamic Shortfall Constraints
African Journals Online (AJOL)
industry standard with regulatory authorities enforcing its use in risk measure- ment and management. Despite its widespread acceptance, VaR is not coherent. Tail Conditional Expectation (TCE), on the other hand, for an underlying con- tinuous distribution, is a coherent risk measures. Our focus in this paper is the dynamic ...
Dynamic Network Formation Using Ant Colony Optimization
2009-03-01
Problem (DVRP) ............................................ 36 2.7.2 Dynamic Traveling Salesman Problem (DTSP) ....................................... 41...47 2.8.3 Distributed Traveling Salesman Problem ................................................. 48 2.8.4 FIRE Ant...uses the fixed cost of the network in its calculation and commodities are not included in the problem formulation . Using a probabilistic undirected
Multivariate Analysis Techniques for Optimal Vision System Design
DEFF Research Database (Denmark)
Sharifzadeh, Sara
The present thesis considers optimization of the spectral vision systems used for quality inspection of food items. The relationship between food quality, vision based techniques and spectral signature are described. The vision instruments for food analysis as well as datasets of the food items...... and simplifcation of the design of practical vision systems....... used in this thesis are described. The methodological strategies are outlined including sparse regression and pre-processing based on feature selection and extraction methods, supervised versus unsupervised analysis and linear versus non-linear approaches. One supervised feature selection algorithm...
Optimized dynamical decoupling in a model quantum memory.
Biercuk, Michael J; Uys, Hermann; VanDevender, Aaron P; Shiga, Nobuyasu; Itano, Wayne M; Bollinger, John J
2009-04-23
Any quantum system, such as those used in quantum information or magnetic resonance, is subject to random phase errors that can dramatically affect the fidelity of a desired quantum operation or measurement. In the context of quantum information, quantum error correction techniques have been developed to correct these errors, but resource requirements are extraordinary. The realization of a physically tractable quantum information system will therefore be facilitated if qubit (quantum bit) error rates are far below the so-called fault-tolerance error threshold, predicted to be of the order of 10(-3)-10(-6). The need to realize such low error rates motivates a search for alternative strategies to suppress dephasing in quantum systems. Here we experimentally demonstrate massive suppression of qubit error rates by the application of optimized dynamical decoupling pulse sequences, using a model quantum system capable of simulating a variety of qubit technologies. We demonstrate an analytically derived pulse sequence, UDD, and find novel sequences through active, real-time experimental feedback. The latter sequences are tailored to maximize error suppression without the need for a priori knowledge of the ambient noise environment, and are capable of suppressing errors by orders of magnitude compared to other existing sequences (including the benchmark multi-pulse spin echo). Our work includes the extension of a treatment to predict qubit decoherence under realistic conditions, yielding strong agreement between experimental data and theory for arbitrary pulse sequences incorporating nonidealized control pulses. These results demonstrate the robustness of qubit memory error suppression through dynamical decoupling techniques across a variety of qubit technologies.
Optimization algorithm based on densification and dynamic canonical descent
Bousson, K.; Correia, S. D.
2006-07-01
Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable. They have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper proposes an optimization method, which reduces the search space by means of densification curves, coupled with the dynamic canonical descent algorithm. The performances of the new method are shown on several known problems classically used for testing optimization algorithms, and proved to outperform competitive algorithms such as simulated annealing and genetic algorithms.
Dynamic Tensile Experimental Techniques for Geomaterials: A Comprehensive Review
Heard, W.; Song, B.; Williams, B.; Martin, B.; Sparks, P.; Nie, X.
2018-01-01
This review article is dedicated to the Dynamic Behavior of Materials Technical Division for celebrating the 75th anniversary of the Society for Experimental Mechanics (SEM). Understanding dynamic behavior of geomaterials is critical for analyzing and solving engineering problems of various applications related to underground explosions, seismic, airblast, and penetration events. Determining the dynamic tensile response of geomaterials has been a great challenge in experiments due to the nature of relatively low tensile strength and high brittleness. Various experimental approaches have been made in the past century, especially in the most recent half century, to understand the dynamic behavior of geomaterials in tension. In this review paper, we summarized the dynamic tensile experimental techniques for geomaterials that have been developed. The major dynamic tensile experimental techniques include dynamic direct tension, dynamic split tension, and spall tension. All three of the experimental techniques are based on Hopkinson or split Hopkinson (also known as Kolsky) bar techniques and principles. Uniqueness and limitations for each experimental technique are also discussed.
Optimization-based Dynamic Human Lifting Prediction
2008-06-01
analysis of human lifting movement for biped robot control. Advanced Motion Control, 2004. The 8th IEEE International Workshop. 7. Pope, M.H. and...constraints. Arisumi et al. (2007) studied the dynamic lifting motion of humanoid robots which considered the instantaneous transferred load to the object... robots . IEEE International Conference on Robotics and Automation, Roma, Italy, 10-14 April 2007. 2. Chaffin, D.B. and Andersson, G.B.J.. Occupational
Topology optimization of continuum structure with dynamic constraints using mode identification
Energy Technology Data Exchange (ETDEWEB)
Li, Jianhongyu; Chen, Shenyan; Huang, Hai [Beihang University, Beijing (China)
2015-04-15
For the problems such as mode exchange and localized modes in topology optimization of continuum structure with dynamic constraints, it is difficult to apply the traditional optimization model which considers fixed order mode frequencies as constraints in optimization calculation. A new optimization model is established, in which the dynamical constraints are changed as frequencies of structural principal vibrations. The order of the principal vibrations is recognized through modal identification in the optimization process, and the constraints are updated to make the optimization calculation execute smoothly. Localized mode elimination techniques are introduced to reduce the localized modes induced by the low density elements, which could improve the optimization efficiency. A new optimization process is designed, which achieves the purpose of overcoming mode exchange problem and localized mode problem at the cost of increasing several structural analyses. Optimization system is developed by using Nastran to perform structural analysis and sensitivity analysis and two-level multipoint approximation algorithm as optimizer. Numerical results verified that the presented method is effective and reasonable.
Optimal Risk Reduction in the Railway Industry by Using Dynamic Programming
Michael Todinov; Eberechi Weli
2013-01-01
The paper suggests for the first time the use of dynamic programming techniques for optimal risk reduction in the railway industry. It is shown that by using the concept ‘amount of removed risk by a risk reduction option’, the problem related to optimal allocation of a fixed budget to achieve a maximum risk reduction in the railway industry can be reduced to an optimisation problem from dynamic programming. For n risk reduction options and size of the available risk reduction budget B (expres...
Combining optimal control theory and molecular dynamics for protein folding.
Arkun, Yaman; Gur, Mert
2012-01-01
A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the Cα atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the Cα atoms. In turn, MD simulation provides an all-atom conformation whose Cα positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the Cα atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization-MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages.
Combining optimal control theory and molecular dynamics for protein folding.
Directory of Open Access Journals (Sweden)
Yaman Arkun
Full Text Available A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD. In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the Cα atoms of a Coarse-Grained (CG protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the Cα atoms. In turn, MD simulation provides an all-atom conformation whose Cα positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the Cα atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization-MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages.
A Deep-Cutting-Plane Technique for Reverse Convex Optimization.
Moshirvaziri, K; Amouzegar, M A
2011-08-01
A large number of problems in engineering design and in many areas of social and physical sciences and technology lend themselves to particular instances of problems studied in this paper. Cutting-plane methods have traditionally been used as an effective tool in devising exact algorithms for solving convex and large-scale combinatorial optimization problems. Its utilization in nonconvex optimization has been also promising. A cutting plane, essentially a hyperplane defined by a linear inequality, can be used to effectively reduce the computational efforts in search of a global solution. Each cut is generated in order to eliminate a large portion of the search domain. Thus, a deep cut is intuitively superior in which it will exclude a larger set of extraneous points from consideration. This paper is concerned with the development of deep-cutting-plane techniques applied to reverse-convex programs. An upper bound and a lower bound for the optimal value are found, updated, and improved at each iteration. The algorithm terminates when the two bounds collapse or all the generated subdivisions have been fathomed. Finally, computational considerations and numerical results on a set of test problems are discussed. An illustrative example, walking through the steps of the algorithm and explaining the computational process, is presented.
Optimization of analytical techniques to characterize antibiotics in aquatic systems
International Nuclear Information System (INIS)
Al Mokh, S.
2013-01-01
Antibiotics are considered as pollutants when they are present in aquatic ecosystems, ultimate receptacles of anthropogenic substances. These compounds are studied as their persistence in the environment or their effects on natural organisms. Numerous efforts have been made worldwide to assess the environmental quality of different water resources for the survival of aquatic species, but also for human consumption and health risk related. Towards goal, the optimization of analytical techniques for these compounds in aquatic systems remains a necessity. Our objective is to develop extraction and detection methods for 12 molecules of aminoglycosides and colistin in sewage treatment plants and hospitals waters. The lack of analytical methods for analysis of these compounds and the deficiency of studies for their detection in water is the reason for their study. Solid Phase Extraction (SPE) in classic mode (offline) or online followed by Liquid Chromatography analysis coupled with Mass Spectrometry (LC/MS/MS) is the most method commonly used for this type of analysis. The parameters are optimized and validated to ensure the best conditions for the environmental analysis. This technique was applied to real samples of wastewater treatment plants in Bordeaux and Lebanon. (author)
Optimized evaporation technique for leachate treatment: Small scale implementation.
Benyoucef, Fatima; Makan, Abdelhadi; El Ghmari, Abderrahman; Ouatmane, Aziz
2016-04-01
This paper introduces an optimized evaporation technique for leachate treatment. For this purpose and in order to study the feasibility and measure the effectiveness of the forced evaporation, three cuboidal steel tubs were designed and implemented. The first control-tub was installed at the ground level to monitor natural evaporation. Similarly, the second and the third tub, models under investigation, were installed respectively at the ground level (equipped-tub 1) and out of the ground level (equipped-tub 2), and provided with special equipment to accelerate the evaporation process. The obtained results showed that the evaporation rate at the equipped-tubs was much accelerated with respect to the control-tub. It was accelerated five times in the winter period, where the evaporation rate was increased from a value of 0.37 mm/day to reach a value of 1.50 mm/day. In the summer period, the evaporation rate was accelerated more than three times and it increased from a value of 3.06 mm/day to reach a value of 10.25 mm/day. Overall, the optimized evaporation technique can be applied effectively either under electric or solar energy supply, and will accelerate the evaporation rate from three to five times whatever the season temperature. Copyright © 2016. Published by Elsevier Ltd.
Dynamic Binary Modification Tools, Techniques and Applications
Hazelwood, Kim
2011-01-01
Dynamic binary modification tools form a software layer between a running application and the underlying operating system, providing the powerful opportunity to inspect and potentially modify every user-level guest application instruction that executes. Toolkits built upon this technology have enabled computer architects to build powerful simulators and emulators for design-space exploration, compiler writers to analyze and debug the code generated by their compilers, software developers to fully explore the features, bottlenecks, and performance of their software, and even end-users to extend
Sensitive Dependence of Optimal Network Dynamics on Network Structure
Directory of Open Access Journals (Sweden)
Takashi Nishikawa
2017-11-01
Full Text Available The relation between network structure and dynamics is determinant for the behavior of complex systems in numerous domains. An important long-standing problem concerns the properties of the networks that optimize the dynamics with respect to a given performance measure. Here, we show that such optimization can lead to sensitive dependence of the dynamics on the structure of the network. Specifically, using diffusively coupled systems as examples, we demonstrate that the stability of a dynamical state can exhibit sensitivity to unweighted structural perturbations (i.e., link removals and node additions for undirected optimal networks and to weighted perturbations (i.e., small changes in link weights for directed optimal networks. As mechanisms underlying this sensitivity, we identify discontinuous transitions occurring in the complement of undirected optimal networks and the prevalence of eigenvector degeneracy in directed optimal networks. These findings establish a unified characterization of networks optimized for dynamical stability, which we illustrate using Turing instability in activator-inhibitor systems, synchronization in power-grid networks, network diffusion, and several other network processes. Our results suggest that the network structure of a complex system operating near an optimum can potentially be fine-tuned for a significantly enhanced stability compared to what one might expect from simple extrapolation. On the other hand, they also suggest constraints on how close to the optimum the system can be in practice. Finally, the results have potential implications for biophysical networks, which have evolved under the competing pressures of optimizing fitness while remaining robust against perturbations.
A Dynamic Continuous Signature Monitoring Technique for Reliable Microprocessors
Sugihara, Makoto; 杉原, 真
2011-01-01
Reliability issues such as a soft error and NBTI (negative bias temperature instability) have become a matter of concern as integrated circuits continue to shrink. It is getting more and more important to take reliability requirements into account even for consumer products. This paper presents a dynamic continuous signature monitoring (DCSM) technique for high reliable computer systems. The DCSM technique dynamically generates reference signatures as well as runtime ones during executing a p...
Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan
2014-12-01
In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method.
Teo, Jing Chun; Foin, Nicolas; Otsuka, Fumiyuki; Bulluck, Heerajnarain; Fam, Jiang Ming; Wong, Philip; Low, Fatt Hoe; Leo, Hwa Liang; Mari, Jean-Martial; Joner, Michael; Girard, Michael J A; Virmani, Renu; Bezerra, HG.; Costa, MA.; Guagliumi, G.; Rollins, AM.; Simon, D.; Gutiérrez-Chico, JL.; Alegría-Barrero, E.; Teijeiro-Mestre, R.; Chan, PH.; Tsujioka, H.; de Silva, R.; Otsuka, F.; Joner, M.; Prati, F.; Virmani, R.; Narula, J.; Members, WC.; Levine, GN.; Bates, ER.; Blankenship, JC.; Bailey, SR.; Bittl, JA.; Prati, F.; Guagliumi, G.; Mintz, G.S.; Costa, Marco; Regar, E.; Akasaka, T.; Roleder, T.; Jąkała, J.; Kałuża, GL.; Partyka, Ł.; Proniewska, K.; Pociask, E.; Girard, MJA.; Strouthidis, NG.; Ethier, CR.; Mari, JM.; Mari, JM.; Strouthidis, NG.; Park, SC.; Girard, MJA.; van der Lee, R.; Foin, N.; Otsuka, F.; Wong, P.K.; Mari, J-M.; Joner, M.; Nakano, M.; Vorpahl, M.; Otsuka, F.; Taniwaki, M.; Yazdani, SK.; Finn, AV.; Nakano, M.; Yahagi, K.; Yamamoto, H.; Taniwaki, M.; Otsuka, F.; Ladich, ER.; Girard, MJ.; Ang, M.; Chung, CW.; Farook, M.; Strouthidis, N.; Mehta, JS.; Foin, N.; Mari, JM.; Nijjer, S.; Sen, S.; Petraco, R.; Ghione, M.; Liu, X.; Kang, JU.; Virmani, R.; Kolodgie, F.D.; Burke, AP.; Farb, A.; Schwartz, S.M.; Yahagi, K.; Kolodgie, F.D.; Otsuka, F.; Finn, AV.; Davis, HR.; Joner, M.; Kume, T.; Akasaka, T.; Kawamoto, T.; Watanabe, N.; Toyota, E.; Neishi, Y.; Rieber, J.; Meissner, O.; Babaryka, G.; Reim, S.; Oswald, M.E.; Koenig, A.S.; Tearney, G. J.; Regar, E.; Akasaka, T.; Adriaenssens, T.; Barlis, P.; Bezerra, HG.; Yabushita, H.; Bouma, BE.; Houser, S. L.; Aretz, HT.; Jang, I-K.; Schlendorf, KH.; Guo, J.; Sun, L.; Chen, Y.D.; Tian, F.; Liu, HB.; Chen, L.; Kawasaki, M.; Bouma, BE.; Bressner, J. E.; Houser, S. L.; Nadkarni, S. K.; MacNeill, BD.; Jansen, CHP.; Onthank, DC.; Cuello, F.; Botnar, RM.; Wiethoff, AJ.; Warley, A.; von Birgelen, C.; Hartmann, A. M.; Kubo, T.; Akasaka, T.; Shite, J.; Suzuki, T.; Uemura, S.; Yu, B.; Habara, M.; Nasu, K.; Terashima, M.; Kaneda, H.; Yokota, D.; Ko, E.; Virmani, R.; Burke, AP.; Kolodgie, F.D.; Farb, A.; Takarada, S.; Imanishi, T.; Kubo, T.; Tanimoto, T.; Kitabata, H.; Nakamura, N.; Hattori, K.; Ozaki, Y.; Ismail, TF.; Okumura, M.; Naruse, H.; Kan, S.; Nishio, R.; Shinke, T.; Otake, H.; Nakagawa, M.; Nagoshi, R.; Inoue, T.; Sinclair, H.D.; Bourantas, C.; Bagnall, A.; Mintz, G.S.; Kunadian, V.; Tearney, G. J.; Yabushita, H.; Houser, S. L.; Aretz, HT.; Jang, I-K.; Schlendorf, KH.; van Soest, G.; Goderie, T.; Regar, E.; Koljenović, S.; Leenders, GL. van; Gonzalo, N.; Xu, C.; Schmitt, JM.; Carlier, SG.; Virmani, R.; van der Meer, FJ; Faber, D.J.; Sassoon, DMB.; Aalders, M.C.; Pasterkamp, G.; Leeuwen, TG. van; Schmitt, JM.; Knuttel, A.; Yadlowsky, M.; Eckhaus, MA.; Karamata, B.; Laubscher, M.; Leutenegger, M.; Bourquin, S.; Lasser, T.; Lambelet, P.; Vermeer, K.A.; Mo, J.; Weda, J.J.A.; Lemij, H.G.; Boer, JF. de
2016-01-01
PURPOSE To optimize conventional coronary optical coherence tomography (OCT) images using the attenuation-compensated technique to improve identification of plaques and the external elastic lamina (EEL) contour. METHOD The attenuation-compensated technique was optimized via manipulating contrast
Dynamic shortfall constraints for optimal portfolios
Directory of Open Access Journals (Sweden)
Bernd Luderer
2010-06-01
Full Text Available We consider a portfolio problem when a Tail Conditional Expectation constraint is imposed. The financial market is composed of n risky assets driven by geometric Brownian motion and one risk-free asset. The Tail Conditional Expectation is calculated for short intervals of time and imposed as risk constraint dynamically. The method of Lagrange multipliers is combined with the Hamilton-Jacobi-Bellman equation to insert the constraint into the resolution framework. A numerical method is applied to obtain an approximate solution to the problem. We find that the imposition of the Tail Conditional Expectation constraint when risky assets evolve following a log-normal distribution, curbs investment in the risky assets and diverts the wealth to consumption.
Dynamic visualization techniques for high consequence software
Energy Technology Data Exchange (ETDEWEB)
Pollock, G.M.
1998-02-01
This report documents a prototype tool developed to investigate the use of visualization and virtual reality technologies for improving software surety confidence. The tool is utilized within the execution phase of the software life cycle. It provides a capability to monitor an executing program against prespecified requirements constraints provided in a program written in the requirements specification language SAGE. The resulting Software Attribute Visual Analysis Tool (SAVAnT) also provides a technique to assess the completeness of a software specification. The prototype tool is described along with the requirements constraint language after a brief literature review is presented. Examples of how the tool can be used are also presented. In conclusion, the most significant advantage of this tool is to provide a first step in evaluating specification completeness, and to provide a more productive method for program comprehension and debugging. The expected payoff is increased software surety confidence, increased program comprehension, and reduced development and debugging time.
Essays on variational approximation techniques for stochastic optimization problems
Deride Silva, Julio A.
This dissertation presents five essays on approximation and modeling techniques, based on variational analysis, applied to stochastic optimization problems. It is divided into two parts, where the first is devoted to equilibrium problems and maxinf optimization, and the second corresponds to two essays in statistics and uncertainty modeling. Stochastic optimization lies at the core of this research as we were interested in relevant equilibrium applications that contain an uncertain component, and the design of a solution strategy. In addition, every stochastic optimization problem relies heavily on the underlying probability distribution that models the uncertainty. We studied these distributions, in particular, their design process and theoretical properties such as their convergence. Finally, the last aspect of stochastic optimization that we covered is the scenario creation problem, in which we described a procedure based on a probabilistic model to create scenarios for the applied problem of power estimation of renewable energies. In the first part, Equilibrium problems and maxinf optimization, we considered three Walrasian equilibrium problems: from economics, we studied a stochastic general equilibrium problem in a pure exchange economy, described in Chapter 3, and a stochastic general equilibrium with financial contracts, in Chapter 4; finally from engineering, we studied an infrastructure planning problem in Chapter 5. We stated these problems as belonging to the maxinf optimization class and, in each instance, we provided an approximation scheme based on the notion of lopsided convergence and non-concave duality. This strategy is the foundation of the augmented Walrasian algorithm, whose convergence is guaranteed by lopsided convergence, that was implemented computationally, obtaining numerical results for relevant examples. The second part, Essays about statistics and uncertainty modeling, contains two essays covering a convergence problem for a sequence
Neoliberal Optimism: Applying Market Techniques to Global Health.
Mei, Yuyang
2017-01-01
Global health and neoliberalism are becoming increasingly intertwined as organizations utilize markets and profit motives to solve the traditional problems of poverty and population health. I use field work conducted over 14 months in a global health technology company to explore how the promise of neoliberalism re-envisions humanitarian efforts. In this company's vaccine refrigerator project, staff members expect their investors and their market to allow them to achieve scale and develop accountability to their users in developing countries. However, the translation of neoliberal techniques to the global health sphere falls short of the ideal, as profits are meager and purchasing power remains with donor organizations. The continued optimism in market principles amidst such a non-ideal market reveals the tenacious ideological commitment to neoliberalism in these global health projects.
Design Optimization of a Speed Reducer Using Deterministic Techniques
Directory of Open Access Journals (Sweden)
Ming-Hua Lin
2013-01-01
Full Text Available The optimal design problem of minimizing the total weight of a speed reducer under constraints is a generalized geometric programming problem. Since the metaheuristic approaches cannot guarantee to find the global optimum of a generalized geometric programming problem, this paper applies an efficient deterministic approach to globally solve speed reducer design problems. The original problem is converted by variable transformations and piecewise linearization techniques. The reformulated problem is a convex mixed-integer nonlinear programming problem solvable to reach an approximate global solution within an acceptable error. Experiment results from solving a practical speed reducer design problem indicate that this study obtains a better solution comparing with the other existing methods.
Techniques for optimizing nanotips derived from frozen taylor cones
Hirsch, Gregory
2017-12-05
Optimization techniques are disclosed for producing sharp and stable tips/nanotips relying on liquid Taylor cones created from electrically conductive materials with high melting points. A wire substrate of such a material with a preform end in the shape of a regular or concave cone, is first melted with a focused laser beam. Under the influence of a high positive potential, a Taylor cone in a liquid/molten state is formed at that end. The cone is then quenched upon cessation of the laser power, thus freezing the Taylor cone. The tip of the frozen Taylor cone is reheated by the laser to allow its precise localized melting and shaping. Tips thus obtained yield desirable end-forms suitable as electron field emission sources for a variety of applications. In-situ regeneration of the tip is readily accomplished. These tips can also be employed as regenerable bright ion sources using field ionization/desorption of introduced chemical species.
Optimization of dynamic soaring maneuvers to enhance endurance of a versatile UAV
Mir, Imran; Maqsood, Adnan; Akhtar, Suhail
2017-06-01
Dynamic soaring is a process of acquiring energy available in atmospheric wind shears and is commonly exhibited by soaring birds to perform long distance flights. This paper aims to demonstrate a viable algorithm which can be implemented in near real time environment to formulate optimal trajectories for dynamic soaring maneuvers for a small scale Unmanned Aerial Vehicle (UAV). The objective is to harness maximum energy from atmosphere wind shear to improve loiter time for Intelligence, Surveillance and Reconnaissance (ISR) missions. Three-dimensional point-mass UAV equations of motion and linear wind gradient profile are used to model flight dynamics. Utilizing UAV states, controls, operational constraints, initial and terminal conditions that enforce a periodic flight, dynamic soaring problem is formulated as an optimal control problem. Optimized trajectories of the maneuver are subsequently generated employing pseudo spectral techniques against distant UAV performance parameters. The discussion also encompasses the requirement for generation of optimal trajectories for dynamic soaring in real time environment and the ability of the proposed algorithm for speedy solution generation. Coupled with the fact that dynamic soaring is all about immediately utilizing the available energy from the wind shear encountered, the proposed algorithm promises its viability for practical on board implementations requiring computation of trajectories in near real time.
Focusing light through dynamical samples using fast continuous wavefront optimization.
Blochet, B; Bourdieu, L; Gigan, S
2017-12-01
We describe a fast continuous optimization wavefront shaping system able to focus light through dynamic scattering media. A micro-electro-mechanical system-based spatial light modulator, a fast photodetector, and field programmable gate array electronics are combined to implement a continuous optimization of a wavefront with a single-mode optimization rate of 4.1 kHz. The system performances are demonstrated by focusing light through colloidal solutions of TiO 2 particles in glycerol with tunable temporal stability.
Optimization Techniques for Dimensionally Truncated Sparse Grids on Heterogeneous Systems
Deftu, A.
2013-02-01
Given the existing heterogeneous processor landscape dominated by CPUs and GPUs, topics such as programming productivity and performance portability have become increasingly important. In this context, an important question refers to how can we develop optimization strategies that cover both CPUs and GPUs. We answer this for fastsg, a library that provides functionality for handling efficiently high-dimensional functions. As it can be employed for compressing and decompressing large-scale simulation data, it finds itself at the core of a computational steering application which serves us as test case. We describe our experience with implementing fastsg\\'s time critical routines for Intel CPUs and Nvidia Fermi GPUs. We show the differences and especially the similarities between our optimization strategies for the two architectures. With regard to our test case for which achieving high speedups is a "must" for real-time visualization, we report a speedup of up to 6.2x times compared to the state-of-the-art implementation of the sparse grid technique for GPUs. © 2013 IEEE.
Optimization techniques for smart integrated sensor networks in environmental monitoring
Gandelli, A.; Grimaccia, F.; Zich, R. E.
2007-12-01
Sensor networks are an emerging field of research which presents significant system challenges involving the use of large numbers of resource-constrained nodes operating essentially unattended and exposed to potential local communication failures. Current sensor networks address problems of meeting standards for accuracy and also delivering data from remote locations with an appropriate level of spatial and temporal resolution. Today advances in sensor technology, wireless communications and digital electronics make it possible to produce large amount of small-size, low-cost sensors which integrate together sensing, processing, and communication capabilities. The advantages are evident not only in the reduction of size, but also in the increase of functional performance and reliability, and a unit-cost reduction in mass production lines. In this work hybrid evolutionary algorithms are applied to optimize the design of cluster formation in wireless sensor networks, guaranteeing at the same time a full network connectivity and a minimum energy consumption. The proposed techniques have been tested in respect of the most known test functions with good results obtained in all the considered cases, especially for optimization of large domain objective functions. This feature makes these algorithms suitable for a wide range of applications, capable of outperforming classical procedures.
Selection of optimal variant route based on dynamic fuzzy GRA
Directory of Open Access Journals (Sweden)
Jalil Heidary Dahooie
2018-09-01
Full Text Available Given the high costs of construction and maintenance, an optimum design methodology is one of the most important steps towards the development of transportation infrastructure, especially freeways. However, the effects of different variables on the decision-making process to find an optimal variant have caused the choice to become a very difficult and professional task for decision makers. So, the current paper aims to determine the optimal variant route for Isfahan-Shiraz freeway through MADM approaches. First, evaluation indices for an optimal route variant are derived through literature review and expert panel assessment. Then, a dynamic fuzzy GRA method is used for weightings and optimal route selection. Bases on the results, the road longevity, views of NGOs and route integration are identified as the highest-weighted criteria in route variant prioritization. Further, Route 3 is defined as the priority for the optimal variant for Isfahan–Shiraz freeway, which is the main basis in practice.
Off-road vehicle dynamics analysis, modelling and optimization
Taghavifar, Hamid
2017-01-01
This book deals with the analysis of off-road vehicle dynamics from kinetics and kinematics perspectives and the performance of vehicle traversing over rough and irregular terrain. The authors consider the wheel performance, soil-tire interactions and their interface, tractive performance of the vehicle, ride comfort, stability over maneuvering, transient and steady state conditions of the vehicle traversing, modeling the aforementioned aspects and optimization from energetic and vehicle mobility perspectives. This book brings novel figures for the transient dynamics and original wheel terrain dynamics at on-the-go condition.
A Monte Carlo simulation technique to determine the optimal portfolio
Directory of Open Access Journals (Sweden)
Hassan Ghodrati
2014-03-01
Full Text Available During the past few years, there have been several studies for portfolio management. One of the primary concerns on any stock market is to detect the risk associated with various assets. One of the recognized methods in order to measure, to forecast, and to manage the existing risk is associated with Value at Risk (VaR, which draws much attention by financial institutions in recent years. VaR is a method for recognizing and evaluating of risk, which uses the standard statistical techniques and the method has been used in other fields, increasingly. The present study has measured the value at risk of 26 companies from chemical industry in Tehran Stock Exchange over the period 2009-2011 using the simulation technique of Monte Carlo with 95% confidence level. The used variability in the present study has been the daily return resulted from the stock daily price change. Moreover, the weight of optimal investment has been determined using a hybrid model called Markowitz and Winker model in each determined stocks. The results showed that the maximum loss would not exceed from 1259432 Rials at 95% confidence level in future day.
The L_infinity constrained global optimal histogram equalization technique for real time imaging
Ren, Qiongwei; Niu, Yi; Liu, Lin; Jiao, Yang; Shi, Guangming
2015-08-01
Although the current imaging sensors can achieve 12 or higher precision, the current display devices and the commonly used digital image formats are still only 8 bits. This mismatch causes significant waste of the sensor precision and loss of information when storing and displaying the images. For better usage of the precision-budget, tone mapping operators have to be used to map the high-precision data into low-precision digital images adaptively. In this paper, the classic histogram equalization tone mapping operator is reexamined in the sense of optimization. We point out that the traditional histogram equalization technique and its variants are fundamentally improper by suffering from local optimum problems. To overcome this drawback, we remodel the histogram equalization tone mapping task based on graphic theory which achieves the global optimal solutions. Another advantage of the graphic-based modeling is that the tone-continuity is also modeled as a vital constraint in our approach which suppress the annoying boundary artifacts of the traditional approaches. In addition, we propose a novel dynamic programming technique to solve the histogram equalization problem in real time. Experimental results shows that the proposed tone-preserved global optimal histogram equalization technique outperforms the traditional approaches by exhibiting more subtle details in the foreground while preserving the smoothness of the background.
Optimal foraging and predator-prey dynamics III
Czech Academy of Sciences Publication Activity Database
Křivan, Vlastimil; Eisner, Jan
2003-01-01
Roč. 63, - (2003), s. 269-279 ISSN 0040-5809 R&D Projects: GA ČR GA201/03/0091; GA MŠk LA 101 Institutional research plan: CEZ:AV0Z5007907 Keywords : Optimal foraging theory * adaptive behavior * predator-prec population dynamics Subject RIV: EH - Ecology, Behaviour Impact factor: 2.261, year: 2003
Topology optimization of dynamics problems with Padé approximants
DEFF Research Database (Denmark)
Jensen, Jakob Søndergaard
2007-01-01
An efficient procedure for topology optimization of dynamics problems is proposed. The method is based on frequency responses represented by Padé approximants and analytical sensitivity analysis derived using the adjoint method. This gives an accurate approximation of the frequency response over ...
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha
2013-01-01
This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.
Bridging Developmental Systems Theory and Evolutionary Psychology Using Dynamic Optimization
Frankenhuis, Willem E.; Panchanathan, Karthik; Clark Barrett, H.
2013-01-01
Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic…
International Nuclear Information System (INIS)
Mestrovic, Ante; Clark, Brenda G.
2005-01-01
Purpose: To develop a method of predicting the values of dose distribution parameters of different radiosurgery techniques for treatment of arteriovenous malformation (AVM) based on internal geometric parameters. Methods and Materials: For each of 18 previously treated AVM patients, four treatment plans were created: circular collimator arcs, dynamic conformal arcs, fixed conformal fields, and intensity-modulated radiosurgery. An algorithm was developed to characterize the target and critical structure shape complexity and the position of the critical structures with respect to the target. Multiple regression was employed to establish the correlation between the internal geometric parameters and the dose distribution for different treatment techniques. The results from the model were applied to predict the dosimetric outcomes of different radiosurgery techniques and select the optimal radiosurgery technique for a number of AVM patients. Results: Several internal geometric parameters showing statistically significant correlation (p < 0.05) with the treatment planning results for each technique were identified. The target volume and the average minimum distance between the target and the critical structures were the most effective predictors for normal tissue dose distribution. The structure overlap volume with the target and the mean distance between the target and the critical structure were the most effective predictors for critical structure dose distribution. The predicted values of dose distribution parameters of different radiosurgery techniques were in close agreement with the original data. Conclusions: A statistical model has been described that successfully predicts the values of dose distribution parameters of different radiosurgery techniques and may be used to predetermine the optimal technique on a patient-to-patient basis
A dynamic optimization model for solid waste recycling.
Anghinolfi, Davide; Paolucci, Massimo; Robba, Michela; Taramasso, Angela Celeste
2013-02-01
Recycling is an important part of waste management (that includes different kinds of issues: environmental, technological, economic, legislative, social, etc.). Differently from many works in literature, this paper is focused on recycling management and on the dynamic optimization of materials collection. The developed dynamic decision model is characterized by state variables, corresponding to the quantity of waste in each bin per each day, and control variables determining the quantity of material that is collected in the area each day and the routes for collecting vehicles. The objective function minimizes the sum of costs minus benefits. The developed decision model is integrated in a GIS-based Decision Support System (DSS). A case study related to the Cogoleto municipality is presented to show the effectiveness of the proposed model. From optimal results, it has been found that the net benefits of the optimized collection are about 2.5 times greater than the estimated current policy. Copyright © 2012 Elsevier Ltd. All rights reserved.
A Thermodynamic Library for Simulation and Optimization of Dynamic Processes
DEFF Research Database (Denmark)
Ritschel, Tobias Kasper Skovborg; Gaspar, Jozsef; Jørgensen, John Bagterp
2017-01-01
Process system tools, such as simulation and optimization of dynamic systems, are widely used in the process industries for development of operational strategies and control for process systems. These tools rely on thermodynamic models and many thermodynamic models have been developed for different...... compounds and mixtures. However, rigorous thermodynamic models are generally computationally intensive and not available as open-source libraries for process simulation and optimization. In this paper, we describe the application of a novel open-source rigorous thermodynamic library, ThermoLib, which...... is designed for dynamic simulation and optimization of vapor-liquid processes. ThermoLib is implemented in Matlab and C and uses cubic equations of state to compute vapor and liquid phase thermodynamic properties. The novelty of ThermoLib is that it provides analytical first and second order derivatives...
Dynamic ADMM for Real-time Optimal Power Flow: Preprint
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2018-02-23
This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation of the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.
Numerical integration and optimization of motions for multibody dynamic systems
Aguilar Mayans, Joan
This thesis considers the optimization and simulation of motions involving rigid body systems. It does so in three distinct parts, with the following topics: optimization and analysis of human high-diving motions, efficient numerical integration of rigid body dynamics with contacts, and motion optimization of a two-link robot arm using Finite-Time Lyapunov Analysis. The first part introduces the concept of eigenpostures, which we use to simulate and analyze human high-diving motions. Eigenpostures are used in two different ways: first, to reduce the complexity of the optimal control problem that we solve to obtain such motions, and second, to generate an eigenposture space to which we map existing real world motions to better analyze them. The benefits of using eigenpostures are showcased through different examples. The second part reviews an extensive list of integration algorithms used for the integration of rigid body dynamics. We analyze the accuracy and stability of the different integrators in the three-dimensional space and the rotation space SO(3). Integrators with an accuracy higher than first order perform more efficiently than integrators with first order accuracy, even in the presence of contacts. The third part uses Finite-time Lyapunov Analysis to optimize motions for a two-link robot arm. Finite-Time Lyapunov Analysis diagnoses the presence of time-scale separation in the dynamics of the optimized motion and provides the information and methodology for obtaining an accurate approximation to the optimal solution, avoiding the complications that timescale separation causes for alternative solution methods.
Optimization technique for problems with an inequality constraint
Russell, K. J.
1972-01-01
General technique uses a modified version of an existing technique termed the pattern search technique. New procedure called the parallel move strategy permits pattern search technique to be used with problems involving a constraint.
Chen, Caroline Wen Jia; Heim, Winfried; Fairley, Karen; Clement, Russell J; Biddiss, Elaine; Torres-Moreno, Ricardo; Andrysek, Jan
2016-08-01
A prosthesis that is not optimally aligned can adversely influence the rehabilitation and health of the amputee. Very few studies to date evaluate the effectiveness and utility of instrument-assisted alignment techniques in clinical practice. To compare an instrument-assisted dynamic alignment technique (Compas(™)) to conventional methods. In a crossover study design, dynamic prosthetic alignments were provided to nine individuals with unilateral transtibial amputations to compare conventional and instrument-assisted alignment techniques. The instrument-assisted technique involved a commercially available force and torque sensing dynamic alignment system (Compas). Cadence, pelvic accelerations, and socket moments were assessed. A custom questionnaire was used to gather user perceptions. No differences between alignment techniques were found in global gait measures including cadence and pelvic accelerations. No significant alignment differences were achieved by examination of angular changes between the socket and foot; however, significantly higher below-the-socket moments were found with the instrument-assisted technique. From the questionnaire, six amputees had no preference, while three preferred the conventional alignment. The use of Compas appears to produce similar alignment results as conventional techniques, although with slightly higher moments at the socket. This study provides new information about the clinical utilization of instrument-assisted prosthetic alignment techniques for individuals with transtibial amputation. © The International Society for Prosthetics and Orthotics 2015.
Use of advanced modeling techniques to optimize thermal packaging designs.
Formato, Richard M; Potami, Raffaele; Ahmed, Iftekhar
2010-01-01
Through a detailed case study the authors demonstrate, for the first time, the capability of using advanced modeling techniques to correctly simulate the transient temperature response of a convective flow-based thermal shipper design. The objective of this case study was to demonstrate that simulation could be utilized to design a 2-inch-wall polyurethane (PUR) shipper to hold its product box temperature between 2 and 8 °C over the prescribed 96-h summer profile (product box is the portion of the shipper that is occupied by the payload). Results obtained from numerical simulation are in excellent agreement with empirical chamber data (within ±1 °C at all times), and geometrical locations of simulation maximum and minimum temperature match well with the corresponding chamber temperature measurements. Furthermore, a control simulation test case was run (results taken from identical product box locations) to compare the coupled conduction-convection model with a conduction-only model, which to date has been the state-of-the-art method. For the conduction-only simulation, all fluid elements were replaced with "solid" elements of identical size and assigned thermal properties of air. While results from the coupled thermal/fluid model closely correlated with the empirical data (±1 °C), the conduction-only model was unable to correctly capture the payload temperature trends, showing a sizeable error compared to empirical values (ΔT > 6 °C). A modeling technique capable of correctly capturing the thermal behavior of passively refrigerated shippers can be used to quickly evaluate and optimize new packaging designs. Such a capability provides a means to reduce the cost and required design time of shippers while simultaneously improving their performance. Another advantage comes from using thermal modeling (assuming a validated model is available) to predict the temperature distribution in a shipper that is exposed to ambient temperatures which were not bracketed
An optimal maintenance policy for machine replacement problem using dynamic programming
Directory of Open Access Journals (Sweden)
Mohsen Sadegh Amalnik
2017-06-01
Full Text Available In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling including renew, repair and do nothing and wish to achieve an optimal threshold for making decisions including renew, repair and continue the production in order to minimize the expected cost. Results show that the optimal policy is sensitive to the data, for the probability of defective machines and parameters defined in the model. This can be clearly demonstrated by a sensitivity analysis technique.
Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari
2014-01-01
A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.
Directory of Open Access Journals (Sweden)
Farzad Tahriri
2014-01-01
Full Text Available A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC is integrated with automatic learning dynamic fuzzy controller (ALDFC technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model.
Tahriri, Farzad; Dawal, Siti Zawiah Md; Taha, Zahari
2014-01-01
A new multiobjective dynamic fuzzy genetic algorithm is applied to solve a fuzzy mixed-model assembly line sequencing problem in which the primary goals are to minimize the total make-span and minimize the setup number simultaneously. Trapezoidal fuzzy numbers are implemented for variables such as operation and travelling time in order to generate results with higher accuracy and representative of real-case data. An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. In establishing the FAGA, five dynamic fuzzy parameter controllers are devised in which fuzzy expert experience controller (FEEC) is integrated with automatic learning dynamic fuzzy controller (ALDFC) technique. The enhanced algorithm dynamically adjusts the population size, number of generations, tournament candidate, crossover rate, and mutation rate compared with using fixed control parameters. The main idea is to improve the performance and effectiveness of existing GAs by dynamic adjustment and control of the five parameters. Verification and validation of the dynamic fuzzy GA are carried out by developing test-beds and testing using a multiobjective fuzzy mixed production assembly line sequencing optimization problem. The simulation results highlight that the performance and efficacy of the proposed novel optimization algorithm are more efficient than the performance of the standard genetic algorithm in mixed assembly line sequencing model. PMID:24982962
Applying Parallel Processing Techniques to Tether Dynamics Simulation
Wells, B. Earl
1996-01-01
The focus of this research has been to determine the effectiveness of applying parallel processing techniques to a sizable real-world problem, the simulation of the dynamics associated with a tether which connects two objects in low earth orbit, and to explore the degree to which the parallelization process can be automated through the creation of new software tools. The goal has been to utilize this specific application problem as a base to develop more generally applicable techniques.
Optimization and Application of Surface Segmentation Technique for Tomographic PIV
Ding, Liuyang; Adrian, Ronald; Wilson, Brandon; Prestridge, Kathy; Team
2014-11-01
Tomographic PIV is a widely used 3D flow measurement technique. It utilizes images recorded by multiple cameras to reconstruct the intensity distribution of a measured volume. The 3D3C velocity field is then computed by 3D cross-correlation. Surface segmentation aims to reduce computational cost. It extracts from a cloud of particles an image of those particles that lie on a mathematically prescribed surface. 2D2C velocity fields are computed on stacks of orthogonal surfaces, then assembled to construct the full 3D3C velocity field. We investigate the reconstruction of adaptive surfaces aligned with the main flow direction minimizing the out-of-plane motion. Numerical assessment is performed on curved-surface reconstruction for Taylor-Couette flow. An optimizing 2D interrogation scheme involving volumetric deformation is proposed to improve the accuracy of the 3D3C velocity field. The numerical test is performed on a synthetic vortex ring showing good measurement accuracy. Experimental results measuring the shock-driven turbulent mixing will also be presented. References
Optimized inspection techniques and structural analysis in lifetime management
International Nuclear Information System (INIS)
Aguado, M.T.; Marcelles, I.
1993-01-01
Preservation of the option of extending the service lifetime of a nuclear power plant beyond its normal design lifetime requires correct remaining lifetime management from the very beginning of plant operation. The methodology used in plant remaining lifetime management is essentially based on the use of standard inspections, surveillance and monitoring programs and calculations, such as thermal-stress and fracture mechanics analysis. The inspection techniques should be continuously optimized, in order to be able to detect and dimension existing defects with the highest possible degree of accuracy. The information obtained during the inspection is combined with the historical data of the components: design, quality, operation, maintenance, and transients, and with the results of destructive testing, fracture mechanics and thermal fatigue analysis. These data are used to estimate the remaining lifetime of nuclear power plant components, systems and structures with the highest degree possible of accuracy. The use of this methodology allows component repairs and replacements to be reduced or avoided and increases the safety levels and availability of the nuclear power plant. Use of this strategy avoids the need for heavy investments at the end of the licensing period
Muscle optimization techniques impact the magnitude of calculated hip joint contact forces
Wesseling, M.; Derikx, L.C.; de Groote, F.; Bartels, W.; Meyer, C.; Verdonschot, Nicolaas Jacobus Joseph; Jonkers, I.
2015-01-01
In musculoskeletal modelling, several optimization techniques are used to calculate muscle forces, which strongly influence resultant hip contact forces (HCF). The goal of this study was to calculate muscle forces using four different optimization techniques, i.e., two different static optimization
International Nuclear Information System (INIS)
Nguyen, Quoc-Hung; Choi, Seung-Bok
2009-01-01
This paper presents an optimal design of a passenger vehicle magnetorheological (MR) damper based on finite element analysis. The MR damper is constrained in a specific volume and the optimization problem identifies the geometric dimensions of the damper that minimize an objective function. The objective function consists of the damping force, the dynamic range, and the inductive time constant of the damper. After describing the configuration of the MR damper, the damping force and dynamic range are obtained on the basis of the Bingham model of an MR fluid. Then, the control energy (power consumption of the damper coil) and the inductive time constant are derived. The objective function for the optimization problem is determined based on the solution of the magnetic circuit of the initial damper. Subsequently, the optimization procedure, using a golden-section algorithm and a local quadratic fitting technique, is constructed via commercial finite element method parametric design language. Using the developed optimization tool, optimal solutions of the MR damper, which are constrained in a specific cylindrical volume defined by its radius and height, are determined and a comparative work on damping force and inductive time constant between the initial and optimal design is undertaken
Dynamic nuclear polarization and optimal control spatial-selective 13C MRI and MRS
DEFF Research Database (Denmark)
Vinding, Mads Sloth; Laustsen, Christoffer; Maximov, Ivan I.
2013-01-01
Aimed at 13C metabolic magnetic resonance imaging (MRI) and spectroscopy (MRS) applications, we demonstrate that dynamic nuclear polarization (DNP) may be combined with optimal control 2D spatial selection to simultaneously obtain high sensitivity and well-defined spatial restriction. This is ach......Aimed at 13C metabolic magnetic resonance imaging (MRI) and spectroscopy (MRS) applications, we demonstrate that dynamic nuclear polarization (DNP) may be combined with optimal control 2D spatial selection to simultaneously obtain high sensitivity and well-defined spatial restriction....... This is achieved through the development of spatial-selective single-shot spiral-readout MRI and MRS experiments combined with dynamic nuclear polarization hyperpolarized [1-13C]pyruvate on a 4.7T pre-clinical MR scanner. The method stands out from related techniques by facilitating anatomic shaped region...
Optimal control and design of a cold store using dynamic optimization
Lukasse, L.; Broeze, J.; Sluis, S. van der
2009-01-01
The design of controlled processes is a combined optimal control and design problem (OCDP). Literature on solving large OCDPs is rare. This paper presents an algorithm for solving large OCDPs. For this algorithm system dynamics, objective function and their first-order derivatives must be continuous
International Nuclear Information System (INIS)
Wu, Xia; Wu, Genhua
2014-01-01
Highlights: • A high efficient method for optimization of atomic clusters is developed. • Its performance is studied by optimizing Lennard-Jones clusters and Ag clusters. • The method is proved to be quite efficient. • A new Ag 61 cluster with stacking-fault face-centered cubic motif is found. - Abstract: Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag 61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron
A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization
Directory of Open Access Journals (Sweden)
Daqing Wu
2012-01-01
Full Text Available A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is constructed to maintain the population diversity. In the second stage, the parallel, positive feedback of CABC was implemented in each small swarm. In the third stage, we make use of the particle swarm optimization global model, which has a faster convergence speed to enhance the global convergence in solving the whole problem. To verify the effectiveness and efficiency of the proposed hybrid algorithm, various scale benchmark problems are tested to demonstrate the potential of the proposed multistage hybrid swarm intelligence optimization algorithm. The results show that DM-PSO-ABC is better in the search precision, and convergence property and has strong ability to escape from the local suboptima when compared with several other peer algorithms.
Energy Technology Data Exchange (ETDEWEB)
Wu, Xia, E-mail: xiawu@mail.nankai.edu.cn; Wu, Genhua
2014-08-31
Highlights: • A high efficient method for optimization of atomic clusters is developed. • Its performance is studied by optimizing Lennard-Jones clusters and Ag clusters. • The method is proved to be quite efficient. • A new Ag{sub 61} cluster with stacking-fault face-centered cubic motif is found. - Abstract: Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag{sub 61} cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron.
International Nuclear Information System (INIS)
Lee, Kyou Seok; Jeon, Sang Youn; Kim, Hyeong Koo
2009-01-01
Under the Safe Shutdown Earthquake (SSE) and Loss of Coolant Accident (LOCA) events, the fuel assembly deflection and impact force between fuel assemblies are obtained by the dynamic transient analysis for the reactor core model. The impact behavior between fuel assemblies shows non-linear characteristics, because fuel assembly shows non-linearly dynamic characteristics and its geometry is complicated. Furthermore, since a reactor core consists of a large number of fuel assemblies, the dynamic behavior of the core under the postulated events is very difficult to analyze. Therefore, it is necessary that fuel assembly model be simplified considering dynamic non-linear characteristics in core analysis. In this study, a simplified fuel assembly finite element model for 17 Type RFA has been developed using optimization technique. To obtain the simplified model, the optimization algorithm of ANSYS was used, and the model was verified by comparison with fuel assembly mechanical test results
Energy Technology Data Exchange (ETDEWEB)
Lee, Kyou Seok; Jeon, Sang Youn; Kim, Hyeong Koo [Korea Nuclear Fuel, Daejeon (Korea, Republic of)
2009-05-15
Under the Safe Shutdown Earthquake (SSE) and Loss of Coolant Accident (LOCA) events, the fuel assembly deflection and impact force between fuel assemblies are obtained by the dynamic transient analysis for the reactor core model. The impact behavior between fuel assemblies shows non-linear characteristics, because fuel assembly shows non-linearly dynamic characteristics and its geometry is complicated. Furthermore, since a reactor core consists of a large number of fuel assemblies, the dynamic behavior of the core under the postulated events is very difficult to analyze. Therefore, it is necessary that fuel assembly model be simplified considering dynamic non-linear characteristics in core analysis. In this study, a simplified fuel assembly finite element model for 17 Type RFA has been developed using optimization technique. To obtain the simplified model, the optimization algorithm of ANSYS was used, and the model was verified by comparison with fuel assembly mechanical test results.
Determination of the optimal tolerance for MLC positioning in sliding window and VMAT techniques
Energy Technology Data Exchange (ETDEWEB)
Hernandez, V., E-mail: vhernandezmasgrau@gmail.com; Abella, R. [Department of Medical Physics, Hospital Sant Joan de Reus, IISPV, Tarragona 43204 (Spain); Calvo, J. F. [Department of Radiation Oncology, Hospital Quirón, Barcelona 08023 (Spain); Jurado-Bruggemann, D. [Department of Medical Physics, Institut Català d’Oncologia, Girona 17007 (Spain); Sancho, I. [Department of Medical Physics, Institut Català d’Oncologia, L’Hospitalet de Llobregat 08908 (Spain); Carrasco, P. [Department of Medical Physics, Hospital de la Santa Creu i Sant Pau, Barcelona 08041 (Spain)
2015-04-15
Purpose: Several authors have recommended a 2 mm tolerance for multileaf collimator (MLC) positioning in sliding window treatments. In volumetric modulated arc therapy (VMAT) treatments, however, the optimal tolerance for MLC positioning remains unknown. In this paper, the authors present the results of a multicenter study to determine the optimal tolerance for both techniques. Methods: The procedure used is based on dynalog file analysis. The study was carried out using seven Varian linear accelerators from five different centers. Dynalogs were collected from over 100 000 clinical treatments and in-house software was used to compute the number of tolerance faults as a function of the user-defined tolerance. Thus, the optimal value for this tolerance, defined as the lowest achievable value, was investigated. Results: Dynalog files accurately predict the number of tolerance faults as a function of the tolerance value, especially for low fault incidences. All MLCs behaved similarly and the Millennium120 and the HD120 models yielded comparable results. In sliding window techniques, the number of beams with an incidence of hold-offs >1% rapidly decreases for a tolerance of 1.5 mm. In VMAT techniques, the number of tolerance faults sharply drops for tolerances around 2 mm. For a tolerance of 2.5 mm, less than 0.1% of the VMAT arcs presented tolerance faults. Conclusions: Dynalog analysis provides a feasible method for investigating the optimal tolerance for MLC positioning in dynamic fields. In sliding window treatments, the tolerance of 2 mm was found to be adequate, although it can be reduced to 1.5 mm. In VMAT treatments, the typically used 5 mm tolerance is excessively high. Instead, a tolerance of 2.5 mm is recommended.
Determination of the optimal tolerance for MLC positioning in sliding window and VMAT techniques.
Hernandez, V; Abella, R; Calvo, J F; Jurado-Bruggemann, D; Sancho, I; Carrasco, P
2015-04-01
Several authors have recommended a 2 mm tolerance for multileaf collimator (MLC) positioning in sliding window treatments. In volumetric modulated arc therapy (VMAT) treatments, however, the optimal tolerance for MLC positioning remains unknown. In this paper, the authors present the results of a multicenter study to determine the optimal tolerance for both techniques. The procedure used is based on dynalog file analysis. The study was carried out using seven Varian linear accelerators from five different centers. Dynalogs were collected from over 100,000 clinical treatments and in-house software was used to compute the number of tolerance faults as a function of the user-defined tolerance. Thus, the optimal value for this tolerance, defined as the lowest achievable value, was investigated. Dynalog files accurately predict the number of tolerance faults as a function of the tolerance value, especially for low fault incidences. All MLCs behaved similarly and the Millennium120 and the HD120 models yielded comparable results. In sliding window techniques, the number of beams with an incidence of hold-offs >1% rapidly decreases for a tolerance of 1.5 mm. In VMAT techniques, the number of tolerance faults sharply drops for tolerances around 2 mm. For a tolerance of 2.5 mm, less than 0.1% of the VMAT arcs presented tolerance faults. Dynalog analysis provides a feasible method for investigating the optimal tolerance for MLC positioning in dynamic fields. In sliding window treatments, the tolerance of 2 mm was found to be adequate, although it can be reduced to 1.5 mm. In VMAT treatments, the typically used 5 mm tolerance is excessively high. Instead, a tolerance of 2.5 mm is recommended.
Optimal dynamic soaring consists of successive shallow arcs.
Bousquet, Gabriel D; Triantafyllou, Michael S; Slotine, Jean-Jacques E
2017-10-01
Albatrosses can travel a thousand kilometres daily over the oceans. They extract their propulsive energy from horizontal wind shears with a flight strategy called dynamic soaring. While thermal soaring, exploited by birds of prey and sports gliders, consists of simply remaining in updrafts, extracting energy from horizontal winds necessitates redistributing momentum across the wind shear layer, by means of an intricate and dynamic flight manoeuvre. Dynamic soaring has been described as a sequence of half-turns connecting upwind climbs and downwind dives through the surface shear layer. Here, we investigate the optimal (minimum-wind) flight trajectory, with a combined numerical and analytic methodology. We show that contrary to current thinking, but consistent with GPS recordings of albatrosses, when the shear layer is thin the optimal trajectory is composed of small-angle, large-radius arcs. Essentially, the albatross is a flying sailboat, sequentially acting as sail and keel, and is most efficient when remaining crosswind at all times. Our analysis constitutes a general framework for dynamic soaring and more broadly energy extraction in complex winds. It is geared to improve the characterization of pelagic birds flight dynamics and habitat, and could enable the development of a robotic albatross that could travel with a virtually infinite range. © 2017 The Author(s).
A fast and optimized dynamic economic load dispatch for large scale power systems
International Nuclear Information System (INIS)
Musse Mohamud Ahmed; Mohd Ruddin Ab Ghani; Ismail Hassan
2000-01-01
This paper presents Lagrangian Multipliers (LM) and Linear Programming (LP) based dynamic economic load dispatch (DELD) solution for large-scale power system operations. It is to minimize the operation cost of power generation. units subject to the considered constraints. After individual generator units are economically loaded and periodically dispatched, fast and optimized DELD has been achieved. DELD with period intervals has been taken into consideration The results found from the algorithm based on LM and LP techniques appear to be modest in both optimizing the operation cost and achieving fast computation. (author)
DEFF Research Database (Denmark)
Larsen, Anders Astrup; Bendsøe, Martin P.; Schmidt, Henrik Nikolaj Blicher
2007-01-01
The aim of this paper is to optimize a thermal model of a friction stir welding process. The optimization is performed using a space mapping technique in which an analytical model is used along with the FEM model to be optimized. The results are compared to traditional gradient based optimization...
Adaptive dynamic programming with applications in optimal control
Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang
2017-01-01
This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...
Shape Optimization of Vehicle Radiator Using Computational Fluid Dynamics (cfd)
Maddipatla, Sridhar; Guessous, Laila
2002-11-01
Automotive manufacturers need to improve the efficiency and lifetime of all engine components. In the case of radiators, performance depends significantly on coolant flow homogeneity across the tubes and overall pressure drop between the inlet and outlet. Design improvements are especially needed in tube-flow uniformity to prevent premature fouling and failure of heat exchangers. Rather than relying on ad-hoc geometry changes, the current study combines Computational Fluid Dynamics with shape optimization methods to improve radiator performance. The goal is to develop an automated suite of virtual tools to assist in radiator design. Two objective functions are considered: a flow non-uniformity coefficient,Cf, and the overall pressure drop, dP*. The methodology used to automate the CFD and shape optimization procedures is discussed. In the first phase, single and multi-variable optimization methods, coupled with CFD, are applied to simplified 2-D radiator models to investigate effects of inlet and outlet positions on the above functions. The second phase concentrates on CFD simulations of a simplified 3-D radiator model. The results, which show possible improvements in both pressure and flow uniformity, validate the optimization criteria that were developed, as well as the potential of shape optimization methods with CFD to improve heat exchanger design. * Improving Radiator Design Through Shape Optimization, L. Guessous and S. Maddipatla, Paper # IMECE2002-33888, Proceedings of the 2002 ASME International Mechanical Engineering Congress and Exposition, November 2002
Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong
2015-04-01
Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.
An Approximate Dynamic Programming Mode for Optimal MEDEVAC Dispatching
2015-03-26
Robbins, PhD Chair LTC Brian J. Lunday, PhD Member AFIT-ENS-MS-15-M-115 Abstract We develop a Markov decision process ( MDP ) model to examine military...medical evacuation (MEDEVAC) dispatch policies. To solve the MDP , we apply an ap- proximate dynamic programming (ADP) technique. The problem of deciding...Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.1 MDP Formulation
Power system dynamic state estimation using prediction based evolutionary technique
International Nuclear Information System (INIS)
Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan
2016-01-01
In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.
SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING
Directory of Open Access Journals (Sweden)
Viorel MINZU
2015-12-01
Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.
Confronting dynamics and uncertainty in optimal decision making for conservation
International Nuclear Information System (INIS)
Williams, Byron K; Johnson, Fred A
2013-01-01
The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a
Confronting dynamics and uncertainty in optimal decision making for conservation
Williams, Byron K.; Johnson, Fred A.
2013-01-01
The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a
Confronting dynamics and uncertainty in optimal decision making for conservation
Williams, Byron K.; Johnson, Fred A.
2013-06-01
The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a
High Dynamic Optimized Carrier Loop Improvement for Tracking Doppler Rates
Directory of Open Access Journals (Sweden)
Amirhossein Fereidountabar
2015-01-01
Full Text Available Mathematical analysis and optimization of a carrier tracking loop are presented. Due to fast changing of the carrier frequency in some satellite systems, such as Low Earth Orbit (LEO or Global Positioning System (GPS, or some planes like Unmanned Aerial Vehicles (UAVs, high dynamic tracking loops play a very important role. In this paper an optimized tracking loop consisting of a third-order Phase Locked Loop (PLL assisted by a second-order Frequency Locked Loop (FLL for UAVs is proposed and discussed. Based on this structure an optimal loop has been designed. The main advantages of this approach are the reduction of the computation complexity and smaller phase error. The paper shows the simulation results, comparing them with a previous work.
Global optimization for quantum dynamics of few-fermion systems
Li, Xikun; Pecak, Daniel; Sowiński, Tomasz; Sherson, Jacob; Nielsen, Anne E. B.
2018-03-01
Quantum state preparation is vital to quantum computation and quantum information processing tasks. In adiabatic state preparation, the target state is theoretically obtained with nearly perfect fidelity if the control parameter is tuned slowly enough. As this, however, leads to slow dynamics, it is often desirable to be able to carry out processes more rapidly. In this work, we employ two global optimization methods to estimate the quantum speed limit for few-fermion systems confined in a one-dimensional harmonic trap. Such systems can be produced experimentally in a well-controlled manner. We determine the optimized control fields and achieve a reduction in the ramping time of more than a factor of four compared to linear ramping. We also investigate how robust the fidelity is to small variations of the control fields away from the optimized shapes.
Optimally combining dynamical decoupling and quantum error correction.
Paz-Silva, Gerardo A; Lidar, D A
2013-01-01
Quantum control and fault-tolerant quantum computing (FTQC) are two of the cornerstones on which the hope of realizing a large-scale quantum computer is pinned, yet only preliminary steps have been taken towards formalizing the interplay between them. Here we explore this interplay using the powerful strategy of dynamical decoupling (DD), and show how it can be seamlessly and optimally integrated with FTQC. To this end we show how to find the optimal decoupling generator set (DGS) for various subspaces relevant to FTQC, and how to simultaneously decouple them. We focus on stabilizer codes, which represent the largest contribution to the size of the DGS, showing that the intuitive choice comprising the stabilizers and logical operators of the code is in fact optimal, i.e., minimizes a natural cost function associated with the length of DD sequences. Our work brings hybrid DD-FTQC schemes, and their potentially considerable advantages, closer to realization.
A novel technique for active vibration control, based on optimal ...
Indian Academy of Sciences (India)
BEHROUZ KHEIRI SARABI
2017-07-11
Jul 11, 2017 ... an actuator weighing matrix and k f represents the final location of the vector. Optimal control that optimizes the performance index is given by [23–25] u. ∗(k) = −L(k)x. ∗(k) + Lg(k)g(k + 1). (8). Quantities with an asterisk represent optimal quantities. L(k) and Lg(k) are control gains and vector g (k) is given as.
Optimal fringe angle selection for digital fringe projection technique.
Wang, Yajun; Zhang, Song
2013-10-10
Existing digital fringe projection (DFP) systems mainly use either horizontal or vertical fringe patterns for three-dimensional shape measurement. This paper reveals that these two fringe directions are usually not optimal where the phase change is the largest to a given depth variation. We propose a novel and efficient method to determine the optimal fringe angle by projecting a set of horizontal and vertical fringe patterns onto a step-height object and by further analyzing two resultant phase maps. Experiments demonstrate the existence of the optimal angle and the success of the proposed optimal angle determination method.
Statistical designs and response surface techniques for the optimization of chromatographic systems.
Ferreira, Sergio Luis Costa; Bruns, Roy Edward; da Silva, Erik Galvão Paranhos; Dos Santos, Walter Nei Lopes; Quintella, Cristina Maria; David, Jorge Mauricio; de Andrade, Jailson Bittencourt; Breitkreitz, Marcia Cristina; Jardim, Isabel Cristina Sales Fontes; Neto, Benicio Barros
2007-07-27
This paper describes fundamentals and applications of multivariate statistical techniques for the optimization of chromatographic systems. The surface response methodologies: central composite design, Doehlert matrix and Box-Behnken design are discussed and applications of these techniques for optimization of sample preparation steps (extractions) and determination of experimental conditions for chromatographic separations are presented. The use of mixture design for optimization of mobile phases is also related. An optimization example involving a real separation process is exhaustively described. A discussion about model validation is presented. Some applications of other multivariate techniques for optimization of chromatographic methods are also summarized.
TaPT: Temperature-Aware Dynamic Cache Optimization for Embedded Systems
Directory of Open Access Journals (Sweden)
Tosiron Adegbija
2017-12-01
Full Text Available Embedded systems have stringent design constraints, which has necessitated much prior research focus on optimizing energy consumption and/or performance. Since embedded systems typically have fewer cooling options, rising temperature, and thus temperature optimization, is an emergent concern. Most embedded systems only dissipate heat by passive convection, due to the absence of dedicated thermal management hardware mechanisms. The embedded system’s temperature not only affects the system’s reliability, but can also affect the performance, power, and cost. Thus, embedded systems require efficient thermal management techniques. However, thermal management can conflict with other optimization objectives, such as execution time and energy consumption. In this paper, we focus on managing the temperature using a synergy of cache optimization and dynamic frequency scaling, while also optimizing the execution time and energy consumption. This paper provides new insights on the impact of cache parameters on efficient temperature-aware cache tuning heuristics. In addition, we present temperature-aware phase-based tuning, TaPT, which determines Pareto optimal clock frequency and cache configurations for fine-grained execution time, energy, and temperature tradeoffs. TaPT enables autonomous system optimization and also allows designers to specify temperature constraints and optimization priorities. Experiments show that TaPT can effectively reduce execution time, energy, and temperature, while imposing minimal hardware overhead.
Optimal Passive Dynamics for Physical Interaction: Catching a Mass
Directory of Open Access Journals (Sweden)
Kevin Kemper
2013-05-01
Full Text Available For manipulation tasks in uncertain environments, intentionally designed series impedance in mechanical systems can provide significant benefits that cannot be achieved in software. Traditionally, the design of actuated systems revolves around sizing torques, speeds, and control strategies without considering the system’s passive dynamics. However, the passive dynamics of the mechanical system, including inertia, stiffness, and damping along with other parameters such as torque and stroke limits often impose performance limitations that cannot be overcome with software control. In this paper, we develop relationships between an actuator’s passive dynamics and the resulting performance for the purpose of better understanding how to tune the passive dynamics for catching an unexpected object. We use a mathematically optimal controller subject to force limitations to stop the incoming object without breaking contact and bouncing. The use of an optimal controller is important so that our results directly reflect the physical system’s performance. We analytically calculate the maximum velocity that can be caught by a realistic actuator with limitations such as force and stroke limits. The results show that in order to maximize the velocity of an object that can be caught without exceeding the actuator’s torque and stroke limits, a soft spring along with a strong damper will be desired.
Kinematics, Dynamics, and Optimal Control of Pneumatic Hexapod Robot
Directory of Open Access Journals (Sweden)
Long Bai
2017-01-01
Full Text Available Pneumatic hexapod robot is driven by inert gas carried by itself, which has board application prospect in rescue operation of disaster conditions containing flammable gas. Cruising ability is main constraint for practical engineering application which is influenced by kinematics and dynamics character. The matrix operators and pseudospectral method are used to solve dynamics modeling and numerical calculation problem of robot under straight line walking. Kinematics model is numerically solved and relationship of body, joints, and drive cylinders is obtained. With dynamics model and kinematics boundary conditions, the optimal input gas pressure of leg swing and body moving in one step is obtained by pseudospectral method. According to action character of magnetic valve, calculation results of control inputs satisfy engineering design requirements, and cruising ability under finite gas is obtained.
Adaptive particle swarm optimization approach for static and dynamic economic load dispatch
International Nuclear Information System (INIS)
Panigrahi, B.K.; Ravikumar Pandi, V.; Das, Sanjoy
2008-01-01
This paper presents a novel heuristic optimization approach to constrained economic load dispatch (ELD) problems using the adaptive-variable population - PSO technique. The proposed methodology easily takes care of different constraints like transmission losses, dynamic operation constraints (ramp rate limits) and prohibited operating zones and also accounts for non-smoothness of cost functions arising due to the use of multiple fuels. Simulations were performed over various systems with different numbers of generating units, and comparisons are performed with other existing relevant approaches. The findings affirmed the robustness, fast convergence and proficiency of the proposed methodology over other existing techniques
Optimized "detectors" for dynamics analysis in solid-state NMR
Smith, Albert A.; Ernst, Matthias; Meier, Beat H.
2018-01-01
Relaxation in nuclear magnetic resonance (NMR) results from stochastic motions that modulate anisotropic NMR interactions. Therefore, measurement of relaxation-rate constants can be used to characterize molecular-dynamic processes. The motion is often characterized by Markov processes using an auto-correlation function, which is assumed to be a sum of multiple decaying exponentials. We have recently shown that such a model can lead to severe misrepresentation of the real motion, when the real correlation function is more complex than the model. Furthermore, multiple distributions of motion may yield the same set of dynamics data. Therefore, we introduce optimized dynamics "detectors" to characterize motions which are linear combinations of relaxation-rate constants. A detector estimates the average or total amplitude of motion for a range of motional correlation times. The information obtained through the detectors is less specific than information obtained using an explicit model, but this is necessary because the information contained in the relaxation data is ambiguous, if one does not know the correct motional model. On the other hand, if one has a molecular dynamics trajectory, one may calculate the corresponding detector responses, allowing direct comparison to experimental NMR dynamics analysis. We describe how to construct a set of optimized detectors for a given set of relaxation measurements. We then investigate the properties of detectors for a number of different data sets, thus gaining an insight into the actual information content of the NMR data. Finally, we show an example analysis of ubiquitin dynamics data using detectors, using the DIFRATE software.
New numerical methods for open-loop and feedback solutions to dynamic optimization problems
Ghosh, Pradipto
The topic of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each particle in the swarm uses its own memory as well as the knowledge accumulated by the entire swarm to iteratively converge on an optimal or near-optimal solution. It is relatively straightforward to implement and unlike gradient-based solvers, does not require an initial guess or continuity in the problem definition. Although particle swarm optimization has been successfully employed in solving static optimization problems, its application in dynamic optimization, as posed in optimal control theory, is still relatively new. In the first half of this thesis particle swarm optimization is used to generate near-optimal solutions to several nontrivial trajectory optimization problems including thrust programming for minimum fuel, multi-burn spacecraft orbit transfer, and computing minimum-time rest-to-rest trajectories for a robotic manipulator. A distinct feature of the particle swarm optimization implementation in this work is the runtime selection of the optimal solution structure. Optimal trajectories are generated by solving instances of constrained nonlinear mixed-integer programming problems with the swarming technique. For each solved optimal programming problem, the particle swarm optimization result is compared with a nearly exact solution found via a direct method using nonlinear programming. Numerical experiments indicate that swarm search can locate solutions to very great accuracy. The second half of this research develops a new extremal-field approach for synthesizing nearly optimal feedback controllers for optimal control and two-player pursuit-evasion games described by general nonlinear differential equations. A notable revelation from this development
Optimizing Two-level Supersaturated Designs using Swarm Intelligence Techniques.
Phoa, Frederick Kin Hing; Chen, Ray-Bing; Wang, Weichung; Wong, Weng Kee
Supersaturated designs (SSDs) are often used to reduce the number of experimental runs in screening experiments with a large number of factors. As more factors are used in the study, the search for an optimal SSD becomes increasingly challenging because of the large number of feasible selection of factor level settings. This paper tackles this discrete optimization problem via an algorithm based on swarm intelligence. Using the commonly used E ( s 2 ) criterion as an illustrative example, we propose an algorithm to find E ( s 2 )-optimal SSDs by showing that they attain the theoretical lower bounds in Bulutoglu and Cheng (2004) and Bulutoglu (2007). We show that our algorithm consistently produces SSDs that are at least as efficient as those from the traditional CP exchange method in terms of computational effort, frequency of finding the E ( s 2 )-optimal SSD and also has good potential for finding D 3 -, D 4 - and D 5 -optimal SSDs.
INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization
Energy Technology Data Exchange (ETDEWEB)
Groer, Christopher S [ORNL; Sullivan, Blair D [ORNL; Weerapurage, Dinesh P [ORNL
2012-10-01
It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.
Genetic algorithm optimization for dynamic construction site layout planning
Directory of Open Access Journals (Sweden)
Farmakis Panagiotis M.
2018-02-01
Full Text Available The dynamic construction site layout planning (DCSLP problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental considerations resulting from facilities’ operations and interconnections. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time- hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenarios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indicate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process.
Optimization of Algorithms Using Extensions of Dynamic Programming
AbouEisha, Hassan M.
2017-04-09
We study and answer questions related to the complexity of various important problems such as: multi-frontal solvers of hp-adaptive finite element method, sorting and majority. We advocate the use of dynamic programming as a viable tool to study optimal algorithms for these problems. The main approach used to attack these problems is modeling classes of algorithms that may solve this problem using a discrete model of computation then defining cost functions on this discrete structure that reflect different complexity measures of the represented algorithms. As a last step, dynamic programming algorithms are designed and used to optimize those models (algorithms) and to obtain exact results on the complexity of the studied problems. The first part of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic programming algorithms for multi-stage and bi-criteria optimization of element partition trees. In addition, it presents results based on optimal element partition trees for famous benchmark meshes such as: meshes with point and edge singularities. New improved heuristics for those benchmark meshes were ob- tained based on insights of the optimal results found by our algorithms. The second part of the thesis starts by introducing a general problem where different problems can be reduced to and show how to use a decision table to model such problem. We describe how decision trees and decision tests for this table correspond to adaptive and non-adaptive algorithms for the original problem. We present exact bounds on the average time complexity of adaptive algorithms for the eight elements sorting problem. Then bounds on adaptive and non-adaptive algorithms for a variant of the majority problem are introduced. Adaptive algorithms are modeled as decision trees whose depth
Optimized maritime emergency resource allocation under dynamic demand.
Directory of Open Access Journals (Sweden)
Wenfen Zhang
Full Text Available Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.
Optimizing spread dynamics on graphs by message passing
International Nuclear Information System (INIS)
Altarelli, F; Braunstein, A; Dall’Asta, L; Zecchina, R
2013-01-01
Cascade processes are responsible for many important phenomena in natural and social sciences. Simple models of irreversible dynamics on graphs, in which nodes activate depending on the state of their neighbors, have been successfully applied to describe cascades in a large variety of contexts. Over the past decades, much effort has been devoted to understanding the typical behavior of the cascades arising from initial conditions extracted at random from some given ensemble. However, the problem of optimizing the trajectory of the system, i.e. of identifying appropriate initial conditions to maximize (or minimize) the final number of active nodes, is still considered to be practically intractable, with the only exception being models that satisfy a sort of diminishing returns property called submodularity. Submodular models can be approximately solved by means of greedy strategies, but by definition they lack cooperative characteristics which are fundamental in many real systems. Here we introduce an efficient algorithm based on statistical physics for the optimization of trajectories in cascade processes on graphs. We show that for a wide class of irreversible dynamics, even in the absence of submodularity, the spread optimization problem can be solved efficiently on large networks. Analytic and algorithmic results on random graphs are complemented by the solution of the spread maximization problem on a real-world network (the Epinions consumer reviews network). (paper)
Complicated problem solution techniques in optimal parameter searching
International Nuclear Information System (INIS)
Gergel', V.P.; Grishagin, V.A.; Rogatneva, E.A.; Strongin, R.G.; Vysotskaya, I.N.; Kukhtin, V.V.
1992-01-01
An algorithm is presented of a global search for numerical solution of multidimentional multiextremal multicriteria optimization problems with complicated constraints. A boundedness of object characteristic changes is assumed at restricted changes of its parameters (Lipschitz condition). The algorithm was realized as a computer code. The algorithm was realized as a computer code. The programme was used to solve in practice the different applied optimization problems. 10 refs.; 3 figs
Directory of Open Access Journals (Sweden)
Kazem Mohammadi- Aghdam
2015-10-01
Full Text Available This paper proposes the application of a new version of the heuristic particle swarm optimization (PSO method for designing water distribution networks (WDNs. The optimization problem of looped water distribution networks is recognized as an NP-hard combinatorial problem which cannot be easily solved using traditional mathematical optimization techniques. In this paper, the concept of dynamic swarm size is considered in an attempt to increase the convergence speed of the original PSO algorithm. In this strategy, the size of the swarm is dynamically changed according to the iteration number of the algorithm. Furthermore, a novel mutation approach is introduced to increase the diversification property of the PSO and to help the algorithm to avoid trapping in local optima. The new version of the PSO algorithm is called dynamic mutated particle swarm optimization (DMPSO. The proposed DMPSO is then applied to solve WDN design problems. Finally, two illustrative examples are used for comparison to verify the efficiency of the proposed DMPSO as compared to other intelligent algorithms.
Comparing dynamical systems concepts and techniques for biomechanical analysis
van Emmerik, Richard E.A.; Ducharme, Scott W.; Amado, Avelino C.; Hamill, Joseph
2016-01-01
Traditional biomechanical analyses of human movement are generally derived from linear mathematics. While these methods can be useful in many situations, they do not describe behaviors in human systems that are predominately nonlinear. For this reason, nonlinear analysis methods based on a dynamical systems approach have become more prevalent in recent literature. These analysis techniques have provided new insights into how systems (1) maintain pattern stability, (2) transition into new stat...
Dynamic Mechanical Testing Techniques for Cortical and Cancellous Bone
Cloete, Trevor
2017-06-01
Bone fracture typically occurs as an impact loading event (sporting accidents, vehicle collisions), the simulation of which requires in-depth understanding of dynamic bone behavior. Bone is a natural composite material with a complex multi length-scale hierarchical microstructure. At a macroscopic level, it is classified into hard/compact cortical bone and soft/spongy cancellous (trabecular) bone, though both are low-impedance materials relative to steels. Cortical bone is predominant in long bones, while in complex bone geometries (joints, flat bones) a cancellous bone core supports a thin cortical shell. Bone has primarily been studied at quasi-static strain rates (ɛ˙ failure, with interrupted quasi-static tests revealing a strong microstructure dependence. However, bone specimens are typically destroyed during dynamic tests, leading to a lack of dynamic microstructural damage investigations. In this paper, a short overview of dynamic bone testing is presented to give context to the challenges of testing low impedance, strain-rate dependent, non-linear, visco-elastic-brittle materials. Recent state-of-the-art experimental developments in dynamic bone testing are reviewed, with emphasis on pulse shaping, momentum trapping and ISR testing. These techniques allow for dynamic bone testing at small strains and near-constant strain rates with intact specimen recovery. The results are compared to those obtained with varying strain rate tests. Interrupted dynamic test results with microstructural analysis of the recovered specimens are presented and discussed. The paper concludes with a discussion of the experimental and modeling challenges that lie ahead in the field of dynamic bone behavior. The financial assistance of the National Research Foundation and the University of Cape Town towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at are those of the author alone.
Kalman filter techniques for accelerated Cartesian dynamic cardiac imaging.
Feng, Xue; Salerno, Michael; Kramer, Christopher M; Meyer, Craig H
2013-05-01
In dynamic MRI, spatial and temporal parallel imaging can be exploited to reduce scan time. Real-time reconstruction enables immediate visualization during the scan. Commonly used view-sharing techniques suffer from limited temporal resolution, and many of the more advanced reconstruction methods are either retrospective, time-consuming, or both. A Kalman filter model capable of real-time reconstruction can be used to increase the spatial and temporal resolution in dynamic MRI reconstruction. The original study describing the use of the Kalman filter in dynamic MRI was limited to non-Cartesian trajectories because of a limitation intrinsic to the dynamic model used in that study. Here the limitation is overcome, and the model is applied to the more commonly used Cartesian trajectory with fast reconstruction. Furthermore, a combination of the Kalman filter model with Cartesian parallel imaging is presented to further increase the spatial and temporal resolution and signal-to-noise ratio. Simulations and experiments were conducted to demonstrate that the Kalman filter model can increase the temporal resolution of the image series compared with view-sharing techniques and decrease the spatial aliasing compared with TGRAPPA. The method requires relatively little computation, and thus is suitable for real-time reconstruction. Copyright © 2012 Wiley Periodicals, Inc.
Comparison of metaheuristic optimization techniques for BWR fuel reloads pattern design
International Nuclear Information System (INIS)
François, Juan-Luis; Ortiz-Servin, Juan José; Martín-del-Campo, Cecilia; Castillo, Alejandro; Esquivel-Estrada, Jaime
2013-01-01
Highlights: ► This paper shows a performance comparison of several optimization techniques for fuel reload in BWR. ► Genetic Algorithms, Neural Networks, Tabu Search and several Ant Algorithms were used. ► All optimization techniques were executed under same conditions: objective function and an equilibrium cycle. ► Fuel bundles with minor actinides were loaded into the core. ► Tabu search and Ant System were the best optimization technique for the studied problem. -- Abstract: Fuel reload pattern optimization is a crucial fuel management activity in nuclear power reactors. Along the years, a lot of work has been done in this area. In particular, several metaheuristic optimization techniques have been applied with good results for boiling water reactors (BWRs). In this paper, a comparison of different metaheuristics: genetic algorithms, tabu search, recurrent neural networks and several ant colony optimization techniques, were applied, in order to evaluate their performance. The optimization of an equilibrium core of a BWR, loaded with mixed oxide fuel composed of plutonium and minor actinides, was selected to be optimized. Results show that the best average values are obtained with the recurrent neural networks technique, meanwhile the best fuel reload was obtained with tabu search. However, according to the number of objective functions evaluated, the two fastest optimization techniques are tabu search and Ant System.
Analysis and optimization of a proton exchange membrane fuel cell using modeling techniques
International Nuclear Information System (INIS)
Torre Valdés, Ing. Raciel de la; García Parra, MSc. Lázaro Roger; González Rodríguez, MSc. Daniel
2015-01-01
This paper proposes a three-dimensional, non-isothermal and steady-state model of Proton Exchange Membrane Fuel Cell using Computational Fluid Dynamic techniques, specifically ANSYS FLUENT 14.5. It's considered multicomponent diffusion and two-phasic flow. The model was compared with experimental published data and with another model. The operation parameters: reactants pressure and temperature, gases flow direction, gas diffusion layer and catalyst layer porosity, reactants humidification and oxygen concentration are analyzed. The model allows the fuel cell design optimization taking in consideration the channels dimensions, the channels length and the membrane thickness. Furthermore, fuel cell performance is analyzed working with SPEEK membrane, an alternative electrolyte to Nafion. In order to carry on membrane material study, it's necessary to modify the expression that describes the electrolyte ionic conductivity. It's found that the device performance has got a great sensibility to pressure, temperature, reactant humidification and oxygen concentration variations. (author)
Marwala, Tshilidzi
2010-01-01
Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...
Optimal control of peridinin excited-state dynamics
Dietzek, Benjamin; Chábera, Pavel; Hanf, Robert; Tschierlei, Stefanie; Popp, Jürgen; Pascher, Torbjörn; Yartsev, Arkady; Polívka, Tomáš
2010-07-01
Optimal control is applied to study the excited-state relaxation of the carbonyl-carotenoid peridinin in solution. Phase-shaping of the excitation pulses is employed to influence the photoinduced reaction dynamics of peridinin. The outcome of various control experiments using different experimentally imposed fitness parameters is discussed. Furthermore, the effects of pump-wavelength and different solvents on the control efficiency are presented. The data show that excited-state population within either the S 1 or the ICT state can be reduced significantly by applying optimal control, while the efficiency of control decreases upon excitation into the low-energy side of the absorption band. However, we are unable to alter the ratio of S 1 and ICT population or increase the population of either state compared to excitation with a transform-limited pulse. We compare the results to various control mechanisms and argue that characteristic low-wavenumber modes are relevant for the photochemistry of peridinin.
Determination of dynamic fracture toughness using a new experimental technique
Cady, Carl M.; Liu, Cheng; Lovato, Manuel L.
2015-09-01
In other studies dynamic fracture toughness has been measured using Charpy impact and modified Hopkinson Bar techniques. In this paper results will be shown for the measurement of fracture toughness using a new test geometry. The crack propagation velocities range from ˜0.15 mm/s to 2.5 m/s. Digital image correlation (DIC) will be the technique used to measure both the strain and the crack growth rates. The boundary of the crack is determined using the correlation coefficient generated during image analysis and with interframe timing the crack growth rate and crack opening can be determined. A comparison of static and dynamic loading experiments will be made for brittle polymeric materials. The analysis technique presented by Sammis et al. [1] is a semi-empirical solution, however, additional Linear Elastic Fracture Mechanics analysis of the strain fields generated as part of the DIC analysis allow for the more commonly used method resembling the crack tip opening displacement (CTOD) experiment. It should be noted that this technique was developed because limited amounts of material were available and crack growth rates were to fast for a standard CTOD method.
Determination of dynamic fracture toughness using a new experimental technique
Directory of Open Access Journals (Sweden)
Cady Carl M.
2015-01-01
Full Text Available In other studies dynamic fracture toughness has been measured using Charpy impact and modified Hopkinson Bar techniques. In this paper results will be shown for the measurement of fracture toughness using a new test geometry. The crack propagation velocities range from ∼0.15 mm/s to 2.5 m/s. Digital image correlation (DIC will be the technique used to measure both the strain and the crack growth rates. The boundary of the crack is determined using the correlation coefficient generated during image analysis and with interframe timing the crack growth rate and crack opening can be determined. A comparison of static and dynamic loading experiments will be made for brittle polymeric materials. The analysis technique presented by Sammis et al. [1] is a semi-empirical solution, however, additional Linear Elastic Fracture Mechanics analysis of the strain fields generated as part of the DIC analysis allow for the more commonly used method resembling the crack tip opening displacement (CTOD experiment. It should be noted that this technique was developed because limited amounts of material were available and crack growth rates were to fast for a standard CTOD method.
Laser sources and techniques for spectroscopy and dynamics
Energy Technology Data Exchange (ETDEWEB)
Kung, A.H. [Lawrence Berkeley Laboratory, CA (United States)
1993-12-01
This program focuses on the development of novel laser and spectroscopic techniques in the IR, UV, and VUV regions for studying combustion related molecular dynamics at the microscopic level. Laser spectroscopic techniques have proven to be extremely powerful in the investigation of molecular processes which require very high sensitivity and selectivity. The authors approach is to use quantum electronic and non-linear optical techniques to extend the spectral coverage and to enhance the optical power of ultrahigh resolution laser sources so as to obtain and analyze photoionization, fluorescence, and photoelectron spectra of jet-cooled free radicals and of reaction products resulting from unimolecular and bimolecular dissociations. New spectroscopic techniques are developed with these sources for the detection of optically thin and often short-lived species. Recent activities center on regenerative amplification of high resolution solid-state lasers, development of tunable high power mid-IR lasers and short-pulse UV/VUV tunable lasers, and development of a multipurpose high-order suppressor crossed molecular beam apparatus for use with synchrotron radiation sources. This program also provides scientific and technical support within the Chemical Sciences Division to the development of LBL`s Combustion Dynamics Initiative.
Model-based dynamic control and optimization of gas networks
Energy Technology Data Exchange (ETDEWEB)
Hofsten, Kai
2001-07-01
This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum
Comparing dynamical systems concepts and techniques for biomechanical analysis
Directory of Open Access Journals (Sweden)
Richard E.A. van Emmerik
2016-03-01
Full Text Available Traditional biomechanical analyses of human movement are generally derived from linear mathematics. While these methods can be useful in many situations, they do not describe behaviors in human systems that are predominately nonlinear. For this reason, nonlinear analysis methods based on a dynamical systems approach have become more prevalent in recent literature. These analysis techniques have provided new insights into how systems (1 maintain pattern stability, (2 transition into new states, and (3 are governed by short- and long-term (fractal correlational processes at different spatio-temporal scales. These different aspects of system dynamics are typically investigated using concepts related to variability, stability, complexity, and adaptability. The purpose of this paper is to compare and contrast these different concepts and demonstrate that, although related, these terms represent fundamentally different aspects of system dynamics. In particular, we argue that variability should not uniformly be equated with stability or complexity of movement. In addition, current dynamic stability measures based on nonlinear analysis methods (such as the finite maximal Lyapunov exponent can reveal local instabilities in movement dynamics, but the degree to which these local instabilities relate to global postural and gait stability and the ability to resist external perturbations remains to be explored. Finally, systematic studies are needed to relate observed reductions in complexity with aging and disease to the adaptive capabilities of the movement system and how complexity changes as a function of different task constraints.
An Optimal Dynamic Data Structure for Stabbing-Semigroup Queries
DEFF Research Database (Denmark)
Agarwal, Pankaj K.; Arge, Lars; Kaplan, Haim
2012-01-01
{R}$, the stabbing-semigroup query asks for computing $\\sum_{s \\in S(q)} \\omega(s)$. We propose a linear-size dynamic data structure, under the pointer-machine model, that answers queries in worst-case $O(\\log n)$ time and supports both insertions and deletions of intervals in amortized $O(\\log n)$ time....... It is the first data structure that attains the optimal $O(\\log n)$ bound for all three operations. Furthermore, our structure can easily be adapted to external memory, where we obtain a linear-size structure that answers queries and supports updates in $O(\\log_B n)$ I/Os, where B is the disk block size....... For the restricted case of a nested family of intervals (either every pair of intervals is disjoint or one contains the other), we present a simpler solution based on dynamic trees...
Optimal dynamic pricing and replenishment policies for deteriorating items
Directory of Open Access Journals (Sweden)
Masoud Rabbani
2014-08-01
Full Text Available Marketing strategies and proper inventory replenishment policies are often incorporated by enterprises to stimulate demand and maximize profit. The aim of this paper is to represent an integrated model for dynamic pricing and inventory control of deteriorating items. To reflect the dynamic characteristic of the problem, the selling price is defined as a time-dependent function of the initial selling price and the discount rate. In this regard, the price is exponentially discounted to compensate negative impact of the deterioration. The planning horizon is assumed to be infinite and the deterioration rate is time-dependent. In addition to price, the demand rate is dependent on advertisement as a powerful marketing tool. Several theoretical results and an iterative solution algorithm are developed to provide the optimal solution. Finally, to show validity of the model and illustrate the solution procedure, numerical results are presented.
Dynamic Simulation and Optimization of Nuclear Hydrogen Production Systems
Energy Technology Data Exchange (ETDEWEB)
Paul I. Barton; Mujid S. Kaximi; Georgios Bollas; Patricio Ramirez Munoz
2009-07-31
This project is part of a research effort to design a hydrogen plant and its interface with a nuclear reactor. This project developed a dynamic modeling, simulation and optimization environment for nuclear hydrogen production systems. A hybrid discrete/continuous model captures both the continuous dynamics of the nuclear plant, the hydrogen plant, and their interface, along with discrete events such as major upsets. This hybrid model makes us of accurate thermodynamic sub-models for the description of phase and reaction equilibria in the thermochemical reactor. Use of the detailed thermodynamic models will allow researchers to examine the process in detail and have confidence in the accurary of the property package they use.
4500 V SPT+ IGBT optimization on static and dynamic losses
International Nuclear Information System (INIS)
Dai Qingyun; Tian Xiaoli; Zhang Wenliang; Lu Shuojin; Zhu Yangjun
2015-01-01
This paper concerns the need for improving the static and dynamic performance of the high voltage insulated gate bipolar transistor (HV IGBTs). A novel structure with a carrier stored layer on the cathode side, known as an enhanced planar IGBT of the 4500 V voltage class is investigated. With the adoption of a soft punch through (SPT) concept as the vertical structure and an enhanced planar concept as the top structure, signed as SPT + IGBT, the simulation results indicate the turn-off switching waveform of the 4500 V SPT + IGBT is soft and also realizes an improved trade-off relationship between on-state voltage drop (V on ) and turn-off loss (E off ) in comparison with the SPT IGBT. Attention is also paid to the influences caused by different carrier stored layer doping dose on static and dynamic performances, to optimize on-state and switching losses of SPT + IGBT. (paper)
Optimal environmental policy and the dynamic property in LDCs
Directory of Open Access Journals (Sweden)
Masahiro Yabuta
2002-01-01
Full Text Available This paper has provided a model framework of foreign assistance policy in the context of dynamic optimal control and investigated the environmental policies in LDCs that received some financial support from abroad. The model framework features a specific behavior of the social planner who determines the level of voluntary expenditure for preservation of natural environment. Because more financial needs for natural environmental protection means less allowance of growth-oriented investment, the social planner confronts a trade-off problem between economic growth and environmental preservation. To tackle with this clearly, we have built a dynamic model with two control variables: per-capita consumption and voluntary expenditure for natural environment.
Optimal Component Lumping: problem formulation and solution techniques
DEFF Research Database (Denmark)
Lin, Bao; Leibovici, Claude F.; Jørgensen, Sten Bay
2008-01-01
This paper presents a systematic method for optimal lumping of a large number of components in order to minimize the loss of information. In principle, a rigorous composition-based model is preferable to describe a system accurately. However, computational intensity and numerical issues restrict...... such applications in process modeling, simulation and design. A pseudo-component approach that lumps a large number of components in a system into a much smaller number of hypothetical groups reduces the dimensionality at the cost of losing information. Moreover, empirical and heuristic approaches are commonly used...... significantly reduces the number of independent variables. The application to a system with 144 components demonstrates that the optimal lumping problem can be efficiently solved with a stochastic optimization method, Tabu Search (TS) algorithm. The case study also reveals that the discrete formulation...
Selection of a suitable multiresponse optimization technique for turning operation
Directory of Open Access Journals (Sweden)
I. Nayak
2016-01-01
Full Text Available The present work deals with the comparison of four multi response optimization methods, viz. multiple response signal-to-noise (MRSN ratio, weighted signal-to-noise (WSN ratio, Grey relational analysis (GRA, and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian methods taking a case study in turning mild steel specimen using HSS cutting tool. The various factors like cutting speed, feed rate, depth of cut and coolant flow rate are considered as the input process variables, while the material removal rate (MRR, surface roughness (SR and specific energy consumption (SEC are considered as various performance characteristics. One set of experimental data is analyzed using the standardized procedures. The optimization performances of these four methods are compared. The results show that MRSN ratio method proves to be the best optimization method. It is found that the feed rate has a highest impact on the overall performance as compared to other process parameters.
Optimal Technique for Abdominal Fascial Closure in Liver Transplant Patients
Directory of Open Access Journals (Sweden)
Unal Aydin
2010-01-01
Conclusion: Our results indicate that the novel technique used in this study contributed to overcoming early and late postoperative complications associated with closure of the abdominal fascia in liver transplant patients. In addition, this new technique has proven to be easily applicable, faster, safer and efficient in these patients; it is also potentially useful for conventional surgery.
Machine learning techniques for optical communication system optimization
DEFF Research Database (Denmark)
Zibar, Darko; Wass, Jesper; Thrane, Jakob
In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction.......In this paper, machine learning techniques relevant to optical communication are presented and discussed. The focus is on applying machine learning tools to optical performance monitoring and performance prediction....
Adjoint Techniques for Topology Optimization of Structures Under Damage Conditions
Akgun, Mehmet A.; Haftka, Raphael T.
2000-01-01
The objective of this cooperative agreement was to seek computationally efficient ways to optimize aerospace structures subject to damage tolerance criteria. Optimization was to involve sizing as well as topology optimization. The work was done in collaboration with Steve Scotti, Chauncey Wu and Joanne Walsh at the NASA Langley Research Center. Computation of constraint sensitivity is normally the most time-consuming step of an optimization procedure. The cooperative work first focused on this issue and implemented the adjoint method of sensitivity computation (Haftka and Gurdal, 1992) in an optimization code (runstream) written in Engineering Analysis Language (EAL). The method was implemented both for bar and plate elements including buckling sensitivity for the latter. Lumping of constraints was investigated as a means to reduce the computational cost. Adjoint sensitivity computation was developed and implemented for lumped stress and buckling constraints. Cost of the direct method and the adjoint method was compared for various structures with and without lumping. The results were reported in two papers (Akgun et al., 1998a and 1999). It is desirable to optimize topology of an aerospace structure subject to a large number of damage scenarios so that a damage tolerant structure is obtained. Including damage scenarios in the design procedure is critical in order to avoid large mass penalties at later stages (Haftka et al., 1983). A common method for topology optimization is that of compliance minimization (Bendsoe, 1995) which has not been used for damage tolerant design. In the present work, topology optimization is treated as a conventional problem aiming to minimize the weight subject to stress constraints. Multiple damage configurations (scenarios) are considered. Each configuration has its own structural stiffness matrix and, normally, requires factoring of the matrix and solution of the system of equations. Damage that is expected to be tolerated is local
Directory of Open Access Journals (Sweden)
Wei Wang
2015-01-01
Full Text Available This paper presented a parameter estimation method based on a coupled hydromechanical model of dynamic compaction and the Pareto multiobjective optimization technique. The hydromechanical model of dynamic compaction is established in the FEM program LS-DYNA. The multiobjective optimization algorithm, Nondominated Sorted Genetic Algorithm (NSGA-IIa, is integrated with the numerical model to identify soil parameters using multiple sources of field data. A field case study is used to demonstrate the capability of the proposed method. The observed pore water pressure and crater depth at early blow of dynamic compaction are simultaneously used to estimate the soil parameters. Robustness of the back estimated parameters is further illustrated by a forward prediction. Results show that the back-analyzed soil parameters can reasonably predict lateral displacements and give generally acceptable predictions of dynamic compaction for an adjacent location. In addition, for prediction of ground response of the dynamic compaction at continuous blows, the prediction based on the second blow is more accurate than the first blow due to the occurrence of the hardening and strengthening of soil during continuous compaction.
[X-ray radiographic imaging technique with high dynamic range].
Liu, Bin; Wang, Li-Ming; Su, Xin-Yan
2014-04-01
In conventional X-ray radiographic imaging system with a fixed energy parameter, the acquired X-ray images are usually overexposed and have no useful information available. It is due to some constraints, like special structure of component, different attenuation coefficients of materials and dynamic range of optoelectronic devices. When maximum of transmitted X-ray luminous exceed capacity limitation of X-ray radiographic imaging system in one scene, the device up to saturate. Also when minimum of transmitted X-ray luminous is below the thermal noise level of imaging system, no useful information is available for imaging. To solve the problem of difficulties in acquiring transmitted X-ray luminous in a wide dynamic range by conventional X-ray radiographic imaging system, we put forward a new X-ray radiographic imaging technique with high dynamic range based on adjusting tube voltage. In the article, the influence by charge capacity of X-ray radiographic imaging system on effective irradiating thickness is analyzed. Through experiments of some standard samples, we gained the relationship between voltage range of X-ray tube and materials or structure of component for best testing sensitivity. Then we put forward an adjusting strategy of tube voltage and effective subgraphs extraction method from acquired raw X-ray images. By the mentioned method, we carried out X-ray radiographic imaging experiments with high dynamic range for components with thickness from 0 to 20 mm. The results show that X-ray radiographic imaging technique with high dynamic range is effective to realize imaging for some components with different thickness. It is available for us to find more detailed projection information from fusion images.
An improved technique for the prediction of optimal image resolution ...
African Journals Online (AJOL)
Past studies to predict optimal image resolution required for generating spatial information for savannah ecosystems have yielded different outcomes, hence providing a knowledge gap that was investigated in the present study. The postulation, for the present study, was that by graphically solving two simultaneous ...
Optimization of an embedded rail structure using a numerical technique
Markine, V.L.; De Man, A.P.; Esveld, C.
2000-01-01
This paper presents several steps of a procedure for design of a railway track aiming at the development of optimal track structures under various predefined service and environmental conditions. The structural behavior of the track is analyzed using a finite element model in which the track and a
Simulation error propagation for a dynamic rod worth measurement technique
International Nuclear Information System (INIS)
Kastanya, D.F.; Turinsky, P.J.
1996-01-01
KRSKO nuclear station, subsequently adapted by Westinghouse, introduced the dynamic rod worth measurement (DRWM) technique for measuring pressurized water reactor rod worths. This technique has the potential for reduced test time and primary loop waste water versus alternatives. The measurement is performed starting from a slightly supercritical state with all rods out (ARO), driving a bank in at the maximum stepping rate, and recording the ex-core detectors responses and bank position as a function of time. The static bank worth is obtained by (1) using the ex-core detectors' responses to obtain the core average flux (2) using the core average flux in the inverse point-kinetics equations to obtain the dynamic bank worth (3) converting the dynamic bank worth to the static bank worth. In this data interpretation process, various calculated quantities obtained from a core simulator are utilized. This paper presents an analysis of the sensitivity to the impact of core simulator errors on the deduced static bank worth
Throughput optimization for dual collaborative spectrum sensing with dynamic scheduling
Cui, Cuimei; Yang, Dezhi
2017-07-01
Cognitive radio technology is envisaged to alleviate both spectrum inefficiency and spectrum scarcity problems by exploiting the existing licensed spectrum opportunistically. However, cognitive radio ad hoc networks (CRAHNs) impose unique challenges due to the high dynamic scheduling in the available spectrum, diverse quality of service (QOS) requirements, as well as hidden terminals and shadow fading issues in a harsh radio environment. To solve these problems, this paper proposes a dynamic and variable time-division multiple-access scheduling mechanism (DV-TDMA) incorporated with dual collaborative spectrum sensing scheme for CRAHNs. This study involves the cross-layered cooperation between the Physical (PHY) layer and Medium Access Control (MAC) layer under the consideration of average sensing time, sensing accuracy and the average throughput of cognitive radio users (CRs). Moreover, multiple-objective optimization algorithm is proposed to maximize the average throughput of CRs while still meeting QOS requirements on sensing time and detection error. Finally, performance evaluation is conducted through simulations, and the simulation results reveal that this optimization algorithm can significantly improve throughput and sensing accuracy and reduce average sensing time.
Aircraft path planning for optimal imaging using dynamic cost functions
Christie, Gordon; Chaudhry, Haseeb; Kochersberger, Kevin
2015-05-01
Unmanned aircraft development has accelerated with recent technological improvements in sensing and communications, which has resulted in an "applications lag" for how these aircraft can best be utilized. The aircraft are becoming smaller, more maneuverable and have longer endurance to perform sensing and sampling missions, but operating them aggressively to exploit these capabilities has not been a primary focus in unmanned systems development. This paper addresses a means of aerial vehicle path planning to provide a realistic optimal path in acquiring imagery for structure from motion (SfM) reconstructions and performing radiation surveys. This method will allow SfM reconstructions to occur accurately and with minimal flight time so that the reconstructions can be executed efficiently. An assumption is made that we have 3D point cloud data available prior to the flight. A discrete set of scan lines are proposed for the given area that are scored based on visibility of the scene. Our approach finds a time-efficient path and calculates trajectories between scan lines and over obstacles encountered along those scan lines. Aircraft dynamics are incorporated into the path planning algorithm as dynamic cost functions to create optimal imaging paths in minimum time. Simulations of the path planning algorithm are shown for an urban environment. We also present our approach for image-based terrain mapping, which is able to efficiently perform a 3D reconstruction of a large area without the use of GPS data.
Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization
Directory of Open Access Journals (Sweden)
Weishang Gao
2013-01-01
Full Text Available Evolutionary algorithms (EAs were shown to be effective for complex constrained optimization problems. However, inflexible exploration-exploitation and improper penalty in EAs with penalty function would lead to losing the global optimum nearby or on the constrained boundary. To determine an appropriate penalty coefficient is also difficult in most studies. In this paper, we propose a bidirectional dynamic diversity evolutionary algorithm (Bi-DDEA with multiagents guiding exploration-exploitation through local extrema to the global optimum in suitable steps. In Bi-DDEA potential advantage is detected by three kinds of agents. The scale and the density of agents will change dynamically according to the emerging of potential optimal area, which play an important role of flexible exploration-exploitation. Meanwhile, a novel double optimum estimation strategy with objective fitness and penalty fitness is suggested to compute, respectively, the dominance trend of agents in feasible region and forbidden region. This bidirectional evolving with multiagents can not only effectively avoid the problem of determining penalty coefficient but also quickly converge to the global optimum nearby or on the constrained boundary. By examining the rapidity and veracity of Bi-DDEA across benchmark functions, the proposed method is shown to be effective.
Optimal PID control of a brushless DC motor using PSO and BF techniques
Directory of Open Access Journals (Sweden)
H.E.A. Ibrahim
2014-06-01
Full Text Available This paper presents a Particle Swarm Optimization (PSO technique and bacterial foraging (BF technique for determining the optimal parameters of (PID controller for speed control of a brushless DC motor (BLDC where the (BLDC motor is modeled in simulink in Matlab. The proposed technique was more efficient in improving the step response characteristics as well as reducing the steady-state error, rise time, settling time and maximum overshoot.
Optimal PID control of a brushless DC motor using PSO and BF techniques
H.E.A. Ibrahim; F.N. Hassan; Anas O. Shomer
2014-01-01
This paper presents a Particle Swarm Optimization (PSO) technique and bacterial foraging (BF) technique for determining the optimal parameters of (PID) controller for speed control of a brushless DC motor (BLDC) where the (BLDC) motor is modeled in simulink in Matlab. The proposed technique was more efficient in improving the step response characteristics as well as reducing the steady-state error, rise time, settling time and maximum overshoot.
A novel technique for active vibration control, based on optimal ...
Indian Academy of Sciences (India)
BEHROUZ KHEIRI SARABI
2017-07-11
Jul 11, 2017 ... Active vibration control; linear quadratic tracking; two-degrees of freedom system. PACS No. 02.30.Yy. 1. Introduction. Demand for energy is ever increasing and researchers are trying hard to make lightweight ... finite actuator dynamics for flexible structures to over- come instability. Stability based on the ...
Purchasing and inventory management techniques for optimizing inventory investment
International Nuclear Information System (INIS)
McFarlane, I.; Gehshan, T.
1993-01-01
In an effort to reduce operations and maintenance costs among nuclear plants, many utilities are taking a closer look at their inventory investment. Various approaches for inventory reduction have been used and discussed, but these approaches are often limited to an inventory management perspective. Interaction with purchasing and planning personnel to reduce inventory investment is a necessity in utility efforts to become more cost competitive. This paper addresses the activities that purchasing and inventory management personnel should conduct in an effort to optimize inventory investment while maintaining service-level goals. Other functions within a materials management organization, such as the warehousing and investment recovery functions, can contribute to optimizing inventory investment. However, these are not addressed in this paper because their contributions often come after inventory management and purchasing decisions have been made
Optimal fuel loading pattern design using artificial intelligence techniques
International Nuclear Information System (INIS)
Kim, Han Gon; Chang, Soon Heung; Lee, Byung Ho
1993-01-01
The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (Author)
Optimal Dynamic Strategies for Index Tracking and Algorithmic Trading
Ward, Brian
In this thesis we study dynamic strategies for index tracking and algorithmic trading. Tracking problems have become ever more important in Financial Engineering as investors seek to precisely control their portfolio risks and exposures over different time horizons. This thesis analyzes various tracking problems and elucidates the tracking errors and strategies one can employ to minimize those errors and maximize profit. In Chapters 2 and 3, we study the empirical tracking properties of exchange traded funds (ETFs), leveraged ETFs (LETFs), and futures products related to spot gold and the Chicago Board Option Exchange (CBOE) Volatility Index (VIX), respectively. These two markets provide interesting and differing examples for understanding index tracking. We find that static strategies work well in the nonleveraged case for gold, but fail to track well in the corresponding leveraged case. For VIX, tracking via neither ETFs, nor futures\\ portfolios succeeds, even in the nonleveraged case. This motivates the need for dynamic strategies, some of which we construct in these two chapters and further expand on in Chapter 4. There, we analyze a framework for index tracking and risk exposure control through financial derivatives. We derive a tracking condition that restricts our exposure choices and also define a slippage process that characterizes the deviations from the index over longer horizons. The framework is applied to a number of models, for example, Black Scholes model and Heston model for equity index tracking, as well as the Square Root (SQR) model and the Concatenated Square Root (CSQR) model for VIX tracking. By specifying how each of these models fall into our framework, we are able to understand the tracking errors in each of these models. Finally, Chapter 5 analyzes a tracking problem of a different kind that arises in algorithmic trading: schedule following for optimal execution. We formulate and solve a stochastic control problem to obtain the optimal
Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization
Directory of Open Access Journals (Sweden)
Haitao Xu
2018-01-01
Full Text Available As we all know, there are a great number of optimization problems in the world. One of the relatively complicated and high-level problems is the vehicle routing problem (VRP. Dynamic vehicle routing problem (DVRP is a major variant of VRP, and it is closer to real logistic scene. In DVRP, the customers’ demands appear with time, and the unserved customers’ points must be updated and rearranged while carrying out the programming paths. Owing to the complexity and significance of the problem, DVRP applications have grabbed the attention of researchers in the past two decades. In this paper, we have two main contributions to solving DVRP. Firstly, DVRP is solved with enhanced Ant Colony Optimization (E-ACO, which is the traditional Ant Colony Optimization (ACO fusing improved K-means and crossover operation. K-means can divide the region with the most reasonable distance, while ACO using crossover is applied to extend search space and avoid falling into local optimum prematurely. Secondly, several new evaluation benchmarks are proposed, which can objectively and comprehensively estimate the proposed method. In the experiment, the results for different scale problems are compared to those of previously published papers. Experimental results show that the algorithm is feasible and efficient.
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha
2013-02-01
This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.
Optimal control and cold war dynamics between plant and herbivore.
Low, Candace; Ellner, Stephen P; Holden, Matthew H
2013-08-01
Herbivores eat the leaves that a plant needs for photosynthesis. However, the degree of antagonism between plant and herbivore may depend critically on the timing of their interactions and the intrinsic value of a leaf. We present a model that investigates whether and when the timing of plant defense and herbivore feeding activity can be optimized by evolution so that their interactions can move from antagonistic to neutral. We assume that temporal changes in environmental conditions will affect intrinsic leaf value, measured as potential carbon gain. Using optimal-control theory, we model herbivore evolution, first in response to fixed plant strategies and then under coevolutionary dynamics in which the plant also evolves in response to the herbivore. In the latter case, we solve for the evolutionarily stable strategies of plant defense induction and herbivore hatching rate under different ecological conditions. Our results suggest that the optimal strategies for both plant and herbivore are to avoid direct conflict. As long as the plant has the capability for moderately lethal defense, the herbivore will modify its hatching rate to avoid plant defenses, and the plant will never have to use them. Insights from this model offer a possible solution to the paradox of sublethal defenses and provide a mechanism for stable plant-herbivore interactions without the need for natural enemy control.
METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS
Directory of Open Access Journals (Sweden)
V. Panteleev Andrei
2017-01-01
Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and
Assessment of Fevicol (adhesive Drying Process through Dynamic Speckle Techniques
Directory of Open Access Journals (Sweden)
Mohammad Z. Ansari
2015-04-01
Full Text Available Dynamic laser speckle (or biospeckle analysis is a useful measurement tool to analyze micro-motion on a sample surface via temporal statistics based on a sequence of speckle images. The aim of this work was to evaluate the use of dynamic speckles as an alternative tool to monitoring Fevicol drying process. Experimental demonstration of intensity-based algorithm to monitor Fevicol drying process is reported. The experiment was explored with the technique called Inertia Moment of co-occurrence matrix. The results allowed verifying the drying process and it was possible to observe different activity stages during the drying process. Statistical Tukey test at 5% significance level allowed differentiating different stages of drying. In conclusion, speckle activity, measured by the Inertia Moment, can be used to monitor drying processes of the Fevicol.
Directory of Open Access Journals (Sweden)
Christopher Expósito-Izquierdo
2017-02-01
Full Text Available This paper summarizes the main contributions of the Ph.D. thesis of Christopher Exp\\'osito-Izquierdo. This thesis seeks to develop a wide set of intelligent heuristic and meta-heuristic algorithms aimed at solving some of the most highlighted optimization problems associated with the transshipment and storage of containers at conventional maritime container terminals. Under the premise that no optimization technique can have a better performance than any other technique under all possible assumptions, the main point of interest in the domain of maritime logistics is to propose optimization techniques superior in terms of effectiveness and computational efficiency to previous proposals found in the scientific literature when solving individual optimization problems under realistic scenarios. Simultaneously, these optimization techniques should be enough competitive to be potentially implemented in practice. }}
Energy Technology Data Exchange (ETDEWEB)
Dall' Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.
2015-07-01
This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the control of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.
Loading technique for dynamic response studies of geological materials
International Nuclear Information System (INIS)
Butler, R.I.; Forrestal, M.J.
1979-04-01
A loading technique to study the dynamic response of tuff was explored. Loading is provided by electrically exploding etched copper mesh patterns with current from a capacitor discharge. Pressure pulses with peak pressures up to 1.25 kbar and 0.10 to 0.20 ms durations were measured with a pressure bar. The upper value of peak pressure was limited by the strength of the experimental apparatus, and higher pressure generation is possible with a redesign of test hardware. 6 figures, 2 tables
Display techniques for dynamic network data in transportation GIS
Energy Technology Data Exchange (ETDEWEB)
Ganter, J.H.; Cashwell, J.W.
1994-05-01
Interest in the characteristics of urban street networks is increasing at the same time new monitoring technologies are delivering detailed traffic data. These emerging streams of data may lead to the dilemma that airborne remote sensing has faced: how to select and access the data, and what meaning is hidden in them? computer-assisted visualization techniques are needed to portray these dynamic data. Of equal importance are controls that let the user filter, symbolize, and replay the data to reveal patterns and trends over varying time spans. We discuss a prototype software system that addresses these requirements.
Dynamics of blood plasma by spectropolarimetry and biochemical techniques
Voloshynska, Katerina; Ilashchuka, Tetjana; Prydij, Olexander; Gruia, Maria
2014-08-01
The aim of the study was to establish objective parameters of the field of laser and incoherent radiation of different spectral ranges (UV, visible, IR) as a non-invasive optical method of interaction with different samples of biological tissues and fluids of patients to determine the dynamics of metabolic syndrome and choosing the best personal treatment. As diagnostic methods have been used ultraviolet spectrometry samples of blood plasma in the liquid state, infrared spectroscopy middle range (2,5 - 25 microns) dry residue of plasma polarization and laser diagnostic technique of thin histological sections of biological tissues.
Transmission Dynamics and Optimal Control of Malaria in Kenya
Directory of Open Access Journals (Sweden)
Gabriel Otieno
2016-01-01
Full Text Available This paper proposes and analyses a mathematical model for the transmission dynamics of malaria with four-time dependent control measures in Kenya: insecticide treated bed nets (ITNs, treatment, indoor residual spray (IRS, and intermittent preventive treatment of malaria in pregnancy (IPTp. We first considered constant control parameters and calculate the basic reproduction number and investigate existence and stability of equilibria as well as stability analysis. We proved that if R0≤1, the disease-free equilibrium is globally asymptotically stable in D. If R0>1, the unique endemic equilibrium exists and is globally asymptotically stable. The model also exhibits backward bifurcation at R0=1. If R0>1, the model admits a unique endemic equilibrium which is globally asymptotically stable in the interior of feasible region D. The sensitivity results showed that the most sensitive parameters are mosquito death rate and mosquito biting rates. We then consider the time-dependent control case and use Pontryagin’s Maximum Principle to derive the necessary conditions for the optimal control of the disease using the proposed model. The existence of optimal control problem is proved. Numerical simulations of the optimal control problem using a set of reasonable parameter values suggest that the optimal control strategy for malaria control in endemic areas is the combined use of treatment and IRS; for epidemic prone areas is the use of treatment and IRS; for seasonal areas is the use of treatment; and for low risk areas is the use of ITNs and treatment. Control programs that follow these strategies can effectively reduce the spread of malaria disease in different malaria transmission settings in Kenya.
A novel technique for active vibration control, based on optimal ...
Indian Academy of Sciences (India)
... structure by simultaneously tracking zero references for modes of vibration. To illustrate the technique, a two-degrees of freedom spring-mass-dampersystem is considered as a test system. The mathematical model of the system is derived and then converted into a state-space model. A linear quadratic tracking control law ...
Optimizing Nuclear Reactor Operation Using Soft Computing Techniques
Entzinger, J.O.; Ruan, D.; Kahraman, Cengiz
2006-01-01
The strict safety regulations for nuclear reactor control make it di±cult to implement new control techniques such as fuzzy logic control (FLC). FLC however, can provide very desirable advantages over classical control, like robustness, adaptation and the capability to include human experience into
Electric power systems advanced forecasting techniques and optimal generation scheduling
Catalão, João P S
2012-01-01
Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie
DEFF Research Database (Denmark)
Ding, Yi; Goel, Lalit; Wang, Peng
2012-01-01
the required level of supply reliability to its customers. In previous research, Genetic Algorithm (GA) has been used to solve most reliability optimization problems. However, the GA is not very computationally efficient in some cases. In this chapter a new heuristic optimization technique—the particle swarm...
DEFF Research Database (Denmark)
Thummala, Prasanth; Schneider, Henrik; Zhang, Zhe
2015-01-01
.The energy efficiency is optimized using a proposed new automatic winding layout (AWL) technique and a comprehensive loss model.The AWL technique generates a large number of transformer winding layouts.The transformer parasitics such as dc resistance, leakage inductance and self-capacitance are calculated...... for each winding layout.An optimization technique is formulated to minimize the sum of energy losses during charge and discharge operations.The efficiency and energy loss distribution results from the optimization routine provide a deep insight into the high voltage transformer designand its impact...
Numerical optimization of piezolaminated beams under static and dynamic excitations
Directory of Open Access Journals (Sweden)
Rajan L. Wankhade
2017-06-01
Full Text Available Shape and vibration controls of smart structures in structural applications have gained much attraction due to their ability of actuation and sensing. The response of structure to bending, vibration, and buckling can be controlled by the use of this ability of a piezoelectric material. In the present work, the static and dynamic control of smart piezolaminated beams is presented. The optimal locations of piezoelectric patches are found out and then a detailed analysis is performed using finite element modeling considering the higher order shear deformation theory. In the first part, for an extension mode, the piezolaminated beam with stacking sequence PZT5/Al/PZT5 is considered. The length of the beam is 100 mm, whereas the thickness of an aluminum core is 16 mm and that of the piezo layer is of 1 mm. The PZT actuators are positioned with an identical poling direction along the thickness and are excited by a direct current voltage of 10 V. For the shear mode, the stacking sequence Al/PZT5/Al is adopted. The length of the beam is kept the same as the extension mechanism i.e. 100 mm, whereas the thickness of the aluminum core is 8 mm and that of the piezo layer is of 2 mm. The actuator is excited by a direct current voltage of 20 V. In the second part, the control of the piezolaminated beam with an optimal location of the actuator is investigated under a dynamic excitation. Electromechanical loading is considered in the finite element formulation for the analysis purpose. Results are provided for beams with different boundary conditions and loading for future references. Both the extension and shear actuation mechanisms are employed for the piezolaminated beam. These results may be used to identify the response of a beam under static and dynamic excitations. From the present work, the optimal location of a piezoelectric patch can be easily identified for the corresponding boundary condition of the beam.
Advanced Techniques for Monitoring, Simulation and Optimization of Machining Processes
Keshari, Anupam
2011-01-01
In today’s manufacturing industry, pressure for productivity, higher quality and cost saving is heavier than ever. Surviving in today’s highly competitive world is not an easy task, contemporary technology updates and heavy investments are needed in state of the art machinery and modern cutting tool systems. If the machining resources are underutilized, feasible techniques are needed to utilize resources efficiently. The new enhancements in the machine tools sector have enabled opportunit...
OPTIMAL DATA REPLACEMENT TECHNIQUE FOR COOPERATIVE CACHING IN MANET
Directory of Open Access Journals (Sweden)
P. Kuppusamy
2014-09-01
Full Text Available A cooperative caching approach improves data accessibility and reduces query latency in Mobile Ad hoc Network (MANET. Maintaining the cache is challenging issue in large MANET due to mobility, cache size and power. The previous research works on caching primarily have dealt with LRU, LFU and LRU-MIN cache replacement algorithms that offered low query latency and greater data accessibility in sparse MANET. This paper proposes Memetic Algorithm (MA to locate the better replaceable data based on neighbours interest and fitness value of cached data to store the newly arrived data. This work also elects ideal CH using Meta heuristic search Ant Colony Optimization algorithm. The simulation results shown that proposed algorithm reduces the latency, control overhead and increases the packet delivery rate than existing approach by increasing nodes and speed respectively.
Arnold, Heinz J P; Müller, Marcus; Waldhaus, Jörg; Hahn, Hartmut; Löwenheim, Hubert
2010-02-01
Whole-organ culture of a sensory organ in a rotating wall vessel bioreactor provides a powerful in vitro model for physiological and pathophysiological investigation as previously demonstrated for the postnatal inner ear. The model is of specific relevance as a tool for regeneration research. In the immature inner ear explant, the density was only 1.29 g/cm(3). The high density of 1.68 g/cm(3) of the functionally mature organ resulted in enhanced settling velocity and deviation from its ideal circular orbital path causing enhanced shear stress. The morphometric and physical properties, as well as the dynamic motion patterns of explants, were analyzed and numerically evaluated by an orbital path index. Application of a novel buoyancy bead technique resulted in a 6.5- to 14.8-fold reduction of the settling velocity. The deviation of the explant from its ideal circular orbital path was adjusted as indicated by an optimum value for the orbital path index (-1.0). Shear stress exerted on the inner ear explant was consequently reduced 6.4- to 15.0-fold. The culture conditions for postnatal stages were optimized, and the preconditions for transferring this in vitro model toward mature high-density stages established. This buoyancy technique may also be useful in tissue engineering of other high-density structures.
Optimization of decision rules based on dynamic programming approach
Zielosko, Beata
2014-01-14
This chapter is devoted to the study of an extension of dynamic programming approach which allows optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure that is the difference between number of rows in a given decision table and the number of rows labeled with the most common decision for this table divided by the number of rows in the decision table. We fix a threshold γ, such that 0 ≤ γ < 1, and study so-called γ-decision rules (approximate decision rules) that localize rows in subtables which uncertainty is at most γ. Presented algorithm constructs a directed acyclic graph Δ γ T which nodes are subtables of the decision table T given by pairs "attribute = value". The algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The chapter contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2014 Springer International Publishing Switzerland.
Performance Study and Dynamic Optimization Design for Thread Pool Systems
Energy Technology Data Exchange (ETDEWEB)
Xu, Dongping [Iowa State Univ., Ames, IA (United States)
2004-12-19
Thread pools have been widely used by many multithreaded applications. However, the determination of the pool size according to the application behavior still remains problematic. To automate this process, in this thesis we have developed a set of performance metrics for quantitatively analyzing thread pool performance. For our experiments, we built a thread pool system which provides a general framework for thread pool research. Based on this simulation environment, we studied the performance impact brought by the thread pool on different multithreaded applications. Additionally, the correlations between internal characterizations of thread pools and their throughput were also examined. We then proposed and evaluated a heuristic algorithm to dynamically determine the optimal thread pool size. The simulation results show that this approach is effective in improving overall application performance.
Dynamic control of biped locomotion robot using optimal regulator
Energy Technology Data Exchange (ETDEWEB)
Sano, Akihito; Furusho, Junji
1988-08-01
For moving in indoor space, it is generally recognized that biped locomotion is suitable. This paper proposes a hierarchical control strategy for the lower level where the position control or the force control at each joint is implemented. In the upper level control, the robot motion is divided into a sagittal plane and a lateral plane. We applied the optimal control algorithm to the motion control in the lateral plane in order to improve the robustness of the control system. The effects of these control schemes are shown by the experiments using the new walking robot BLR-G 1 and the parallel calculation system. BLR-G 1 has 9 degrees of freedom and equips the foot-pressure-sensors and a rate gyroscope. Complete dynamic walking is realized, in which the cycle for each step is about 1.0 second.
Looking for the optimal rate of recombination for evolutionary dynamics
Saakian, David B.
2018-01-01
We consider many-site mutation-recombination models of evolution with selection. We are looking for situations where the recombination increases the mean fitness of the population, and there is an optimal recombination rate. We found two fitness landscapes supporting such nonmonotonic behavior of the mean fitness versus the recombination rate. The first case is related to the evolution near the error threshold on a neutral-network-like fitness landscape, for moderate genome lengths and large population. The more realistic case is the second one, in which we consider the evolutionary dynamics of a finite population on a rugged fitness landscape (the smooth fitness landscape plus some random contributions to the fitness). We also give the solution to the horizontal gene transfer model in the case of asymmetric mutations. To obtain nonmonotonic behavior for both mutation and recombination, we need a specially designed (ideal) fitness landscape.
A Comparative Study on Optimal Structural Dynamics Using Wavelet Functions
Directory of Open Access Journals (Sweden)
Seyed Hossein Mahdavi
2015-01-01
Full Text Available Wavelet solution techniques have become the focus of interest among researchers in different disciplines of science and technology. In this paper, implementation of two different wavelet basis functions has been comparatively considered for dynamic analysis of structures. For this aim, computational technique is developed by using free scale of simple Haar wavelet, initially. Later, complex and continuous Chebyshev wavelet basis functions are presented to improve the time history analysis of structures. Free-scaled Chebyshev coefficient matrix and operation of integration are derived to directly approximate displacements of the corresponding system. In addition, stability of responses has been investigated for the proposed algorithm of discrete Haar wavelet compared against continuous Chebyshev wavelet. To demonstrate the validity of the wavelet-based algorithms, aforesaid schemes have been extended to the linear and nonlinear structural dynamics. The effectiveness of free-scaled Chebyshev wavelet has been compared with simple Haar wavelet and two common integration methods. It is deduced that either indirect method proposed for discrete Haar wavelet or direct approach for continuous Chebyshev wavelet is unconditionally stable. Finally, it is concluded that numerical solution is highly benefited by the least computation time involved and high accuracy of response, particularly using low scale of complex Chebyshev wavelet.
Dynamic programming approach for partial decision rule optimization
Amin, Talha
2012-10-04
This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.
Optimization of Regional Geodynamic Models for Mantle Dynamics
Knepley, M.; Isaac, T.; Jadamec, M. A.
2016-12-01
The SubductionGenerator program is used to construct high resolution, 3D regional thermal structures for mantle convection simulations using a variety of data sources, including sea floor ages and geographically referenced 3D slab locations based on seismic observations. The initial bulk temperature field is constructed using a half-space cooling model or plate cooling model, and related smoothing functions based on a diffusion length-scale analysis. In this work, we seek to improve the 3D thermal model and test different model geometries and dynamically driven flow fields using constraints from observed seismic velocities and plate motions. Through a formal adjoint analysis, we construct the primal-dual version of the multi-objective PDE-constrained optimization problem for the plate motions and seismic misfit. We have efficient, scalable preconditioners for both the forward and adjoint problems based upon a block preconditioning strategy, and a simple gradient update is used to improve the control residual. The full optimal control problem is formulated on a nested hierarchy of grids, allowing a nonlinear multigrid method to accelerate the solution.
Optimization of control poison management by dynamic programming
International Nuclear Information System (INIS)
Ponzoni Filho, P.
1974-01-01
A dynamic programming approach was used to optimize the poison distribution in the core of a nuclear power plant between reloading. This method was applied to a 500 M We PWR subject to two different fuel management policies. The beginning of a stage is marked by a fuel management decision. The state vector of the system is defined by the burnups in the three fuel zones of the core. The change of the state vector is computed in several time steps. A criticality conserving poison management pattern is chosen at the beginning of each step. The burnups at the end of a step are obtained by means of depletion calculations, assuming constant neutron distribution during the step. The violation of burnup and power peaking constraints during the step eliminates the corresponding end states. In the case of identical end states, all except that which produced the largest amount of energy, are eliminated. Among the several end states one is selected for the subsequent stage, when it is subjected to a fuel management decision. This selection is based on an optimally criterion previously chosen, such as: discharged fuel burnup maximization, energy generation cost minimization, etc. (author)
Local versus global optimal sports techniques in a group of athletes.
Huchez, Aurore; Haering, Diane; Holvoët, Patrice; Barbier, Franck; Begon, Mickael
2015-01-01
Various optimization algorithms have been used to achieve optimal control of sports movements. Nevertheless, no local or global optimization algorithm could be the most effective for solving all optimal control problems. This study aims at comparing local and global optimal solutions in a multistart gradient-based optimization by considering actual repetitive performances of a group of athletes performing a transition move on the uneven bars. Twenty-four trials by eight national-level female gymnasts were recorded using a motion capture system, and then multistart sequential quadratic programming optimizations were performed to obtain global optimal, local optimal and suboptimal solutions. The multistart approach combined with a gradient-based algorithm did not often find the local solution to be the best and proposed several other solutions including global optimal and suboptimal techniques. The qualitative change between actual and optimal techniques provided three directions for training: to increase hip flexion-abduction, to transfer leg and arm angular momentum to the trunk and to straighten hand path to the bar.
A nonlinear optimal control approach for chaotic finance dynamics
Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.
2017-11-01
A new nonlinear optimal control approach is proposed for stabilization of the dynamics of a chaotic finance model. The dynamic model of the financial system, which expresses interaction between the interest rate, the investment demand, the price exponent and the profit margin, undergoes approximate linearization round local operating points. These local equilibria are defined at each iteration of the control algorithm and consist of the present value of the systems state vector and the last value of the control inputs vector that was exerted on it. The approximate linearization makes use of Taylor series expansion and of the computation of the associated Jacobian matrices. The truncation of higher order terms in the Taylor series expansion is considered to be a modelling error that is compensated by the robustness of the control loop. As the control algorithm runs, the temporary equilibrium is shifted towards the reference trajectory and finally converges to it. The control method needs to compute an H-infinity feedback control law at each iteration, and requires the repetitive solution of an algebraic Riccati equation. Through Lyapunov stability analysis it is shown that an H-infinity tracking performance criterion holds for the control loop. This implies elevated robustness against model approximations and external perturbations. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven.
Application of Advanced Particle Swarm Optimization Techniques to Wind-thermal Coordination
DEFF Research Database (Denmark)
Singh, Sri Niwas; Østergaard, Jacob; Yadagiri, J.
2009-01-01
wind-thermal coordination algorithm is necessary to determine the optimal proportion of wind and thermal generator capacity that can be integrated into the system. In this paper, four versions of Particle Swarm Optimization (PSO) techniques are proposed for solving wind-thermal coordination problem...
The Adjoint Method for Gradient-based Dynamic Optimization of UV Flash Processes
DEFF Research Database (Denmark)
Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp
2017-01-01
This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Dynamic optimization of UV flash processes is relevant in nonlinear model predictive control of distillation columns, certain two-phase flow......-component flash process which demonstrate the importance of the optimization solver, the compiler, and the linear algebra software for the efficiency of dynamic optimization of UV flash processes....
Dynamic ASE Modeling and Optimization of Aircraft with SpaRibs, Phase I
National Aeronautics and Space Administration — We propose development and demonstration of a dynamic aeroservoelastic modeling and optimization system based on curvilinear internal structural arrangements of...
International Nuclear Information System (INIS)
Hashim, M; Pour, A B; Onn, C H
2014-01-01
Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate
Dynamics of hepatitis C under optimal therapy and sampling based analysis
Pachpute, Gaurav; Chakrabarty, Siddhartha P.
2013-08-01
We examine two models for hepatitis C viral (HCV) dynamics, one for monotherapy with interferon (IFN) and the other for combination therapy with IFN and ribavirin. Optimal therapy for both the models is determined using the steepest gradient method, by defining an objective functional which minimizes infected hepatocyte levels, virion population and side-effects of the drug(s). The optimal therapies for both the models show an initial period of high efficacy, followed by a gradual decline. The period of high efficacy coincides with a significant decrease in the viral load, whereas the efficacy drops after hepatocyte levels are restored. We use the Latin hypercube sampling technique to randomly generate a large number of patient scenarios and study the dynamics of each set under the optimal therapy already determined. Results show an increase in the percentage of responders (indicated by drop in viral load below detection levels) in case of combination therapy (72%) as compared to monotherapy (57%). Statistical tests performed to study correlations between sample parameters and time required for the viral load to fall below detection level, show a strong monotonic correlation with the death rate of infected hepatocytes, identifying it to be an important factor in deciding individual drug regimens.
Multi objective optimization of foam-filled circular tubes for quasi-static and dynamic responses
Directory of Open Access Journals (Sweden)
Fauzan Djamaluddin
Full Text Available AbstractFuel consumption and safety are currently key aspects in automobile design. The foam-filled thin-walled aluminium tube represents a potentially effective material for use in the automotive industry, due to its energy absorption capability and light weight. Multi-objective crashworthiness design optimization for foam-filled double cylindrical tubes is presented in this paper. The double structures are impacted by a rigid wall simulating quasi-static and dynamic loadings. The optimal parameters under consideration are the minimum peak crushing force and maximum specific energy absorption, using the non-dominated sorting genetic algorithm-II (NSGA-II technique. Radial basis functions (RBF and D-Optimal are adopted to determine the more complex crashworthiness functional objectives. The comparison is performed by finite element analysis of the impact crashworthiness characteristics in tubes under static and dynamic loads. Finally, the optimum crashworthiness performance of empty and foam-filled double tubes is investigated and compared to the traditional single foam-filled tube. The results indicate that the foam-filled double aluminium circular tube can be recommended for crashworthy structures.
Performance metric optimization advocates CPFR in supply chains: A system dynamics model based study
Directory of Open Access Journals (Sweden)
Balaji Janamanchi
2016-12-01
Full Text Available Background: Supply Chain partners often find themselves in rather helpless positions, unable to improve their firm’s performance and profitability because their partners although willing to share production information do not fully collaborate in tackling customer order variations as they don’t seem to appreciate the benefits of such collaboration. Methods: We use a two-player (supplier-manufacturer System Dynamics model to study the dynamics to assess the impact and usefulness of supply chain partner collaboration on the supply chain performance measures. Results: Simulation results of supply chain metrics under varied customer order patterns viz., basecase, random normal, random uniform, random upwardtrend, and random downwardtrend under (a basecase, (b independent optimization by manufacturer, and (c collaborative optimization by manufacturer and supplier, are obtained to contrast them to develop useful insights. Conclusions: Focus on obtaining improved inventory turns with optimization techniques provides some viable options to managers and makes a strong case for increased collaborative planning forecasting and replenishment (CPFR in supply chains. Despite the differences in the inventory management practices that it was contrasted with, CPFR has proven to be beneficial in a supply chain environment for all SC partners.
Optimization of digital radiography techniques for specific application
International Nuclear Information System (INIS)
Harara, W.
2010-12-01
A low cost digital radiography system (DRS) for testing weld joints and castings in laboratory was assembled. The DRS is composed from X-ray source, scintillator, first surface mirror with Aluminum coating, charged coupled device (CCD) camera and lens. The DRS was used to test flawed carbon steel welded plates with thicknesses up to 12 mm. The comparison between the digital radiographs of the plates weldments and the radiographs of the same plates weldments using medium speed film type had shown that, the detection capability of the weld flaws are nearly identical for the two radiography techniques, while the sensitivity achieved in digital radiography of the plates weldments was one IQI wire less than the sensitivity achieved by conventional radiography of the same plates weldments according to EN 462-1. Further, the DRS was also successfully used to test (100 x 100 x 100) mm Aluminum casting with artificial flaws of varied dimensions and orientations. The resulted digital radiographs of the casting show that, all the flaws had been detected and their dimensions can be measured accurately, this confirm that, The proposed DRS can be used to detect and measure the flaws in the Aluminum and others light metals castings accurately. (author)
Energy Technology Data Exchange (ETDEWEB)
Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew
2006-01-01
Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and
Dispersion analysis techniques within the space vehicle dynamics simulation program
Snow, L. S.; Kuhn, A. E.
1975-01-01
The Space Vehicle Dynamics Simulation (SVDS) program was evaluated as a dispersion analysis tool. The Linear Error Analysis (LEA) post processor was examined in detail and simulation techniques relative to conducting a dispersion analysis using the SVDS were considered. The LEA processor is a tool for correlating trajectory dispersion data developed by simulating 3 sigma uncertainties as single error source cases. The processor combines trajectory and performance deviations by a root-sum-square (RSS process) and develops a covariance matrix for the deviations. Results are used in dispersion analyses for the baseline reference and orbiter flight test missions. As a part of this study, LEA results were verified as follows: (A) Hand calculating the RSS data and the elements of the covariance matrix for comparison with the LEA processor computed data. (B) Comparing results with previous error analyses. The LEA comparisons and verification are made at main engine cutoff (MECO).
Directory of Open Access Journals (Sweden)
Delfim Soares
2011-01-01
Full Text Available In this work, coupled numerical analysis of interacting acoustic and dynamic models is focused. In this context, several numerical methods, such as the finite difference method, the finite element method, the boundary element method, meshless methods, and so forth, are considered to model each subdomain of the coupled model, and multidomain decomposition techniques are applied to deal with the coupling relations. Two basic coupling algorithms are discussed here, namely the explicit direct coupling approach and the implicit iterative coupling approach, which are formulated based on explicit/implicit time-marching techniques. Completely independent spatial and temporal discretizations among the interacting subdomains are permitted, allowing optimal discretization for each sub-domain of the model to be considered. At the end of the paper, numerical results are presented, illustrating the performance and potentialities of the discussed methodologies.
A dynamic mechanical analysis technique for porous media.
Pattison, Adam Jeffry; McGarry, Matthew; Weaver, John B; Paulsen, Keith D
2015-02-01
Dynamic mechanical analysis (DMA) is a common way to measure the mechanical properties of materials as functions of frequency. Traditionally, a viscoelastic mechanical model is applied and current DMA techniques fit an analytical approximation to measured dynamic motion data by neglecting inertial forces and adding empirical correction factors to account for transverse boundary displacements. Here, a finite-element (FE) approach to processing DMA data was developed to estimate poroelastic material properties. Frequency-dependent inertial forces, which are significant in soft media and often neglected in DMA, were included in the FE model. The technique applies a constitutive relation to the DMA measurements and exploits a nonlinear inversion to estimate the material properties in the model that best fit the model response to the DMA data. A viscoelastic version of this approach was developed to validate the approach by comparing complex modulus estimates to the direct DMA results. Both analytical and FE poroelastic models were also developed to explore their behavior in the DMA testing environment. All of the models were applied to tofu as a representative soft poroelastic material that is a common phantom in elastography imaging studies. Five samples of three different stiffnesses were tested from 1-14 Hz with rough platens placed on the top and bottom surfaces of the material specimen under test to restrict transverse displacements and promote fluid-solid interaction. The viscoelastic models were identical in the static case, and nearly the same at frequency with inertial forces accounting for some of the discrepancy. The poroelastic analytical method was not sufficient when the relevant physical boundary constraints were applied, whereas the poroelastic FE approach produced high quality estimates of shear modulus and hydraulic conductivity. These results illustrated appropriate shear modulus contrast between tofu samples and yielded a consistent contrast in
An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics
Turkington, Bruce
2013-08-01
A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.
A technique for measuring dynamic friction coefficient under impact loading.
Lin, Y L; Qin, J G; Chen, R; Zhao, P D; Lu, F Y
2014-09-01
We develop a novel setup based on the split Hopkinson pressure bar technique to test the dynamic friction coefficient under impact loading. In the setup, the major improvement is that the end of the incident bar near the specimen is wedge-shaped, which results in a combined compressive and shear loading applied to the specimen. In fact, the shear loading is caused by the interfacial friction between specimen and bars. Therefore, when the two loading force histories are measured, the friction coefficient histories can be calculated without any assumptions and theoretical derivations. The geometry of the friction pairs is simple, and can be either cuboid or cylindrical. Regarding the measurements, two quartz transducers are used to directly record the force histories, and an optical apparatus is designed to test the interfacial slip movement. By using the setup, the dynamic friction coefficient of PTFE/aluminum 7075 friction pairs was tested. The time resolved dynamic friction coefficient and slip movement histories were achieved. The results show that the friction coefficient changes during the loading process, the average data of the relatively stable flat plateau section of the friction coefficient curves is 0.137, the maximum normal pressure is 52 MPa, the maximum relative slip velocity is 1.5 m/s, and the acceleration is 8400 m(2)/s. Furthermore, the friction test was simulated using an explicit FEM code LS-DYNA. The simulation results showed that the constant pressure and slip velocity can both be obtained with a wide flat plateau incident pulse. For some special friction pairs, normal pressure up to a few hundred MPa, interfacial slip velocities up to 10 m/s, and slip movement up to centimeter-level can be expected.
A Multilevel Introspective Dynamic Optimization System For Holistic Power-Aware Computing
DEFF Research Database (Denmark)
Venkatachalam, Vasanth; Probst, Christian; Franz, Michael
2005-01-01
at specific levels, without fully exploring their synergy with other levels. Most software techniques target either operating systems or compilers but do not explore the interaction between the two layers. These techniques also have not fully explored the potential of virtual machines for power management....... In contrast, we are developing a system that integrates information from multiple levels of software and hardware, connecting these levels through a communication channel. At the heart of this system are a virtual machine that compiles and dynamically profiles code, and an optimizer that reoptimizes all code......, including that of applications and the virtual machine itself. We believe this introspective, holistic approach enables more informed power-management decisions....
The optimal injection technique for the osteoarthritic ankle: A randomized, cross-over trial
Witteveen, Angelique G. H.; Kok, Aimee; Sierevelt, Inger N.; Kerkhoffs, Gino M. M. J.; van Dijk, C. Niek
2013-01-01
Background: To optimize the injection technique for the osteoarthritic ankle in order to enhance the effect of intra-articular injections and minimize adverse events. Methods: Randomized cross-over trial. Comparing two injection techniques in patients with symptomatic ankle osteoarthritis. Patients
Techniques for the optimal design of photovoltaic inverters interconnected with the electric grid
DEFF Research Database (Denmark)
Koutroulis, Eftichios; Blaabjerg, Frede
2011-01-01
The DC/AC inverters are the key elements of grid-connected PV energy production systems. In this paper, a new technique for the optimal design of the power section and output filter of a full-bridge, grid-connected PV inverter, is proposed. The objective function which is minimized during...... the Genetic Algorithm-based optimization procedure is the PV inverter Levelized Cost Of the Electricity generated (LCOE). The proposed method has been applied for the optimal design of PV inverters installed at various sites in Europe. The simulation results indicate that the optimal values of the PV inverter...
Gradient vs. approximation design optimization techniques in low-dimensional convex problems
Fedorik, Filip
2013-10-01
Design Optimization methods' application in structural designing represents a suitable manner for efficient designs of practical problems. The optimization techniques' implementation into multi-physical softwares permits designers to utilize them in a wide range of engineering problems. These methods are usually based on modified mathematical programming techniques and/or their combinations to improve universality and robustness for various human and technical problems. The presented paper deals with the analysis of optimization methods and tools within the frame of one to three-dimensional strictly convex optimization problems, which represent a component of the Design Optimization module in the Ansys program. The First Order method, based on combination of steepest descent and conjugate gradient method, and Supbproblem Approximation method, which uses approximation of dependent variables' functions, accompanying with facilitation of Random, Sweep, Factorial and Gradient Tools, are analyzed, where in different characteristics of the methods are observed.
Second law analysis and simulation techniques for the energy optimization of buildings
Terlizzese, Tiziano
2010-01-01
The research activity described in this thesis is focused mainly on the study of finite-element techniques applied to thermo-fluid dynamic problems of plant components and on the study of dynamic simulation techniques applied to integrated building design in order to enhance the energy performance of the building. The first part of this doctorate thesis is a broad dissertation on second law analysis of thermodynamic processes with the purpose of including the issue of the energy efficiency of...
Investigation of dynamics of ELM crashes and their mitigation techniques
Energy Technology Data Exchange (ETDEWEB)
Pankin, Alexei Y. [Tech-X Corporation, Boulder, CO (United States)
2015-08-14
The accurate prediction of H-mode pedestal dynamics is critical for planning experiments in existing tokamaks and in the design of future tokamaks such as ITER and DEMO. The main objective of the proposed research is to advance the understanding of the physics of H-mode pedestal. Through advances in coupled kinetic-MHD simulations, a new model for H-mode pedestal and ELM crashes as well as an improved model for the bootstrap current will be developed. ELMmitigation techniques will also be investigated. The proposed research will help design efficient confinement scenarios and reduce transient heat loads on the divertor and plasma facing components. During the last two years, the principal investigator (PI) of this proposal actively participated in physics studies related to the DOE Joint Research Targets. These studies include the modeling of divertor heat load in the DIII-D, Alcator C-Mod, and NSTX tokamaks in 2010, and the modeling of H-mode pedestal structure in the DIII-D tokamak in 2011. It is proposed that this close collaboration with experimentalists from major US tokamaks continue during the next funding period. Verification and validation will be a strong component of the proposed research. During the course of the project, advances will be made in the following areas; Dynamics of the H-mode pedestal buildup and recovery after ELM crashes – The effects of neutral fueling, particle and thermal pinches will be explored; Dynamics of ELM crashes in realistic tokamak geometries – Heat loads associated with ELM crashes will be validated against experimental measurements. An improved model for ELM crashes will be developed; ELM mitigation – The effect of resonant magnetic perturbations on ELMs stability and their evolution will be investigated; Development of a new bootstrap current model – A reduced model for will be developed through careful verification of existing models for bootstrap current against first-principle kinetic neoclassical simulations
Directory of Open Access Journals (Sweden)
MUDASIR AHMED MEMON
2017-01-01
Full Text Available In this paper, PSO (Particle Swarm Optimization based technique is proposed to derive optimized switching angles that minimizes the THD (Total Harmonic Distortion and reduces the effect of selected low order non-triple harmonics from the output of the multilevel inverter. Conventional harmonic elimination techniques have plenty of limitations, and other heuristic techniques also not provide the satisfactory results. In this paper, single phase symmetrical cascaded H-Bridge 11-Level multilevel inverter is considered, and proposed algorithm is utilized to obtain the optimized switching angles that reduced the effect of 5th, 7th, 11th and 13th non-triplen harmonics from the output voltage of the multilevel inverter. A simulation result indicates that this technique outperforms other methods in terms of minimizing THD and provides high-quality output voltage waveform.
Conceptualizing a tool to optimize therapy based on dynamic heterogeneity
International Nuclear Information System (INIS)
Liao, David; Estévez-Salmerón, Luis; Tlsty, Thea D
2012-01-01
Complex biological systems often display a randomness paralleled in processes studied in fundamental physics. This simple stochasticity emerges owing to the complexity of the system and underlies a fundamental aspect of biology called phenotypic stochasticity. Ongoing stochastic fluctuations in phenotype at the single-unit level can contribute to two emergent population phenotypes. Phenotypic stochasticity not only generates heterogeneity within a cell population, but also allows reversible transitions back and forth between multiple states. This phenotypic interconversion tends to restore a population to a previous composition after that population has been depleted of specific members. We call this tendency homeostatic heterogeneity. These concepts of dynamic heterogeneity can be applied to populations composed of molecules, cells, individuals, etc. Here we discuss the concept that phenotypic stochasticity both underlies the generation of heterogeneity within a cell population and can be used to control population composition, contributing, in particular, to both the ongoing emergence of drug resistance and an opportunity for depleting drug-resistant cells. Using notions of both ‘large’ and ‘small’ numbers of biomolecular components, we rationalize our use of Markov processes to model the generation and eradication of drug-resistant cells. Using these insights, we have developed a graphical tool, called a metronomogram, that we propose will allow us to optimize dosing frequencies and total course durations for clinical benefit. (paper)
Photocathode Optimization for a Dynamic Transmission Electron Microscope: Final Report
Energy Technology Data Exchange (ETDEWEB)
Ellis, P; Flom, Z; Heinselman, K; Nguyen, T; Tung, S; Haskell, R; Reed, B W; LaGrange, T
2011-08-04
The Dynamic Transmission Electron Microscope (DTEM) team at Harvey Mudd College has been sponsored by LLNL to design and build a test setup for optimizing the performance of the DTEM's electron source. Unlike a traditional TEM, the DTEM achieves much faster exposure times by using photoemission from a photocathode to produce electrons for imaging. The DTEM team's work is motivated by the need to improve the coherence and current density of the electron cloud produced by the electron gun in order to increase the image resolution and contrast achievable by DTEM. The photoemission test setup is nearly complete and the team will soon complete baseline tests of electron gun performance. The photoemission laser and high voltage power supply have been repaired; the optics path for relaying the laser to the photocathode has been finalized, assembled, and aligned; the internal setup of the vacuum chamber has been finalized and mostly implemented; and system control, synchronization, and data acquisition has been implemented in LabVIEW. Immediate future work includes determining a consistent alignment procedure to place the laser waist on the photocathode, and taking baseline performance measurements of the tantalum photocathode. Future research will examine the performance of the electron gun as a function of the photoemission laser profile, the photocathode material, and the geometry and voltages of the accelerating and focusing components in the electron gun. This report presents the team's progress and outlines the work that remains.
Optimization of freeform surfaces using intelligent deformation techniques for LED applications
Isaac, Annie Shalom; Neumann, Cornelius
2018-04-01
For many years, optical designers have great interests in designing efficient optimization algorithms to bring significant improvement to their initial design. However, the optimization is limited due to a large number of parameters present in the Non-uniform Rationaly b-Spline Surfaces. This limitation was overcome by an indirect technique known as optimization using freeform deformation (FFD). In this approach, the optical surface is placed inside a cubical grid. The vertices of this grid are modified, which deforms the underlying optical surface during the optimization. One of the challenges in this technique is the selection of appropriate vertices of the cubical grid. This is because these vertices share no relationship with the optical performance. When irrelevant vertices are selected, the computational complexity increases. Moreover, the surfaces created by them are not always feasible to manufacture, which is the same problem faced in any optimization technique while creating freeform surfaces. Therefore, this research addresses these two important issues and provides feasible design techniques to solve them. Finally, the proposed techniques are validated using two different illumination examples: street lighting lens and stop lamp for automobiles.
Warehouse stocking optimization based on dynamic ant colony genetic algorithm
Xiao, Xiaoxu
2018-04-01
In view of the various orders of FAW (First Automotive Works) International Logistics Co., Ltd., the SLP method is used to optimize the layout of the warehousing units in the enterprise, thus the warehouse logistics is optimized and the external processing speed of the order is improved. In addition, the relevant intelligent algorithms for optimizing the stocking route problem are analyzed. The ant colony algorithm and genetic algorithm which have good applicability are emphatically studied. The parameters of ant colony algorithm are optimized by genetic algorithm, which improves the performance of ant colony algorithm. A typical path optimization problem model is taken as an example to prove the effectiveness of parameter optimization.
Bulgakov, V. K.; Strigunov, V. V.
2009-05-01
The Pontryagin maximum principle is used to prove a theorem concerning optimal control in regional macroeconomics. A boundary value problem for optimal trajectories of the state and adjoint variables is formulated, and optimal curves are analyzed. An algorithm is proposed for solving the boundary value problem of optimal control. The performance of the algorithm is demonstrated by computing an optimal control and the corresponding optimal trajectories.
Zhang, Shuo; Zhang, Chengning; Han, Guangwei; Wang, Qinghui
2014-01-01
A dual-motor coupling-propulsion electric bus (DMCPEB) is modeled, and its optimal control strategy is studied in this paper. The necessary dynamic features of energy loss for subsystems is modeled. Dynamic programming (DP) technique is applied to find the optimal control strategy including upshift threshold, downshift threshold, and power split ratio between the main motor and auxiliary motor. Improved control rules are extracted from the DP-based control solution, forming near-optimal control strategies. Simulation results demonstrate that a significant improvement in reducing energy loss due to the dual-motor coupling-propulsion system (DMCPS) running is realized without increasing the frequency of the mode switch. PMID:25540814
Dynamic motion planning of 3D human locomotion using gradient-based optimization.
Kim, Hyung Joo; Wang, Qian; Rahmatalla, Salam; Swan, Colby C; Arora, Jasbir S; Abdel-Malek, Karim; Assouline, Jose G
2008-06-01
Since humans can walk with an infinite variety of postures and limb movements, there is no unique solution to the modeling problem to predict human gait motions. Accordingly, we test herein the hypothesis that the redundancy of human walking mechanisms makes solving for human joint profiles and force time histories an indeterminate problem best solved by inverse dynamics and optimization methods. A new optimization-based human-modeling framework is thus described for predicting three-dimensional human gait motions on level and inclined planes. The basic unknowns in the framework are the joint motion time histories of a 25-degree-of-freedom human model and its six global degrees of freedom. The joint motion histories are calculated by minimizing an objective function such as deviation of the trunk from upright posture that relates to the human model's performance. A variety of important constraints are imposed on the optimization problem, including (1) satisfaction of dynamic equilibrium equations by requiring the model's zero moment point (ZMP) to lie within the instantaneous geometrical base of support, (2) foot collision avoidance, (3) limits on ground-foot friction, and (4) vanishing yawing moment. Analytical forms of objective and constraint functions are presented and discussed for the proposed human-modeling framework in which the resulting optimization problems are solved using gradient-based mathematical programming techniques. When the framework is applied to the modeling of bipedal locomotion on level and inclined planes, acyclic human walking motions that are smooth and realistic as opposed to less natural robotic motions are obtained. The aspects of the modeling framework requiring further investigation and refinement, as well as potential applications of the framework in biomechanics, are discussed.
Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming.
Wang, Haizhou; Song, Mingzhou
2011-12-01
The heuristic k -means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp . We demonstrate its advantage in optimality and runtime over the standard iterative k -means algorithm.
Directory of Open Access Journals (Sweden)
Jeevanandham Arumugam
2009-01-01
Full Text Available In this paper a classical lead-lag power system stabilizer is used for demonstration. The stabilizer parameters are selected in such a manner to damp the rotor oscillations. The problem of selecting the stabilizer parameters is converted to a simple optimization problem with an eigen value based objective function and it is proposed to employ simulated annealing and particle swarm optimization for solving the optimization problem. The objective function allows the selection of the stabilizer parameters to optimally place the closed-loop eigen values in the left hand side of the complex s-plane. The single machine connected to infinite bus system and 10-machine 39-bus system are considered for this study. The effectiveness of the stabilizer tuned using the best technique, in enhancing the stability of power system. Stability is confirmed through eigen value analysis and simulation results and suitable heuristic technique will be selected for the best performance of the system.
Application of Dynamic Speckle Techniques in Monitoring Biofilms Drying Process
Enes, Adilson M.; Júnior, Roberto A. Braga; Dal Fabbro, Inácio M.; da Silva, Washington A.; Pereira, Joelma
2008-04-01
Horticultural crops exhibit losses far greater than grains in Brazil which are associated to inappropriate maturation, mechanical bruising, infestation by microorganisms, wilting, etc. Appropriate packing prevents excessive mass loss associated to transpiration as well as to respiration, by controlling gas exchanging with outside environment. Common packing materials are identified as plastic films, waxes and biofilms. Although research developed with edible films and biopolymers has increased during last years to attend the food industry demands, avoiding environmental problems, little efforts have been reported on biofilm physical properties investigations. These properties, as drying time and biofilm interactions with environment are considered of basic importance. This research work aimed to contribute to development of a methodology to evaluate yucca (Maniot vulgaris) based biofilms drying time supported by a biospeckle technique. Biospeckle is a phenomenon generated by a laser beam scattered on a dynamic active surface, producing a time varying pattern which is proportional to the surface activity level. By capturing and processing the biospeckle image it is possible to attribute a numerical quantity to the surface bioactivity. Materials exhibiting high moisture content will also show high activity, which will support the drying time determination. Tests were set by placing biofilm samples on polyetilen plates and further submitted to laser exposition at four hours interval to capture the pattern images, generating the Intensities Dispersion Modulus. Results indicates that proposed methodology is applicable in determining biofilm drying time as well as vapor losses to environment.
Development of structural health monitoring techniques using dynamics testing
Energy Technology Data Exchange (ETDEWEB)
James, G.H. III [Sandia National Labs., Albuquerque, NM (United States). Experimental Structural Dynamics Dept.
1996-03-01
Today`s society depends upon many structures (such as aircraft, bridges, wind turbines, offshore platforms, buildings, and nuclear weapons) which are nearing the end of their design lifetime. Since these structures cannot be economically replaced, techniques for structural health monitoring must be developed and implemented. Modal and structural dynamics measurements hold promise for the global non-destructive inspection of a variety of structures since surface measurements of a vibrating structure can provide information about the health of the internal members without costly (or impossible) dismantling of the structure. In order to develop structural health monitoring for application to operational structures, developments in four areas have been undertaken within this project: operational evaluation, diagnostic measurements, information condensation, and damage identification. The developments in each of these four aspects of structural health monitoring have been exercised on a broad range of experimental data. This experimental data has been extracted from structures from several application areas which include aging aircraft, wind energy, aging bridges, offshore structures, structural supports, and mechanical parts. As a result of these advances, Sandia National Laboratories is in a position to perform further advanced development, operational implementation, and technical consulting for a broad class of the nation`s aging infrastructure problems.
DataFoundry: Warehousing techniques for dynamic environments
Energy Technology Data Exchange (ETDEWEB)
Critchlow, T.; Fidelis, K.; Ganesh, M.; Musick, R.; Slezak, T., LLNL
1998-01-29
Data warehouses and data marts have been successfully applied to a multitude of commercial business applications as tools for integrating and providing access to data located across an enterprise. Although the need for this capability is as vital in the scientific world as in the business domain, working warehouses in our community are scarce. A primary technical reason for this is that our understanding of the concepts being explored in an evolving scientific domain change constantly, leading to rapid changes in the data representation. When any database providing information to a warehouse changes its format, the warehouse must be updated to reflect these changes, or it will not function properly. The cost of maintaining a warehouse using traditional techniques in this environment is prohibitive. This paper describes ideas for dramatically reducing the amount of work that must be done to keep a warehouse up to date in a dynamic, scientific environment. The ideas are being applied in a prototype warehouse called DataFoundry. DataFoundry, currently in use by structural biologists at LLNL, will eventually support scientists at the Department of Energy`s Joint Genome Institute.
Dynamic high-temperature Kolsky tension bar techniques
Directory of Open Access Journals (Sweden)
Song Bo
2015-01-01
Full Text Available Kolsky tension bar techniques were modified for dynamic high-temperature tensile characterization of thin-sheet alloys. An induction coil heater was used to heat the specimen while a cooling system was applied to keep the bars at room temperature during heating. A preload system was developed to generate a small pretension load in the bar system during heating in order to compensate for the effect of thermal expansion generated in the high-temperature tensile specimen. A laser system was applied to directly measure the displacements at both ends of the tensile specimen in order to calculate the strain in the specimen. A pair of high-sensitivity semiconductor strain gages was used to measure the weak transmitted force due to the low flow stress in the thin specimen at elevated temperatures. As an example, the high-temperature Kolsky tension bar was used to characterize a DOP-26 iridium alloy in high-strain-rate tension at 860 s−1/1030 ∘C.
Optimal management with hybrid dynamics : The shallow lake problem
Reddy, P.V.; Schumacher, Hans; Engwerda, Jacob; Camlibel, M.K.; Julius, A.A.; Pasumarthy, R.
2015-01-01
In this article we analyze an optimal management problem that arises in ecological economics using hybrid systems modeling. First, we introduce a discounted autonomous infinite horizon hybrid optimal control problem and develop few tools to analyze the necessary conditions for optimality. Next,
International Nuclear Information System (INIS)
Ogawa, Kazuhiro; Amao, Satoshi; Ichikawa, Yuji; Shoji, Tetsuo
2008-01-01
This study proposes an innovative technique for repairing of cracked or damaged parts of structures, such as nuclear or thermal power plants, by means of cold gas dynamic spray (CS) technique. In the case of generation of cracks etc. in the structure, the cracks can be repaired by welding. However, the welding spends considerable time on repair, and also needs special skills. The CS technique is known as a new technique not only for coatings but also for thick depositions. It has many advantages, i.e. dense deposition, high deposition rate and low oxidation. Therefore, it has a possibility to apply the CS technique instead of welding to repair the cracks etc. In this study, the cold gas dynamic spray technique as a new repairing technique for some structures is introduced. (author)
2016-09-01
applications for optimization techniques spanning from developing market forecasts in economics [1] to automatically composing jazz solos in music [2...a traveling salesman problem with moving targets, where the route taken to cover a number of targets require the solution to an optimal control...increased faster than memory access speeds [56]. This limitation basically comes down to the physical limitations of how fast electrons can travel over
Bang, Soonam; Heo, Joon; Han, Soohee; Sohn, Hong-Gyoo
2010-01-01
Infiltration-route analysis is a military application of geospatial information system (GIS) technology. In order to find susceptible routes, optimal-path-searching algorithms are applied to minimize the cost function, which is the summed result of detection probability. The cost function was determined according to the thermal observation device (TOD) detection probability, the viewshed analysis results, and two feature layers extracted from the vector product interim terrain data. The detection probability is computed and recorded for an individual cell (50 m × 50 m), and the optimal infiltration routes are determined with A* algorithm by minimizing the summed costs on the routes from a start point to an end point. In the present study, in order to simulate the dynamic nature of a real-world problem, one thousand cost surfaces in the GIS environment were generated with randomly located TODs and randomly selected infiltration start points. Accordingly, one thousand sets of vulnerable routes for infiltration purposes could be found, which could be accumulated and presented as an infiltration vulnerability map. This application can be further utilized for both optimal infiltration routing and surveillance network design. Indeed, dynamic simulation in the GIS environment is considered to be a powerful and practical solution for optimization problems. A similar approach can be applied to the dynamic optimal routing for civil infrastructure, which requires consideration of terrain-related constraints and cost functions.
Directory of Open Access Journals (Sweden)
Hong-Gyoo Sohn
2010-01-01
Full Text Available Infiltration-route analysis is a military application of geospatial information system (GIS technology. In order to find susceptible routes, optimal-path-searching algorithms are applied to minimize the cost function, which is the summed result of detection probability. The cost function was determined according to the thermal observation device (TOD detection probability, the viewshed analysis results, and two feature layers extracted from the vector product interim terrain data. The detection probability is computed and recorded for an individual cell (50 m × 50 m, and the optimal infiltration routes are determined with A* algorithm by minimizing the summed costs on the routes from a start point to an end point. In the present study, in order to simulate the dynamic nature of a realworld problem, one thousand cost surfaces in the GIS environment were generated with randomly located TODs and randomly selected infiltration start points. Accordingly, one thousand sets of vulnerable routes for infiltration purposes could be found, which could be accumulated and presented as an infiltration vulnerability map. This application can be further utilized for both optimal infiltration routing and surveillance network design. Indeed, dynamic simulation in the GIS environment is considered to be a powerful and practical solution for optimization problems. A similar approach can be applied to the dynamic optimal routing for civil infrastructure, which requires consideration of terrain-related constraints and cost functions.
International Nuclear Information System (INIS)
Sutrisno; Widowati; Solikhin
2016-01-01
In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well. (paper)
Optimization Techniques for Design Problems in Selected Areas in WSNs: A Tutorial.
Ibrahim, Ahmed; Alfa, Attahiru
2017-08-01
This paper is intended to serve as an overview of, and mostly a tutorial to illustrate, the optimization techniques used in several different key design aspects that have been considered in the literature of wireless sensor networks (WSNs). It targets the researchers who are new to the mathematical optimization tool, and wish to apply it to WSN design problems. We hence divide the paper into two main parts. One part is dedicated to introduce optimization theory and an overview on some of its techniques that could be helpful in design problem in WSNs. In the second part, we present a number of design aspects that we came across in the WSN literature in which mathematical optimization methods have been used in the design. For each design aspect, a key paper is selected, and for each we explain the formulation techniques and the solution methods implemented. We also provide in-depth analyses and assessments of the problem formulations, the corresponding solution techniques and experimental procedures in some of these papers. The analyses and assessments, which are provided in the form of comments, are meant to reflect the points that we believe should be taken into account when using optimization as a tool for design purposes.
Active load sharing technique for on-line efficiency optimization in DC microgrids
DEFF Research Database (Denmark)
Sanseverino, E. Riva; Zizzo, G.; Boscaino, V.
2017-01-01
-DC converters, is modeled. An active load sharing technique is proposed for the on-line optimization of the global efficiency of the DC distribution network. The algorithm aims at the instantaneous efficiency optimization of the whole DC network, based on the on-line load current sampling. A Look Up Table......, is created to store the real efficiencies of the converters taking into account components tolerances. A MATLAB/Simulink model of the DC distribution network has been set up and a Genetic Algorithm has been employed for the global efficiency optimization. Simulation results are shown to validate the proposed...
Application of response surface techniques to helicopter rotor blade optimization procedure
Henderson, Joseph Lynn; Walsh, Joanne L.; Young, Katherine C.
1995-01-01
In multidisciplinary optimization problems, response surface techniques can be used to replace the complex analyses that define the objective function and/or constraints with simple functions, typically polynomials. In this work a response surface is applied to the design optimization of a helicopter rotor blade. In previous work, this problem has been formulated with a multilevel approach. Here, the response surface takes advantage of this decomposition and is used to replace the lower level, a structural optimization of the blade. Problems that were encountered and important considerations in applying the response surface are discussed. Preliminary results are also presented that illustrate the benefits of using the response surface.
Directory of Open Access Journals (Sweden)
Thenmozhi Srinivasan
2015-01-01
Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.
International Nuclear Information System (INIS)
Bousige, Colin; Boţan, Alexandru; Coasne, Benoît; Ulm, Franz-Josef; Pellenq, Roland J.-M.
2015-01-01
We report an efficient atom-scale reconstruction method that consists of combining the Hybrid Reverse Monte Carlo algorithm (HRMC) with Molecular Dynamics (MD) in the framework of a simulated annealing technique. In the spirit of the experimentally constrained molecular relaxation technique [Biswas et al., Phys. Rev. B 69, 195207 (2004)], this modified procedure offers a refined strategy in the field of reconstruction techniques, with special interest for heterogeneous and disordered solids such as amorphous porous materials. While the HRMC method generates physical structures, thanks to the use of energy penalties, the combination with MD makes the method at least one order of magnitude faster than HRMC simulations to obtain structures of similar quality. Furthermore, in order to ensure the transferability of this technique, we provide rational arguments to select the various input parameters such as the relative weight ω of the energy penalty with respect to the structure optimization. By applying the method to disordered porous carbons, we show that adsorption properties provide data to test the global texture of the reconstructed sample but are only weakly sensitive to the presence of defects. In contrast, the vibrational properties such as the phonon density of states are found to be very sensitive to the local structure of the sample
Krasteva, Denitza T.
1998-01-01
Multidisciplinary design optimization (MDO) for large-scale engineering problems poses many challenges (e.g., the design of an efficient concurrent paradigm for global optimization based on disciplinary analyses, expensive computations over vast data sets, etc.) This work focuses on the application of distributed schemes for massively parallel architectures to MDO problems, as a tool for reducing computation time and solving larger problems. The specific problem considered here is configuration optimization of a high speed civil transport (HSCT), and the efficient parallelization of the embedded paradigm for reasonable design space identification. Two distributed dynamic load balancing techniques (random polling and global round robin with message combining) and two necessary termination detection schemes (global task count and token passing) were implemented and evaluated in terms of effectiveness and scalability to large problem sizes and a thousand processors. The effect of certain parameters on execution time was also inspected. Empirical results demonstrated stable performance and effectiveness for all schemes, and the parametric study showed that the selected algorithmic parameters have a negligible effect on performance.
Yang, Pengyi; Yoo, Paul D; Fernando, Juanita; Zhou, Bing B; Zhang, Zili; Zomaya, Albert Y
2014-03-01
Data sampling is a widely used technique in a broad range of machine learning problems. Traditional sampling approaches generally rely on random resampling from a given dataset. However, these approaches do not take into consideration additional information, such as sample quality and usefulness. We recently proposed a data sampling technique, called sample subset optimization (SSO). The SSO technique relies on a cross-validation procedure for identifying and selecting the most useful samples as subsets. In this paper, we describe the application of SSO techniques to imbalanced and ensemble learning problems, respectively. For imbalanced learning, the SSO technique is employed as an under-sampling technique for identifying a subset of highly discriminative samples in the majority class. In ensemble learning, the SSO technique is utilized as a generic ensemble technique where multiple optimized subsets of samples from each class are selected for building an ensemble classifier. We demonstrate the utilities and advantages of the proposed techniques on a variety of bioinformatics applications where class imbalance, small sample size, and noisy data are prevalent.
Lankford, George Bernard
In this dissertation, we address applying mathematical and numerical techniques in the fields of high energy physics and biomedical sciences. The first portion of this thesis presents a method for optimizing the design of klystron circuits. A klystron is an electron beam tube lined with cavities that emit resonant frequencies to velocity modulate electrons that pass through the tube. Radio frequencies (RF) inserted in the klystron are amplified due to the velocity modulation of the electrons. The routine described in this work automates the selection of cavity positions, resonant frequencies, quality factors, and other circuit parameters to maximize the efficiency with required gain. The method is based on deterministic sampling methods. We will describe the procedure and give several examples for both narrow and wide band klystrons, using the klystron codes AJDISK (Java) and TESLA (Python). The rest of the dissertation is dedicated to developing, calibrating and using a mathematical model for hepatitis C dynamics with triple drug combination therapy. Groundbreaking new drugs, called direct acting antivirals, have been introduced recently to fight off chronic hepatitis C virus infection. The model we introduce is for hepatitis C dynamics treated with the direct acting antiviral drug, telaprevir, along with traditional interferon and ribavirin treatments to understand how this therapy affects the viral load of patients exhibiting different types of response. We use sensitivity and identifiability techniques to determine which parameters can be best estimated from viral load data. We use these estimations to give patient-specific fits of the model to partial viral response, end-of-treatment response, and breakthrough patients. We will then revise the model to incorporate an immune response dynamic to more accurately describe the dynamics. Finally, we will implement a suboptimal control to acquire a drug treatment regimen that will alleviate the systemic cost
Directory of Open Access Journals (Sweden)
Behrang Mohajer
2013-01-01
Full Text Available A new algorithm named random particle optimization algorithm (RPOA for local path planning problem of mobile robots in dynamic and unknown environments is proposed. The new algorithm inspired from bacterial foraging technique is based on particles which are randomly distributed around a robot. These particles search the optimal path toward the target position while avoiding the moving obstacles by getting help from the robot’s sensors. The criterion of optimal path selection relies on the particles distance to target and Gaussian cost function assign to detected obstacles. Then, a high level decision making strategy will decide to select best mobile robot path among the proceeded particles, and finally a low level decision control provides a control signal for control of considered holonomic mobile robot. This process is implemented without requirement to tuning algorithm or complex calculation, and furthermore, it is independent from gradient base methods such as heuristic (artificial potential field methods. Therefore, in this paper, the problem of local mobile path planning is free from getting stuck in local minima and is easy computed. To evaluate the proposed algorithm, some simulations in three various scenarios are performed and results are compared by the artificial potential field.
Tuning of PID controller using optimization techniques for a MIMO process
Thulasi dharan, S.; Kavyarasan, K.; Bagyaveereswaran, V.
2017-11-01
In this paper, two processes were considered one is Quadruple tank process and the other is CSTR (Continuous Stirred Tank Reactor) process. These are majorly used in many industrial applications for various domains, especially, CSTR in chemical plants.At first mathematical model of both the process is to be done followed by linearization of the system due to MIMO process and controllers are the major part to control the whole process to our desired point as per the applications so the tuning of the controller plays a major role among the whole process. For tuning of parameters we use two optimizations techniques like Particle Swarm Optimization, Genetic Algorithm. The above techniques are majorly used in different applications to obtain which gives the best among all, we use these techniques to obtain the best tuned values among many. Finally, we will compare the performance of the each process with both the techniques.
A Novel Analytical Technique for Optimal Allocation of Capacitors in Radial Distribution Systems
Directory of Open Access Journals (Sweden)
Sarfaraz Nawaz
2017-07-01
Full Text Available In this paper, a novel analytical technique is proposed to determine the optimal size and location of shunt capacitor units in radial distribution systems. An objective function is formulated to reduce real power loss, to improve the voltage profile and to increase annual cost savings. A new constant, the Loss Sensitivity Constant (LSC, is proposed here. The value of LSC decides the location and size of candidate buses. The technique is demonstrated on an IEEE-33 bus system at different load levels and the 130-bus distribution system of Jamawa Ramgarh village, Jaipur city. The obtained results are compared with the latest optimization techniques to show the effectiveness and robustness of the proposed technique.
Optimization of dynamic MOSA model parameters using ATP/EMTP software tool
Directory of Open Access Journals (Sweden)
Jasika Ranko
2017-01-01
Full Text Available This paper demonstrates the procedure for estimating parameters of a dynamic metal-oxide surge arrester model by using a genetic algorithm, implemented in ATP/EMTP graphic preprocessor (ATPDraw optimization module. The advantages of new ATPDraw options that allow optimization of electric circuit elements are shown. The optimization process is applied to two frequency-dependent MOSA models. At the end of the work, a comparison of results obtained before and after optimization is given.
The importance of functional form in optimal control solutions of problems in population dynamics
Runge, M.C.; Johnson, F.A.
2002-01-01
Optimal control theory is finding increased application in both theoretical and applied ecology, and it is a central element of adaptive resource management. One of the steps in an adaptive management process is to develop alternative models of system dynamics, models that are all reasonable in light of available data, but that differ substantially in their implications for optimal control of the resource. We explored how the form of the recruitment and survival functions in a general population model for ducks affected the patterns in the optimal harvest strategy, using a combination of analytical, numerical, and simulation techniques. We compared three relationships between recruitment and population density (linear, exponential, and hyperbolic) and three relationships between survival during the nonharvest season and population density (constant, logistic, and one related to the compensatory harvest mortality hypothesis). We found that the form of the component functions had a dramatic influence on the optimal harvest strategy and the ultimate equilibrium state of the system. For instance, while it is commonly assumed that a compensatory hypothesis leads to higher optimal harvest rates than an additive hypothesis, we found this to depend on the form of the recruitment function, in part because of differences in the optimal steady-state population density. This work has strong direct consequences for those developing alternative models to describe harvested systems, but it is relevant to a larger class of problems applying optimal control at the population level. Often, different functional forms will not be statistically distinguishable in the range of the data. Nevertheless, differences between the functions outside the range of the data can have an important impact on the optimal harvest strategy. Thus, development of alternative models by identifying a single functional form, then choosing different parameter combinations from extremes on the likelihood
Advanced techniques in dynamic infrared imaging research and application for cancer patients
International Nuclear Information System (INIS)
Boggio, Esteban F.; Santa Cruz, Gustavo A.
2009-01-01
Infrared Imaging for biomedical applications is a non-invasive technique employed to visualize the distribution of infrared radiance coming from the subject under study, either in a static or a dynamic mode. The main difference is that while with the static method basal situations are studied, in the dynamic approach a sequence of thermograms, using thermal stimuli applied onto the patient are acquired, following the temperature evolution throughout the time. Since tumors possess abnormal metabolic activity, a structure and a vascular distribution essentially different from healthy tissue, and a lack of response to homeostatic signals, thermal stresses enhance even more their presence. For this reason, a completely non-invasive system, referred to as Enhancement and Stimulation System (ESS) was constructed, capable of imparting a cool or hot convective air flow onto the surface to examine and permitting to include in the study the time-course of the thermal stress application. In this work, the design of the Dynamic Infrared Imaging-ESS prototype, its characterization and optimization will be presented. In addition, examples of biomedical interest employing small animals will be shown as well. (author)
Optimization of fuel-cell tram operation based on two dimension dynamic programming
Zhang, Wenbin; Lu, Xuecheng; Zhao, Jingsong; Li, Jianqiu
2018-02-01
This paper proposes an optimal control strategy based on the two-dimension dynamic programming (2DDP) algorithm targeting at minimizing operation energy consumption for a fuel-cell tram. The energy consumption model with the tram dynamics is firstly deduced. Optimal control problem are analyzed and the 2DDP strategy is applied to solve the problem. The optimal tram speed profiles are obtained for each interstation which consist of three stages: accelerate to the set speed with the maximum traction power, dynamically adjust to maintain a uniform speed and decelerate to zero speed with the maximum braking power at a suitable timing. The optimal control curves of all the interstations are connected with the parking time to form the optimal control method of the whole line. The optimized speed profiles are also simplified for drivers to follow.
Wittneben, Julia-Gabriela; Buser, Daniel; Belser, Urs C; Brägger, Urs
2013-01-01
An optimal esthetic implant restoration is a combination of a visually pleasing prosthesis and surrounding peri-implant soft tissue architecture. This article introduces a clinical method, the dynamic compression technique, of conditioning soft tissues around bone-level implants with provisional restorations in the esthetic zone. The technique has several goals: to establish an adequate emergence profile; to recreate a balanced mucosa course and level in harmony with the gingiva of the adjacent teeth, including papilla height/width, localization of the mucosal zenith and the tissue profile's triangular shape; as well as to establish an accurate proximal contact area with the adjacent tooth/implant crown.
Optimal Control and Forecasting of Complex Dynamical Systems
Grigorenko, Ilya
2006-01-01
This important book reviews applications of optimization and optimal control theory to modern problems in physics, nano-science and finance. The theory presented here can be efficiently applied to various problems, such as the determination of the optimal shape of a laser pulse to induce certain excitations in quantum systems, the optimal design of nanostructured materials and devices, or the control of chaotic systems and minimization of the forecast error for a given forecasting model (for example, artificial neural networks). Starting from a brief review of the history of variational calcul
A Dynamic Programming Solution for Energy-Optimal Video Playback on Mobile Devices
Directory of Open Access Journals (Sweden)
Minseok Song
2016-01-01
Full Text Available Due to the development of mobile technology and wide availability of smartphones, the Internet of Things (IoT starts to handle high volumes of video data to facilitate multimedia-based services, which requires energy-efficient video playback. In video playback, frames have to be decoded and rendered at high playback rate, increasing the computation cost on the CPU. To save the CPU power, dynamic voltage and frequency scaling (DVFS dynamically adjusts the operating voltage of the processor along with frequency, in which appropriate selection of frequency on power could achieve a balance between performance and power. We present a decoding model that allows buffering frames to let the CPU run at low frequency and then propose an algorithm that determines the CPU frequency needed to decode each frame in a video, with the aim of minimizing power consumption while meeting buffer size and deadline constraints, using a dynamic programming technique. We finally extend this algorithm to optimize CPU frequencies over a short sequence of frames, producing a practical method of reducing the energy required for video decoding. Experimental results show a system-wide reduction in energy of 27%, compared with a processor running at full speed.
Energy Technology Data Exchange (ETDEWEB)
Kagawa, Yuki; Okada, Masahiro; Yagyu, Yukinobu; Kumano, Seishi; Murakami, Takamichi [Dept. of Radiology, Kinki Univ. Faculty of Medicine, Osaka (Japan)], e-mail: murakami@med.kindai.ac.jp; Kanematsu, Masayuki [Dept. of Radiology, Gifu Univ., School of Medicine, Gifu (Japan); Kudo, Masayuki [CT Research JP, GE Healthcare JP Corporation, Tokyo (Japan)
2013-10-15
Background: A new multiphasic fast imaging technique, known as volume helical shuttle technique, is a breakthrough for liver imaging that offers new clinical opportunities in dynamic blood flow studies. This technique enables virtually real-time hemodynamics assessment by shuttling the patient cradle back and forth during serial scanning. Purpose: To determine optimal scan timing of hepatic arterial-phase imaging for detecting hypervascular hepatocellular carcinoma (HCC) with maximum tumor-to-liver contrast by volume helical shuttle technique. Material and Methods: One hundred and one hypervascular HCCs in 50 patients were prospectively studied by 64-channel multidetector-row computed tomography (MDCT) with multiphasic fast imaging technique. Contrast medium containing 600 mg iodine per kg body weight was intravenously injected for 30 s. Six seconds after the contrast arrival in the abdominal aorta detected with bolus tracking, serial 12-phase imaging of the whole liver was performed during 24-s breath-holding with multiphasic fast imaging technique during arterial phase. By placing regions of interest in the abdominal aorta, portal vein, liver parenchyma, and hypervascular HCCs on the multiphase images, time-density curves of anatomical regions and HCCs were composed. Timing of maximum tumor-to-liver contrast after the contrast arrival in the abdominal aorta was determined. Results: For the detection of hypervascular HCC at arterial phase, mean time and value of maximum tumor-to-liver contrast after the contrast arrival were 21 s and 38.0 HU, respectively. Conclusion: Optimal delay time for the hepatic arterial-phase imaging maximizing the contrast enhancement of hypervascular HCCs was 21 s after arrival of contrast medium in the abdominal aorta.
Liu, Qingshan; Guo, Zhishan; Wang, Jun
2012-02-01
In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.
Optimal blood glucose level control using dynamic programming based on minimal Bergman model
Rettian Anggita Sari, Maria; Hartono
2018-03-01
The purpose of this article is to simulate the glucose dynamic and the insulin kinetic of diabetic patient. The model used in this research is a non-linear Minimal Bergman model. Optimal control theory is then applied to formulate the problem in order to determine the optimal dose of insulin in the treatment of diabetes mellitus such that the glucose level is in the normal range for some specific time range. The optimization problem is solved using dynamic programming. The result shows that dynamic programming is quite reliable to represent the interaction between glucose and insulin levels in diabetes mellitus patient.
Directory of Open Access Journals (Sweden)
Renato de Sousa Gomide
Full Text Available Abstract Introduction: Due to the increasing popularization of computers and the internet expansion, Alternative and Augmentative Communication technologies have been employed to restore the ability to communicate of people with aphasia and tetraplegia. Virtual keyboards are one of the most primitive mechanisms for alternatively entering text and play a very important role in accomplishing this task. However, the text entry for this kind of keyboard is much slower than entering information through their physical counterparts. Many techniques and layouts have been proposed to improve the typing performance of virtual keyboards, each one concerning a different issue or solving a specific problem. However, not all of them are suitable to assist seriously people with motor impairment. Methods: In order to develop an assistive virtual keyboard with improved typing performance, we performed a systematic review on scientific databases. Results: We found 250 related papers and 52 of them were selected to compose. After that, we identified eight essentials virtual keyboard features, five methods to optimize data entry performance and five metrics to assess typing performance. Conclusion: Based on this review, we introduce a concept of an assistive, optimized, compact and adaptive virtual keyboard that gathers a set of suitable techniques such as: a new ambiguous keyboard layout, disambiguation algorithms, dynamic scan techniques, static text prediction of letters and words and, finally, the use of phonetic and similarity algorithms to reduce the user's typing error rate.
Modeling of radial asymmetry in lens distortion facilitated by modern optimization techniques
CSIR Research Space (South Africa)
De Villiers, Johan P
2010-01-18
Full Text Available -centering. This paper shows that the characterization of lens distortion can be improved by over 79% compared to prevailing methods. This is achieved by using modern numerical optimization techniques such as the Leapfrog algorithm, and sensitivity-normalized parameter...
Jude Hemanth, Duraisamy; Umamaheswari, Subramaniyan; Popescu, Daniela Elena; Naaji, Antoanela
2016-01-01
Image steganography is one of the ever growing computational approaches which has found its application in many fields. The frequency domain techniques are highly preferred for image steganography applications. However, there are significant drawbacks associated with these techniques. In transform based approaches, the secret data is embedded in random manner in the transform coefficients of the cover image. These transform coefficients may not be optimal in terms of the stego image quality and embedding capacity. In this work, the application of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been explored in the context of determining the optimal coefficients in these transforms. Frequency domain transforms such as Bandelet Transform (BT) and Finite Ridgelet Transform (FRIT) are used in combination with GA and PSO to improve the efficiency of the image steganography system.
International Nuclear Information System (INIS)
Li Qin; Yang Lizhi; Song Lixia; Qin De'en; Xue Yongshe; Wang Zhipeng
2012-01-01
Aim at high rate of large blast fragmentation, a big difficulty in long hole drilling and blasting underground uranium mine stope, it is pointed out at the same time of taking integrated technical management measures, the key is to optimize the drilling and blasting parameters and insure safety the act of one that primes, adopt 'minimum burden' blasting technique, renew the stope fragmentation process, and use new process of hole bottom indirect initiation fragmentation; optimize the detonating circuit and use safe, reliable and economically rational duplex non-electric detonating circuit. The production practice shows that under the guarantee of strictly controlled construction quality, the application of optimized blast fragmentation technique has enhanced the reliability of safety detonation and preferably solved the problem of high rate of large blast fragments. (authors)
Optimally Managing Dynamic Military Server-to-Customer Systems
2014-08-07
Maria E. Mayorga. A model for optimally dispatching ambulances to emergency calls with classification errors in patient priorities, IIE ...Industrial & Systems Engineering at the University of Wisconsin- Madison in May 2013. Best Paper Award for IIE Transactions Focused Issue on Scheduling...powerful computational tools and advanced algorithms. The model solutions will be interpreted to provide simple guidelines that can be used to optimally
Optimal Dynamic Advertising Strategy Under Age-Specific Market Segmentation
Krastev, Vladimir
2011-12-01
We consider the model proposed by Faggian and Grosset for determining the advertising efforts and goodwill in the long run of a company under age segmentation of consumers. Reducing this model to optimal control sub problems we find the optimal advertising strategy and goodwill.
Optimal inference in dynamic models with conditional moment restrictions
DEFF Research Database (Denmark)
Christensen, Bent Jesper; Sørensen, Michael
optimal estimator reduces to Newey's. Specification and hypothesis testing in our framework are introduced. We derive the theory of optimal instruments and the associated asymptotic dis- tribution theory for general cases including non-martingale estimating functions and general history dependence...
A Stepwise Optimal Design of a Dynamic Vibration Absorber with Tunable Resonant Frequency
Directory of Open Access Journals (Sweden)
Jiejian DI
2014-08-01
Full Text Available A new kind of dynamic vibration absorber (DVA with tunable resonant frequency is presented. The kinematics differential equation about it is built and the stepwise optimization is performed. Firstly, four main system parameters involving the ratios of mass m, natural frequency f, vibration frequency g and damping z are solved by small-step-search method to obtain optimal steady state amplitude. Secondly, the sizing optimization of the dynamic vibration absorber is proceeded to search an optimal damping effect based on the optimal parameters (g, m, z, f. And such the damping effect is simulated in a flat structure, and the results show that the working frequency band and damping effect of the DVA after optimization won 20 % of the effect of ascension compared with that before optimization.
Design refinement of multilayer optical thin film devices with two optimization techniques
International Nuclear Information System (INIS)
Apparao, K.V.S.R.
1992-01-01
The design efficiency of two different optimization techniques of designing multilayer optical thin film devices is compared. Ten different devices of varying complexities are chosen as design examples for the comparison. The design refinement efficiency and the design parameter characteristics of all the sample designs obtained with the two techniques are compared. The results of the comparison demonstrate that the new method of design developed using damped least squares technique with indirect derivatives give superior and efficient designs compared to the method developed with direct derivatives. (author). 23 refs., 4 tabs., 14 figs
Convergence of Sample Path Optimal Policies for Stochastic Dynamic Programming
National Research Council Canada - National Science Library
Fu, Michael C; Jin, Xing
2005-01-01
.... These results have practical implications for Monte Carlo simulation-based solution approaches to stochastic dynamic programming problems where it is impractical to extract the explicit transition...
The Use of Lean Manufacturing Techniques – SMED Analysis to Optimization of the Production Process
Directory of Open Access Journals (Sweden)
Dusan Sabadka
2017-09-01
Full Text Available Lean is a culture of real and continuous optimization. As a concept of continuous optimization in the midst of limited resources must be practiced continuously as a long term organizational norm. This paper revels why changeover time reduction is important in manufacturing industries and from the various tool and techniques available within Lean manufacturing describes mainly SMED (Single Minute Exchange of Dies for changeover time reduction and its application in Shaft manufacturing industry. This paper also describes principles, benefits, procedure and practical application of SMED. Theoretical bases are verified in a practical part that describes analysis and design optimization of non-productive time at changeover honing machine in selected shaft manufacturing compaty. The output is the structural design of universal palette and evaluation of productivity due to optimization of operations of time honing gear shafts. The result achieved showed considerable reduction in delay arising out of machine setting time, batch setting time and demonstration delay.
A multi-agent technique for contingency constrained optimal power flows
Energy Technology Data Exchange (ETDEWEB)
Talukdar, S.; Ramesh, V.C. (Carnegie Mellon Univ., Pittsburgh, PA (United States). Engineering Design Research Center)
1994-05-01
This paper does three things. First, it proposes that each critical contingency in a power system be represented by a correction time'' (the time required to eliminate the violations produced by the contingency), rather than by a set of hard constraints. Second, it adds these correction times to an optimal power flow and decomposes the resulting problem into a number of smaller optimization problems. Third, it proposes a multiagent technique for solving the smaller problems in parallel. The agents encapsulate traditional optimization algorithms as well as a new algorithm, called the voyager, that generates starting points for the traditional algorithms. All the agents communicate asynchronously, meaning that they can work in parallel without ever interrupting or delaying one another. The resulting scheme has potential for handling power system contingencies and other difficult global optimization problems.
A comparison of techniques for calculating protein essential dynamics
van Aalten, D.M.F.; de Groot, B.L.; Findlay, J.B.C.; Berendsen, H.J.C.; Amadei, A
1997-01-01
Recently the basic theory of essential dynamics, a method for extracting large concerted motions from protein molecular dynamics trajectories, was described. Here, we introduce and test new aspects. A method for diagonalizing large covariance matrices is presented. We show that it is possible to
International Nuclear Information System (INIS)
Seeram, Euclid; Davidson, Rob; Bushong, Stewart; Swan, Hans
2013-01-01
The purpose of this paper is to review the literature on exposure technique approaches in Computed Radiography (CR) imaging as a means of radiation dose optimization in CR imaging. Specifically the review assessed three approaches: optimization of kVp; optimization of mAs; and optimization of the Exposure Indicator (EI) in practice. Only papers dating back to 2005 were described in this review. The major themes, patterns, and common findings from the literature reviewed showed that important features are related to radiation dose management strategies for digital radiography include identification of the EI as a dose control mechanism and as a “surrogate for dose management”. In addition the use of the EI has been viewed as an opportunity for dose optimization. Furthermore optimization research has focussed mainly on optimizing the kVp in CR imaging as a means of implementing the ALARA philosophy, and studies have concentrated on mainly chest imaging using different CR systems such as those commercially available from Fuji, Agfa, Kodak, and Konica-Minolta. These studies have produced “conflicting results”. In addition, a common pattern was the use of automatic exposure control (AEC) and the measurement of constant effective dose, and the use of a dose-area product (DAP) meter
Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2018-01-01
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP
Directory of Open Access Journals (Sweden)
Marius Tufoi
2011-10-01
Full Text Available This work presents design methods, optimization and realization of mechanical for continuous casting plants using modern techniques: CAD,CAM and CAE. These current techniques refer to techniques CAD (Computer-Aided Design, CAE (Computer-Aided Engineering and CAM (Computer-Aided Manufacturing. Techniques mentioned above are areas of information technology aimed at helping engineering a variety of areas to be faster, more efficient and creative. A synthesis of the works published in the last 15 years shows that computer aided design and manufacturing are two areas which have developed simultaneously being treated in a common vision based on the natural links that exist between the activities of design and production or manufacturing. The paper will present a practical case application of techniques CAD, CAE and CAM.
An optimal dynamic interval stabbing-max data structure?
DEFF Research Database (Denmark)
Agarwal, Pankaj Kumar; Arge, Lars; Yi, Ke
2005-01-01
In this paper we consider the dynamic stabbing-max problem, that is, the problem of dynamically maintaining a set S of n axis-parallel hyper-rectangles in Rd, where each rectangle s ∈ S has a weight w(s) ∈ R, so that the rectangle with the maximum weight containing a query point can be determined...
2015-06-01
This Technical Report on Prototype Intelligent Network Flow Optimization (INFLO) Dynamic Speed Harmonization and : Queue Warning is the final report for the project. It describes the prototyping, acceptance testing and small-scale : demonstration of ...
Optimal response to non-equilibrium disturbances under truncated Burgers-Hopf dynamics
Thalabard, Simon; Turkington, Bruce
2017-04-01
We model and compute the average response of truncated Burgers-Hopf dynamics to finite perturbations away from the Gibbs equipartition energy spectrum using a dynamical optimization framework recently conceptualized in a series of papers. Non-equilibrium averages are there approximated in terms of geodesic paths in probability space that ‘best-fit’ the Liouvillean dynamics over a family of quasi-equilibrium trial densities. By recasting the geodesic principle as an optimal control problem, we solve numerically for the non-equilibrium responses using an augmented Lagrangian, non-linear conjugate gradient descent method. For moderate perturbations, we find an excellent agreement between the optimal predictions and the direct numerical simulations of the truncated Burgers-Hopf dynamics. In this near-equilibrium regime, we argue that the optimal response theory provides an approximate yet predictive counterpart to fluctuation-dissipation identities.
Directory of Open Access Journals (Sweden)
Maria Elena Menconi
2013-09-01
Full Text Available A Genetic Algorithm (GA is an optimization process inspired by natural systems ability of surviving in many different environments through the mechanisms of natural selection and genetics. The pairing of GA-based optimization techniques with dynamic energy models is a common and effective practice to find energy efficient design solutions. In this paper is implemented an optimization tool that use a GA and a dynamic energy model. Efficiency of GAs depends largely on the coding strategy and on the parameters selection. In order to test the code and to find the best combination of parameters, a parametric analysis of GA's performances is carried out. The algorithm, coded in Matlab, works with populations of strings. Each string, that represents a complete design solution, is initially randomly generated by the GA and evaluated in terms of energy performances by the dynamic thermal simulator. A new population is then generated using three different GA stochastic operators: reproduction, crossover and mutation, by selecting, mixing and randomly modifying the fittest solutions of the previous generation. Each generation is energetically evaluated and thus the fitness of the strings, that represent the energy efficiency of the design solutions, improves every cycle till eventually converge to the best solution. This whole methodology is well documented and applied in residential buildings design but can be easily extended to livestock housing. In this paper the algorithm is coded to be applied on a simple sheepfold model in order to optimize only passive design solutions.
Optimal dynamic control of resources in a distributed system
Shin, Kang G.; Krishna, C. M.; Lee, Yann-Hang
1989-01-01
The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.
Selection of optimal variant route based on dynamic fuzzy GRA
Jalil Heidary Dahooie; Amir Salar Vanaki; Navid Mohammadi; Hamid Reza Firoozfar
2018-01-01
Given the high costs of construction and maintenance, an optimum design methodology is one of the most important steps towards the development of transportation infrastructure, especially freeways. However, the effects of different variables on the decision-making process to find an optimal variant have caused the choice to become a very difficult and professional task for decision makers. So, the current paper aims to determine the optimal variant route for Isfahan-Shiraz freeway through MAD...
A characteristic study of CCF modeling techniques and optimization of CCF defense strategies
International Nuclear Information System (INIS)
Kim, Min Chull
2000-02-01
Common Cause Failures (CCFs ) are among the major contributors to risk and core damage frequency (CDF ) from operating nuclear power plants (NPPs ). Our study on CCF focused on the following aspects : 1) a characteristic study on the CCF modeling techniques and 2) development of the optimal CCF defense strategy. Firstly, the characteristics of CCF modeling techniques were studied through sensitivity study of CCF occurrence probability upon system redundancy. The modeling techniques considered in this study include those most widely used worldwide, i.e., beta factor, MGL, alpha factor, and binomial failure rate models. We found that MGL and alpha factor models are essentially identical in terms of the CCF probability. Secondly, in the study for CCF defense, the various methods identified in the previous studies for defending against CCF were classified into five different categories. Based on these categories, we developed a generic method by which the optimal CCF defense strategy can be selected. The method is not only qualitative but also quantitative in nature: the selection of the optimal strategy among candidates is based on the use of analytic hierarchical process (AHP). We applied this method to two motor-driven valves for containment sump isolation in Ulchin 3 and 4 nuclear power plants. The result indicates that the method for developing an optimal CCF defense strategy is effective
Directory of Open Access Journals (Sweden)
GHOLAMIAN, A. S.
2009-06-01
Full Text Available In this paper, a magnet shape optimization method for reduction of cogging torque and torque ripple in Permanent Magnet (PM brushless DC motors is presented by using the reduced basis technique coupled by finite element and design of experiments methods. The primary objective of the method is to reduce the enormous number of design variables required to define the magnet shape. The reduced basis technique is a weighted combination of several basis shapes. The aim of the method is to find the best combination using the weights for each shape as the design variables. A multi-level design process is developed to find suitable basis shapes or trial shapes at each level that can be used in the reduced basis technique. Each level is treated as a separated optimization problem until the required objective is achieved. The experimental design of Taguchi method is used to build the approximation model and to perform optimization. This method is demonstrated on the magnet shape optimization of a 6-poles/18-slots PM BLDC motor.
Evolutionary techniques for sensor networks energy optimization in marine environmental monitoring
Grimaccia, Francesco; Johnstone, Ron; Mussetta, Marco; Pirisi, Andrea; Zich, Riccardo E.
2012-10-01
The sustainable management of coastal and offshore ecosystems, such as for example coral reef environments, requires the collection of accurate data across various temporal and spatial scales. Accordingly, monitoring systems are seen as central tools for ecosystem-based environmental management, helping on one hand to accurately describe the water column and substrate biophysical properties, and on the other hand to correctly steer sustainability policies by providing timely and useful information to decision-makers. A robust and intelligent sensor network that can adjust and be adapted to different and changing environmental or management demands would revolutionize our capacity to wove accurately model, predict, and manage human impacts on our coastal, marine, and other similar environments. In this paper advanced evolutionary techniques are applied to optimize the design of an innovative energy harvesting device for marine applications. The authors implement an enhanced technique in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches, Particle Swarm Optimization and Genetic Algorithms. Here, this hybrid procedure is applied to a power buoy designed for marine environmental monitoring applications in order to optimize the recovered energy from sea-wave, by selecting the optimal device configuration.
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.
Structure preserving simulation of non-smooth dynamics and optimal control
Koch, Michael W.
2016-01-01
This work deals with so-called structure preserving integrators which are applied to systems with non-smooth dynamics. In addition to forward dynamic simulations of simple mechanical systems, herein the focus particularly lies on the optimal control of multibody systems. The aim is to provide a biomechanical modelling of the human lower extremities and the analysis of human jumping movements and of the upright gait. In order to do this, the solutions of the investigated optimal control proble...
Dynamic optimization and robust explicit model predictive control of hydrogen storage tank
Panos, C.
2010-09-01
We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.
Nonlinear dynamic simulation of optimal depletion of crude oil in the lower 48 United States
International Nuclear Information System (INIS)
Ruth, M.; Cleveland, C.J.
1993-01-01
This study combines the economic theory of optimal resource use with econometric estimates of demand and supply parameters to develop a nonlinear dynamic model of crude oil exploration, development, and production in the lower 48 United States. The model is simulated with the graphical programming language STELLA, for the years 1985 to 2020. The procedure encourages use of economic theory and econometrics in combination with nonlinear dynamic simulation to enhance our understanding of complex interactions present in models of optimal resource use. (author)
Analysis on the Metrics used in Optimizing Electronic Business based on Learning Techniques
Directory of Open Access Journals (Sweden)
Irina-Steliana STAN
2014-09-01
Full Text Available The present paper proposes a methodology of analyzing the metrics related to electronic business. The drafts of the optimizing models include KPIs that can highlight the business specific, if only they are integrated by using learning-based techniques. Having set the most important and high-impact elements of the business, the models should get in the end the link between them, by automating business flows. The human resource will be found in the situation of collaborating more and more with the optimizing models which will translate into high quality decisions followed by profitability increase.
Directory of Open Access Journals (Sweden)
Yukawa Masahiro
2006-01-01
Full Text Available In stereophonic acoustic echo cancellation (SAEC problem, fast and accurate tracking of echo path is strongly required for stable echo cancellation. In this paper, we propose a class of efficient fast SAEC schemes with linear computational complexity (with respect to filter length. The proposed schemes are based on pairwise optimal weight realization (POWER technique, thus realizing a "best" strategy (in the sense of pairwise and worst-case optimization to use multiple-state information obtained by preprocessing. Numerical examples demonstrate that the proposed schemes significantly improve the convergence behavior compared with conventional methods in terms of system mismatch as well as echo return loss enhancement (ERLE.
Liu, Ping; Li, Guodong; Liu, Xinggao
2015-09-01
Control vector parameterization (CVP) is an important approach of the engineering optimization for the industrial dynamic processes. However, its major defect, the low optimization efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering optimization for the industrial dynamic processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the optimization efficiency for industrial dynamic processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in dynamic process simulation. Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering optimization approach for the industrial dynamic processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Zhang De-Sheng
2016-01-01
Full Text Available Both efficiency and cavitation performance of the hydrofoil are the key technologies to design the tidal current turbine. In this paper, the hydrofoil efficiency and lift coefficient were improved based on particle swarm optimization method and XFoil codes. The cavitation performance of the optimized hydrofoil was also discussed by the computational fluid dynamic. Numerical results show the efficiency of the optimized hydrofoil was improved 11% ranging from the attack angle of 0-7° compared to the original NACA63-818 hydrofoil. The minimum pressure on leading edge of the optimized hydrofoil dropped above 15% at the high attack angle conditions of 10°, 15°, and 20°, respectively, which is benefit for the hydrofoil to avoiding the cavitation.
Molecular Dynamics: from basic techniques to applications (A Molecular Dynamics Primer)
Hernández, E. R.
2008-11-01
It is now 50 years since the first papers describing the use of Molecular Dynamics (MD) were published by Alder and Wainright, and since then, together with Monte Carlo (MC) techniques, MD has become an essential tool in the theoretical study of materials properties at finite temperatures. In its early days, MD was used in combination with simple yet general models, such as hard spheres or Lennard-Jones models of liquids, systems which, though simple, were nevertheless not amenable to an analytical statistical mechanical treatment. Nowadays, however, MD is most frequently used in combination with rather sophisticated models, ranging all the way between empirical force fields to first-principles methods, with the aim of describing as accurately as possible any given material. From a computational aid in statistical mechanics and many-body physics, MD has evolved to become a widely used tool in physical chemistry, condensed matter physics, biology, geology and materials science. The aim of this course is to describe the basic algorithms of MD, and to provide attendees with the necessary theoretical background in order to enable them to use MD simulations in their research work. Also, examples of the use of MD in different scientific disciplines will be provided, with the aim of illustrating the the many possibilities and the wide spread use of MD simulation techniques in scientific research today.
Automated Computational Fluid Dynamics Design With Shape Optimization, Phase II
National Aeronautics and Space Administration — Computational fluid dynamics (CFD) is used as an analysis tool to help the designer gain greater understanding of the fluid flow phenomena involved in the components...
Automated Computational Fluid Dynamics Design With Shape Optimization, Phase I
National Aeronautics and Space Administration — Computational fluid dynamics (CFD) is used as an analysis tool to help the designer gain greater understanding of the fluid flow phenomena involved in the components...
Kodali, Anuradha
outcomes of multiple binary classifiers over time using a sliding window or block dynamic fusion method that exploits temporal data correlations over time. We solve this NP-hard optimization problem via a Lagrangian relaxation (variational) technique. The third step optimizes the classifier parameters, viz., probabilities of detection and false alarm, using a genetic algorithm. The proposed algorithm is demonstrated by computing the diagnostic performance metrics on a twin-spool commercial jet engine, an automotive engine, and UCI datasets (problems with high classification error are specifically chosen for experimentation). We show that the primal-dual optimization framework performed consistently better than any traditional fusion technique, even when it is forced to give a single fault decision across a range of classification problems. Secondly, we implement the inference algorithms to diagnose faults in vehicle systems that are controlled by a network of electronic control units (ECUs). The faults, originating from various interactions and especially between hardware and software, are particularly challenging to address. Our basic strategy is to divide the fault universe of such cyber-physical systems in a hierarchical manner, and monitor the critical variables/signals that have impact at different levels of interactions. The proposed diagnostic strategy is validated on an electrical power generation and storage system (EPGS) controlled by two ECUs in an environment with CANoe/MATLAB co-simulation. Eleven faults are injected with the failures originating in actuator hardware, sensor, controller hardware and software components. Diagnostic matrix is established to represent the relationship between the faults and the test outcomes (also known as fault signatures) via simulations. The results show that the proposed diagnostic strategy is effective in addressing the interaction-caused faults.
Directory of Open Access Journals (Sweden)
Jingtao Shi
2013-01-01
Full Text Available This paper is concerned with the relationship between maximum principle and dynamic programming for stochastic recursive optimal control problems. Under certain differentiability conditions, relations among the adjoint processes, the generalized Hamiltonian function, and the value function are given. A linear quadratic recursive utility portfolio optimization problem in the financial engineering is discussed as an explicitly illustrated example of the main result.
Optimization of a new flow design for solid oxide cells using computational fluid dynamics modelling
DEFF Research Database (Denmark)
Duhn, Jakob Dragsbæk; Jensen, Anker Degn; Wedel, Stig
2016-01-01
Design of a gas distributor to distribute gas flow into parallel channels for Solid Oxide Cells (SOC) is optimized, with respect to flow distribution, using Computational Fluid Dynamics (CFD) modelling. The CFD model is based on a 3d geometric model and the optimized structural parameters include...
Evaluating dynamic covariance matrix forecasting and portfolio optimization
Sendstad, Lars Hegnes; Holten, Dag Martin
2012-01-01
In this thesis we have evaluated the covariance forecasting ability of the simple moving average, the exponential moving average and the dynamic conditional correlation models. Overall we found that a dynamic portfolio can gain significant improvements by implementing a multivariate GARCH forecast. We further divided the global investment universe into sectors and regions in order to investigate the relative portfolio performance of several asset allocation strategies with both variance and c...
Directory of Open Access Journals (Sweden)
Ian D. Washington
2015-07-01
Full Text Available A technique for optimizing large-scale differential-algebraic process models under uncertainty using a parallel embedded model approach is developed in this article. A combined multi-period multiple-shooting discretization scheme is proposed, which creates a significant number of independent numerical integration tasks for each shooting interval over all scenario/period realizations. Each independent integration task is able to be solved in parallel as part of the function evaluations within a gradient-based non-linear programming solver. The focus of this paper is on demonstrating potential computation performance improvement when the embedded differential-algebraic equation model solution of the multi-period discretization is implemented in parallel. We assess our parallel dynamic optimization approach on two case studies; the first is a benchmark literature problem, while the second is a large-scale air separation problem that considers a robust set-point transition under parametric uncertainty. Results indicate that focusing on the speed-up of the embedded model evaluation can significantly decrease the overall computation time; however, as the multi-period formulation grows with increased realizations, the computational burden quickly shifts to the internal computation performed within the non-linear programming algorithm. This highlights the need for further decomposition, structure exploitation and parallelization within the non-linear programming algorithm and is the subject for further investigation.
Optimal Control of a Fed-batch Fermentation Process by Neuro-Dynamic Programming
Directory of Open Access Journals (Sweden)
Tatiana Ilkova
2004-10-01
Full Text Available In this paper the method for optimal control of a fermentation process is presented, that is based on an approach for optimal control - Neuro-Dynamic programming. For this aim the approximation neural network is developed and the decision of the optimization problem is improved by an iteration mode founded on the Bellman equation. With this approach computing time and procedure are decreased and quality of the biomass at the end of the process is increased.
An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries
Vellev, Stoyan
2008-01-01
The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-determinis...
Okumura, Hisashi
2011-01-07
The partial multicanonical algorithm for molecular dynamics and Monte Carlo simulations samples a wide range of an important part of the potential energy. Although it is a strong technique for structure prediction of biomolecules, the choice of the partial potential energy has not been optimized. In order to find the best choice, partial multicanonical molecular dynamics simulations of an alanine dipeptide in explicit water solvent were performed with 15 trial choices for the partial potential energy. The best choice was found to be the sum of the electrostatic, Lennard-Jones, and torsion-angle potential energies between solute atoms. In this case, the partial multicanonical simulation sampled all of the local-minimum free-energy states of the P(II), C(5), α(R), α(P), α(L), and C states and visited these states most frequently. Furthermore, backbone dihedral angles ϕ and ψ rotated very well. It is also found that the most important term among these three terms is the electrostatic potential energy and that the Lennard-Jones term also helps the simulation to overcome the steric restrictions. On the other hand, multicanonical simulation sampled all of the six states, but visited these states fewer times. Conventional canonical simulation sampled only four of the six states: The P(II), C(5), α(R), and α(P) states.
A Multi-Cycle Q-Modulation for Dynamic Optimization of Inductive Links.
Lee, Byunghun; Yeon, Pyungwoo; Ghovanloo, Maysam
2016-08-01
This paper presents a new method, called multi-cycle Q-modulation, which can be used in wireless power transmission (WPT) to modulate the quality factor (Q) of the receiver (Rx) coil and dynamically optimize the load impedance to maximize the power transfer efficiency (PTE) in two-coil links. A key advantage of the proposed method is that it can be easily implemented using off-the-shelf components without requiring fast switching at or above the carrier frequency, which is more suitable for integrated circuit design. Moreover, the proposed technique does not need any sophisticated synchronization between the power carrier and Q-modulation switching pulses. The multi-cycle Q-modulation is analyzed theoretically by a lumped circuit model, and verified in simulation and measurement using an off-the-shelf prototype. Automatic resonance tuning (ART) in the Rx, combined with multi-cycle Q-modulation helped maximizing PTE of the inductive link dynamically in the presence of environmental and loading variations, which can otherwise significantly degrade the PTE in multi-coil settings. In the prototype conventional 2-coil link, the proposed method increased the power amplifier (PA) plus inductive link efficiency from 4.8% to 16.5% at ( R L = 1 kΩ, d 23 = 3 cm), and from 23% to 28.2% at ( R L = 100 Ω, d 23 = 3 cm) after 11% change in the resonance capacitance, while delivering 168.1 mW to the load (PDL).
Amplification of the parametric dynamical Casimir effect via optimal control
Hoeb, Fabian; Angaroni, Fabrizio; Zoller, Jonathan; Calarco, Tommaso; Strini, Giuliano; Montangero, Simone; Benenti, Giuliano
2017-09-01
We introduce different strategies to enhance photon generation in a cavity within the Rabi model in the ultrastrong coupling regime. We show that a bang-bang strategy allows one to enhance the effect up to 1 order of magnitude with respect to simply driving the system in resonance for a fixed time. Moreover, up to about another order of magnitude can be gained by exploiting quantum optimal control strategies. Finally, we show that such optimized protocols are robust with respect to systematic errors and noise, paving the way to future experimental implementations of such strategies.
Modelling of Rabies Transmission Dynamics Using Optimal Control Analysis
Directory of Open Access Journals (Sweden)
Joshua Kiddy K. Asamoah
2017-01-01
Full Text Available We examine an optimal way of eradicating rabies transmission from dogs into the human population, using preexposure prophylaxis (vaccination and postexposure prophylaxis (treatment due to public education. We obtain the disease-free equilibrium, the endemic equilibrium, the stability, and the sensitivity analysis of the optimal control model. Using the Latin hypercube sampling (LHS, the forward-backward sweep scheme and the fourth-order Range-Kutta numerical method predict that the global alliance for rabies control’s aim of working to eliminate deaths from canine rabies by 2030 is attainable through mass vaccination of susceptible dogs and continuous use of pre- and postexposure prophylaxis in humans.
A Preconditioning Technique for First-Order Primal-Dual Splitting Method in Convex Optimization
Directory of Open Access Journals (Sweden)
Meng Wen
2017-01-01
Full Text Available We introduce a preconditioning technique for the first-order primal-dual splitting method. The primal-dual splitting method offers a very general framework for solving a large class of optimization problems arising in image processing. The key idea of the preconditioning technique is that the constant iterative parameters are updated self-adaptively in the iteration process. We also give a simple and easy way to choose the diagonal preconditioners while the convergence of the iterative algorithm is maintained. The efficiency of the proposed method is demonstrated on an image denoising problem. Numerical results show that the preconditioned iterative algorithm performs better than the original one.
Artificial intelligence search techniques for the optimization of cold source geometry
International Nuclear Information System (INIS)
Azmy, Y.Y.
1988-01-01
Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness that produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometric shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape, which is the unknown in such a study. An analogy is drawn between this problem and a state space search, then a simple artificial intelligence (AI) search technique is used to determine the optimum cold source shape based on a two-group, r-z diffusion model. This AI design concept was implemented in the computer program AID, which consists of two modules, a physical model module, and a search module, which can be independently modified, improved, or made more sophisticated
Optimization of brushless direct current motor design using an intelligent technique.
Shabanian, Alireza; Tousiwas, Armin Amini Poustchi; Pourmandi, Massoud; Khormali, Aminollah; Ataei, Abdolhay
2015-07-01
This paper presents a method for the optimal design of a slotless permanent magnet brushless DC (BLDC) motor with surface mounted magnets using an improved bee algorithm (IBA). The 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. This method is based on the capability of swarm-based algorithms in finding the optimal solution. One sample case is used to illustrate the performance of the design approach and optimization technique. The IBA has a better performance and speed of convergence compared with bee algorithm (BA). Simulation results show that the proposed method has a very high/efficient performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Tong, S.S.; Powell, D.; Goel, S.
1992-02-01
A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs
Optimization models and techniques for implementation and pricing of electricity markets
International Nuclear Information System (INIS)
Madrigal Martinez, M.
2001-01-01
The operation and planning of vertically integrated electric power systems can be optimized using models that simulate solutions to problems. As the electric power industry is going through a period of restructuring, there is a need for new optimization tools. This thesis describes the importance of optimization tools and presents techniques for implementing them. It also presents methods for pricing primary electricity markets. Three modeling groups are studied. The first considers a simplified continuous and discrete model for power pool auctions. The second considers the unit commitment problem, and the third makes use of a new type of linear network-constrained clearing system model for daily markets for power and spinning reserve. The newly proposed model considers bids for supply and demand and bilateral contracts. It is a direct current model for the transmission network
Approximating Optimal Release in a Deterministic Model for the Sterile Insect Technique
Directory of Open Access Journals (Sweden)
Sergio Ramirez
2016-01-01
Full Text Available Cost/benefit analyses are essential to support management planning and decisions before launching any pest control program. In particular, applications of the sterile insect technique (SIT are often prevented by the projected economic burden associated with rearing processes. This has had a deep impact on the technique development and its use on insects with long larval periods, as often seen in beetles. Under the assumptions of long adult timespan and multiple mating, we show how to find approximate optimal sterile release policies that minimize costs. The theoretical framework proposed considers the release of insects by pulses and finds approximate optimal release sizes through stochastic searching. The scheme is then used to compare simulated release strategies obtained for different pulse schedules and release bounds, providing a platform for evaluating the convenience of increasing sterile male release intensity or extending the period of control.
A genetic algorithm technique to optimize the configuration of heat storage in DH networks
Directory of Open Access Journals (Sweden)
Amru Rizal Razani
2016-12-01
Full Text Available The technical and economical evaluation of heat storage layout and configuration in the DH network is one of important aspect for optimizing the heat production from the heat supplier’s point of view in one side as well as to satisfy the heat customer demand in the other side. Generally, the state of the art technique has considered three optional planning layouts for DH network. A classical network with centralized heat storage at Combined Heat and Power (CHP plant, decentralized storages in the network, and decentralized small storages at the substations or in the customer building. In this paper, through the use of genetic algorithm technique, comparison of three different scenarios is presented to evaluate the optimal planning of heat storage layout in CHP based DH supply system according to economical and technical aspects in the network.
Lv, Hanfeng; Zhang, Liang; Wang, Dingjie; Wu, Jie
2014-03-01
It is well known that inertial integrated navigation systems can provide accurate navigation information. In these systems, inertial sensor random error often becomes the limiting factor to get a better performance. So it is imperative to have accurate characterization of the random error. Allan variance analysis technique has a good performance in analyzing inertial sensor random error, and it is always used to characterize various types of the random error terms. This paper proposes a new method named optimization iterative algorithm based on nonnegative constraint applied to Allan variance analysis technique to estimate parameters of the random error terms. The parameter estimates by this method are nonnegative and optimal, and the estimation process does not have matrix nearly singular issues. Testing with simulation data and the experimental data of a fiber optical gyro, the parameters estimated by the presented method are compared against other excellent methods with good agreement; moreover, the objective function has the minimum value.
Optimal dynamic pricing for deteriorating items with reference-price effects
Xue, Musen; Tang, Wansheng; Zhang, Jianxiong
2016-07-01
In this paper, a dynamic pricing problem for deteriorating items with the consumers' reference-price effect is studied. An optimal control model is established to maximise the total profit, where the demand not only depends on the current price, but also is sensitive to the historical price. The continuous-time dynamic optimal pricing strategy with reference-price effect is obtained through solving the optimal control model on the basis of Pontryagin's maximum principle. In addition, numerical simulations and sensitivity analysis are carried out. Finally, some managerial suggestions that firm may adopt to formulate its pricing policy are proposed.
Was Your Glass Left Half Full? Family Dynamics and Optimism
Buri, John R.; Gunty, Amy
2008-01-01
Students' levels of a frequently studied adaptive schema (optimism) as a function of parenting variables (parental authority, family intrusiveness, parental overprotection, parentification, parental psychological control, and parental nurturance) were investigated. Results revealed that positive parenting styles were positively related to the…
Tidal Farm Array Optimization: Dynamics, Engineering, And Environment
Thyng, K. M.; Funke, S. W.; Roc, T.
2016-02-01
Through a novel collaboration, we seek to improve optimization of turbine placement in tidal farms. In this work, a given flow field is modeled using OpenTidalFarm in two dimensions and with turbine representations. The algorithm finds the optimal placement of turbines in terms of maximizing power production in the setup given restrictions such as required depth. Subsequent analysis ties in engineering and economics to adjust that power production according to realistic associated costs. Accounting for costs can greatly impact optimal turbine layout by limiting the number of turbines that it is cost efficient to build. Additionally, considering environmental impacts can further limit turbine placement, and may be in the form of, for example, restricting spatial and time-averaged changes to the speed, vorticity, mixing, or the tidal range. We model a tidally-driven idealized headland channel that approximates the length scales of Minas Passage in the Bay of Fundy, Canada. With this system, we have simulated the domain with no turbines as a base case, solved for the optimal layout within a given farm lease area to maximize power production, and an additional case which accounts for engineering costs. On-going work focuses on assessing existing environmental impact to be used for implementing turbine placement restrictions.
An Optimization Approach to the Dynamic Allocation of Economic Capital
Laeven, R.J.A.; Goovaerts, M.J.
2004-01-01
We propose an optimization approach to allocating economic capital, distinguishing between an allocation or raising principle and a measure for the risk residual. The approach is applied both at the aggregate (conglomerate) level and at the individual (subsidiary) level and yields an integrated
Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH
2009-09-01
A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.
Energy Technology Data Exchange (ETDEWEB)
AlRashidi, M.R. [Electrical Engineering Department, College of Technological Studies, Shuwaikh (Kuwait); El-Hawary, M.E. [Department of Electrical and Computer Engineering, Dalhousie University, Halifax, NS B3J 2X4 (Canada)
2009-04-15
Computational intelligence tools are attracting added attention in different research areas and research in power systems is not different. This paper provides an overview of major computational issues with regard to the optimal power flow (OPF). Then, it offers a brief summary of major computational intelligence tools. A detailed coverage of most OPF related research work that make use of modern computational intelligence techniques is presented next. (author)
Directory of Open Access Journals (Sweden)
Mehiddin Al-Baali
2015-12-01
Full Text Available We deal with the design of parallel algorithms by using variable partitioning techniques to solve nonlinear optimization problems. We propose an iterative solution method that is very efficient for separable functions, our scope being to discuss its performance for general functions. Experimental results on an illustrative example have suggested some useful modifications that, even though they improve the efficiency of our parallel method, leave some questions open for further investigation.
DEFF Research Database (Denmark)
Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu
2017-01-01
This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...... forecast information is not fully utilized. While model predictive control (MPC) as a look ahead policy can integrate the updated forecast in the optimization process. The proposed hybrid optimization approach makes full use of the advantages of ADP and MPC to obtain a better solution by using the real...
Search method optimization technique for thermal design of high power RFQ structure
International Nuclear Information System (INIS)
Sharma, N.K.; Joshi, S.C.
2009-01-01
RRCAT has taken up the development of 3 MeV RFQ structure for the low energy part of 100 MeV H - ion injector linac. RFQ is a precision machined resonating structure designed for high rf duty factor. RFQ structural stability during high rf power operation is an important design issue. The thermal analysis of RFQ has been performed using ANSYS finite element analysis software and optimization of various parameters is attempted using Search Method optimization technique. It is an effective optimization technique for the systems governed by a large number of independent variables. The method involves examining a number of combinations of values of independent variables and drawing conclusions from the magnitude of the objective function at these combinations. In these methods there is a continuous improvement in the objective function throughout the course of the search and hence these methods are very efficient. The method has been employed in optimization of various parameters (called independent variables) of RFQ like cooling water flow rate, cooling water inlet temperatures, cavity thickness etc. involved in RFQ thermal design. The temperature rise within RFQ structure is the objective function during the thermal design. Using ANSYS Programming Development Language (APDL), various multiple iterative programmes are written and the analysis are performed to minimize the objective function. The dependency of the objective function on various independent variables is established and the optimum values of the parameters are evaluated. The results of the analysis are presented in the paper. (author)
Validating specifications of dynamic systems using automated reasoning techniques
Feenstra, Remco; Bioch, J.C.; Wieringa, Roelf J.; Tan, Y.H
In this paper, we propose a new approach to validating formal specifications of observable behavior of discrete dynamic systems. By observable behavior we mean system behavior as observed by users or other systems in the environment of the system. Validation of a formal specification of an informal
COMPARISON OF SAMPLING TECHNIQUES USED IN STUDYING LEPIDOPTERA POPULATION DYNAMICS
Four methods (light traps, foliage samples, canvas bands, and gypsy moth egg mass surveys) that are used to study the population dynamics of foliage-feeding Lepidoptera were compared for 10 species, including gypsy moth, Lymantria dispar L. Samples were collected weekly at 12 sit...
Morrow, Melissa M.; Rankin, Jeffery W.; Neptune, Richard R.; Kaufman, Kenton R.
2014-01-01
The primary purpose of this study was to compare static and dynamic optimization muscle force and work predictions during the push phase of wheelchair propulsion. A secondary purpose was to compare the differences in predicted shoulder and elbow kinetics and kinematics and handrim forces. The forward dynamics simulation minimized differences between simulated and experimental data (obtained from 10 manual wheelchair users) and muscle co-contraction. For direct comparison between models, the shoulder and elbow muscle moment arms and net joint moments from the dynamic optimization were used as inputs into the static optimization routine. RMS errors between model predictions were calculated to quantify model agreement. There was a wide range of individual muscle force agreement that spanned from poor (26.4 % Fmax error in the middle deltoid) to good (6.4 % Fmax error in the anterior deltoid) in the prime movers of the shoulder. The predicted muscle forces from the static optimization were sufficient to create the appropriate motion and joint moments at the shoulder for the push phase of wheelchair propulsion, but showed deviations in the elbow moment, pronation-supination motion and hand rim forces. These results suggest the static approach does not produce results similar enough to be a replacement for forward dynamics simulations, and care should be taken in choosing the appropriate method for a specific task and set of constraints. Dynamic optimization modeling approaches may be required for motions that are greatly influenced by muscle activation dynamics or that require significant co-contraction. PMID:25282075
Optimization of machining techniques–A retrospective and literature ...
Indian Academy of Sciences (India)
Various conventional techniques employed for machining optimization include geometric programming, geometric plus linear programming, goal programming, sequential unconstrained minimizationtechnique, dynamic programming etc. The latest techniques for optimization include fuzzy logic, scatter search technique, ...
An Optimized Grey Dynamic Model for Forecasting the Output of High-Tech Industry in China
Directory of Open Access Journals (Sweden)
Zheng-Xin Wang
2014-01-01
Full Text Available The grey dynamic model by convolution integral with the first-order derivative of the 1-AGO data and n series related, abbreviated as GDMC(1,n, performs well in modelling and forecasting of a grey system. To improve the modelling accuracy of GDMC(1,n, n interpolation coefficients (taken as unknown parameters are introduced into the background values of the n variables. The parameters optimization is formulated as a combinatorial optimization problem and is solved collectively using the particle swarm optimization algorithm. The optimized result has been verified by a case study of the economic output of high-tech industry in China. Comparisons of the obtained modelling results from the optimized GDMC(1,n model with the traditional one demonstrate that the optimal algorithm is a good alternative for parameters optimization of the GDMC(1,n model. The modelling results can assist the government in developing future policies regarding high-tech industry management.
Worst-Case-Optimal Dynamic Reinsurance for Large Claims
DEFF Research Database (Denmark)
Korn, Ralf; Menkens, Olaf; Steffensen, Mogens
2012-01-01
We control the surplus process of a non-life insurance company by dynamic proportional reinsurance. The objective is to maximize expected (utility of the) surplus under the worst-case claim development. In the large claim case with a worst-case upper limit on claim numbers and claim sizes, we fin...
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for...
Dynamic optimal foraging theory explains vertical migrations of bigeye tuna
DEFF Research Database (Denmark)
Thygesen, Uffe Høgsbro; Sommer, Lene; Evans, Karen
2016-01-01
dynamic programming. With little calibration of model parameters, our results are consistent with observed data on vertical movement: we find that small tuna should display constant-depth strategies while large tuna should display vertical migrations. The analysis supports the hypothesis that the tuna...
On the Utility of Island Models in Dynamic Optimization
DEFF Research Database (Denmark)
Lissovoi, Andrei; Witt, Carsten
2015-01-01
A simple island model with λ islands and migration occurring after every τ iterations is studied on the dynamic fitness function Maze. This model is equivalent to a (1+λ) EA if τ=1, i.e., migration occurs during every iteration. It is proved that even for an increased offspring population size up...
Cache-mesh, a Dynamics Data Structure for Performance Optimization
DEFF Research Database (Denmark)
Nguyen, Tuan T.; Dahl, Vedrana Andersen; Bærentzen, J. Andreas
2017-01-01
This paper proposes the cache-mesh, a dynamic mesh data structure in 3D that allows modifications of stored topological relations effortlessly. The cache-mesh can adapt to arbitrary problems and provide fast retrieval to the most-referred-to topological relations. This adaptation requires trivial...
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA...
Market Dynamics and Optimal Timber Salvage After a Natural Catastrophe
Jeffrey P. Prestemon; Thomas P. Holmes
2004-01-01
Forest-based natural catastrophes are regular features of timber production in the United States, especially from hurricanes, fires, and insect and disease outbreaks. These catastrophes affect timber prices and result in economic transfers. We develop a model of timber market dynamics after such a catastrophe that shows how timber salvage affects the welfare of...
Global optimization for quantum dynamics of few-fermion systems
DEFF Research Database (Denmark)
Li, Xikun; Pecak, Daniel; Sowinski, Tomasz
2018-01-01
Quantum state preparation is vital to quantum computation and quantum information processing tasks. In adiabatic state preparation, the target state is theoretically obtained with nearly perfect fidelity if the control parameter is tuned slowly enough. As this, however, leads to slow dynamics, it...
Optimal control of peridinin excited-state dynamics
Czech Academy of Sciences Publication Activity Database
Dietzek, B.; Chábera, P.; Hanf, R.; Tschierlei, S.; Popp, J.; Pascher, T.; Yartsev, A.; Polívka, Tomáš
2010-01-01
Roč. 373, 1-2 (2010), s. 129-136 ISSN 0301-0104 Institutional research plan: CEZ:AV0Z50510513 Keywords : peridin * excited-state dynamics * coherent control Subject RIV: BO - Biophysics Impact factor: 2.017, year: 2010
Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas
Directory of Open Access Journals (Sweden)
Jin Xisong
2018-02-01
Full Text Available Previous research has focused on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, existing dynamic models are not easily applied to high-dimensional problems due to the curse of dimensionality. In this paper, we extend the framework of the Dynamic Conditional Correlation/Equicorrelation and an extreme value approach into a series of Dynamic Conditional Elliptical Copulas. We investigate risk measures such as Value at Risk (VaR and Expected Shortfall (ES for passive portfolios and dynamic optimal portfolios using Mean-Variance and ES criteria for a sample of US stocks over a period of 10 years. Our results suggest that (1 Modeling the marginal distribution is important for dynamic high-dimensional multivariate models. (2 Neglecting the dynamic dependence in the copula causes over-aggressive risk management. (3 The DCC/DECO Gaussian copula and t-copula work very well for both VaR and ES. (4 Grouped t-copulas and t-copulas with dynamic degrees of freedom further match the fat tail. (5 Correctly modeling the dependence structure makes an improvement in portfolio optimization with respect to tail risk. (6 Models driven by multivariate t innovations with exogenously given degrees of freedom provide a flexible and applicable alternative for optimal portfolio risk management.
Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.
Mazandarani, Mehran; Pariz, Naser
2018-03-16
This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Parameter optimization method for the water quality dynamic model based on data-driven theory.
Liang, Shuxiu; Han, Songlin; Sun, Zhaochen
2015-09-15
Parameter optimization is important for developing a water quality dynamic model. In this study, we applied data-driven method to select and optimize parameters for a complex three-dimensional water quality model. First, a data-driven model was developed to train the response relationship between phytoplankton and environmental factors based on the measured data. Second, an eight-variable water quality dynamic model was established and coupled to a physical model. Parameter sensitivity analysis was investigated by changing parameter values individually in an assigned range. The above results served as guidelines for the control parameter selection and the simulated result verification. Finally, using the data-driven model to approximate the computational water quality model, we employed the Particle Swarm Optimization (PSO) algorithm to optimize the control parameters. The optimization routines and results were analyzed and discussed based on the establishment of the water quality model in Xiangshan Bay (XSB). Copyright © 2015 Elsevier Ltd. All rights reserved.
Stochastic optimization in insurance a dynamic programming approach
Azcue, Pablo
2014-01-01
The main purpose of the book is to show how a viscosity approach can be used to tackle control problems in insurance. The problems covered are the maximization of survival probability as well as the maximization of dividends in the classical collective risk model. The authors consider the possibility of controlling the risk process by reinsurance as well as by investments. They show that optimal value functions are characterized as either the unique or the smallest viscosity solution of the associated Hamilton-Jacobi-Bellman equation; they also study the structure of the optimal strategies and show how to find them. The viscosity approach was widely used in control problems related to mathematical finance but until quite recently it was not used to solve control problems related to actuarial mathematical science. This book is designed to familiarize the reader on how to use this approach. The intended audience is graduate students as well as researchers in this area.
Optimally Convex Controller and Model Reduction for a Dynamic System
Directory of Open Access Journals (Sweden)
P. S. KHUNTIA
2008-07-01
Full Text Available This paper presents analysis and design of a family of controllers based on numerical convex optimization for an aircraft pitch control system. A design method is proposed here to solve control system design problems in which a set of multiple closed loop performance specifications are simultaneously satisfied. The transfer matrix of the system is determined through the convex combination of the transfer matrices of the plant and the controllers. The present system with optimal convex controller has been tested for stability using Kharitonov’s Stability Criteria. The simulation deals here withthe problem of pitch control system of a BRAVO fighter aircraft which results in higher order close loop transfer function. So the order of the higher order transfer function is reduced to minimize the complexity of the system.
Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R
2013-01-01
This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.
Optimization in Quaternion Dynamic Systems: Gradient, Hessian, and Learning Algorithms.
Xu, Dongpo; Xia, Yili; Mandic, Danilo P
2016-02-01
The optimization of real scalar functions of quaternion variables, such as the mean square error or array output power, underpins many practical applications. Solutions typically require the calculation of the gradient and Hessian. However, real functions of quaternion variables are essentially nonanalytic, which are prohibitive to the development of quaternion-valued learning systems. To address this issue, we propose new definitions of quaternion gradient and Hessian, based on the novel generalized Hamilton-real (GHR) calculus, thus making a possible efficient derivation of general optimization algorithms directly in the quaternion field, rather than using the isomorphism with the real domain, as is current practice. In addition, unlike the existing quaternion gradients, the GHR calculus allows for the product and chain rule, and for a one-to-one correspondence of the novel quaternion gradient and Hessian with their real counterparts. Properties of the quaternion gradient and Hessian relevant to numerical applications are also introduced, opening a new avenue of research in quaternion optimization and greatly simplified the derivations of learning algorithms. The proposed GHR calculus is shown to yield the same generic algorithm forms as the corresponding real- and complex-valued algorithms. Advantages of the proposed framework are illuminated over illustrative simulations in quaternion signal processing and neural networks.
Optimization and anti-optimization of structures under uncertainty
National Research Council Canada - National Science Library
Elishakoff, Isaac; Ohsaki, Makoto
2010-01-01
.... The necessity of anti-optimization approach is first demonstrated, then the anti-optimization techniques are applied to static, dynamic and buckling problems, thus covering the broadest possible set of applications...
International Nuclear Information System (INIS)
Schoenbrod, Betina; Quispe, Benjamin; Cattaneo, Alberto; Rodriguez, Ivanna; Chocron, Mauricio; Farias, Silvia
2012-09-01
Atucha II NPP is a Pressurized Vessel Heavy Water Reactor (PVHWR) of 740 MWe designed by SIEMENSKWU. After some years of delay, this NPP is in advanced construction state, being the beginning of commercial operation expected for 2013. Nucleoelectrica Argentina (N.A.S.A.) is the company in charge of the finalization of this project and the future operation of the plant. The Comision Nacional de Energia Atomica (C.N.E.A.) is the R and D nuclear institution in the country that, among many other topics, provides technical support to the stations. The Commissioning Chemistry Division of CNAII is in charge of the commissioning of the demineralization water plant and the organization of the chemical laboratory. The water plant started operating successfully in July 2010 and is providing the plant with nuclear grade purity water. Currently, in the conventional ('cold') laboratory several activities are taking place. On one hand, analytical techniques for the future operation of the plant are being tested and optimized. On the other hand, the laboratory is participating in the cleaning and conservation of the different components of the plant, providing technical support and the necessary analysis. To define the analytical techniques for the normal operation of the plant, the parameters to be measured and their range were established in the Chemistry Manual. The necessary equipment and reagents were bought. In this work, a summary of the analytical techniques that are being implemented and optimized is presented. Common anions (chloride, sulfate, fluoride, bromide and nitrate) are analyzed by ion chromatography. Cations, mainly sodium, are determined by absorption spectrometry. A UV-Vis spectrometer is used to determine silicates, iron, ammonia, DQO, total solids, true color and turbidity. TOC measurements are performed with a TOC analyzer. To optimize the methods, several parameters are evaluated: linearity, detection and quantification limits, precision and
Peng, NaiFu; Guan, Hui; Wu, ChuiJie
2016-04-01
In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeling equations are derived. Then the multiscale global optimization method based on coarse graining analysis is presented, by which a set of approximate global optimal bases is directly obtained from Navier-Stokes equations and the construction of optimal dynamical systems is realized. The optimal bases show good properties, such as showing the physical properties of complex flows and the turbulent vortex structures, being intrinsic to real physical problem and dynamical systems, and having scaling symmetry in mathematics, etc.. In conclusion, using fewer terms of optimal bases will approach the exact solutions of Navier-Stokes equations, and the dynamical systems based on them show the most optimal behavior.
Optimal parameters for the FFA-Beddoes dynamic stall model
Energy Technology Data Exchange (ETDEWEB)
Bjoerck, A.; Mert, M. [FFA, The Aeronautical Research Institute of Sweden, Bromma (Sweden); Madsen, H.A. [Risoe National Lab., Roskilde (Denmark)
1999-03-01
Unsteady aerodynamic effects, like dynamic stall, must be considered in calculation of dynamic forces for wind turbines. Models incorporated in aero-elastic programs are of semi-empirical nature. Resulting aerodynamic forces therefore depend on values used for the semi-empiricial parameters. In this paper a study of finding appropriate parameters to use with the Beddoes-Leishman model is discussed. Minimisation of the `tracking error` between results from 2D wind tunnel tests and simulation with the model is used to find optimum values for the parameters. The resulting optimum parameters show a large variation from case to case. Using these different sets of optimum parameters in the calculation of blade vibrations, give rise to quite different predictions of aerodynamic damping which is discussed. (au)
Team dynamics in virtual, partially distributed teams : optimal role fulfillment
Eubanks, Dawn L.; Palanski, Michael; Olabisi, Joy; Joinson, Adam; Dove, James
2016-01-01
In this study, we explored team roles in virtual, partially distributed teams, or vPDTs (teams with at least one co-located subgroup and at least two subgroups that are geographically dispersed but that collaborate virtually). Past research on virtual teams emphasizes the importance of team dynamics. We argue that the following three roles are particularly important for high functioning virtual teams: Project Coordinator, Implementer and Completer-Finisher. We hypothesized that the highest pe...
Dynamically Optimal Phosphorus Management and Agricultural Water Protection
Iho, Antti; Laukkanen, Marita
2009-01-01
This paper puts forward a model of the role of phosphorus in crop production, soil phosphorus dynamics and phosphorus loading that integrates the salient economic and ecological features of agricultural phosphorus management. The model accounts for the links between phosphorus fertilization, crop yield, accumulation of soil phosphorus reserves, and phosphorus loading. It can be used to guide precision phosphorus management and erosion control as means to mitigate agricultural loading. Using a...
Optimal static and dynamic recycling of defective binary devices
Challet, Damien; Pérez Castillo, Isaac
2004-11-01
The binary defect combination problem consists in finding a fully working subset from a given ensemble of imperfect binary components. We determine the typical properties of the model using methods of statistical mechanics, in particular the region in the parameter space where there is almost surely at least one fully working subset. Dynamic recycling of a flux of imperfect binary components leads to zero wastage.
International Nuclear Information System (INIS)
Yuan, Xiaohui; Ji, Bin; Zhang, Shuangquan; Tian, Hao; Chen, Zhihuan
2014-01-01
Highlights: • Dynamic load economic dispatch with wind power (DLEDW) model is established. • Markov chains combined with scenario analysis method are used to predict wind power. • Chance constrained technique is used to simulate the impacts of wind forecast error. • Improved artificial physical optimization algorithm is proposed to solve DLEDW. • Heuristic search strategies are applied to handle the constraints of DLEDW. - Abstract: Wind power, a kind of promising renewable energy resource, has recently been getting more attractive because of various environmental and economic considerations. But the penetration of wind power with its fluctuation nature has made the operation of power system more intractable. To coordinate the reliability and operation cost, this paper established a stochastic model of dynamic load economic dispatch with wind integration (DLEDW). In this model, constraints such as ramping up/down capacity, prohibited operating zone are considered and effects of valve-point are taken into account. Markov chains combined with scenario analysis method is used to generate predictive values of wind power and chance constrained programming (CCP) is applied to simulate the impacts of wind power fluctuation on system operation. An improved artificial physical optimization algorithm is presented to solve the DLEDW problem. Heuristic strategies based on the priority list and stochastic simulation techniques are proposed to handle the constraints. In addition, a local chaotic mutation strategy is applied to overcome the disadvantage of premature convergence of artificial physical optimization algorithm. Two test systems with and without wind power integration are used to verify the feasibility and effectiveness of the proposed method and the results are compared with those of gravitational search algorithm, particle swarm optimization and standard artificial physical optimization. The simulation results demonstrate that the proposed method has a
Dynamically Selecting Optimal Distribution Strategies for Web Documents
Pierre, G.E.O.; van Steen, M.R.; Tanenbaum, A.S.
2002-01-01
To improve the scalability of the Web, it is common practice to apply caching and replication techniques. Numerous strategies for placing and maintaining multiple copies of Web documents at several sites have been proposed. These approaches essentially apply a global strategy by which a single
Directory of Open Access Journals (Sweden)
Jun-Jie Ma
2007-03-01
Full Text Available The effectiveness of wireless sensor networks (WSNs depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named Ã¢Â€Âœvirtual force directed co-evolutionary particle swarm optimizationÃ¢Â€Â (VFCPSO, since this algorithm combines the co-evolutionary particle swarm optimization (CPSO with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.
Time-limited optimal dynamics beyond the Quantum Speed Limit
DEFF Research Database (Denmark)
Gajdacz, Miroslav; Das, Kunal K.; Arlt, Jan
2015-01-01
-off expressed in terms of the direct Hilbert velocity provides a robust prediction of the quantum speed limit and allows to adapt the control optimization such that it yields a predefined fidelity. The results are verified numerically in a multilevel system with a constrained Hamiltonian, and a classification......The quantum speed limit sets the minimum time required to transfer a quantum system completely into a given target state. At shorter times the higher operation speed has to be paid with a loss of fidelity. Here we quantify the trade-off between the fidelity and the duration in a system driven...
Optimizing Grippers for Compensating Pose Uncertainties by Dynamic Simulation
DEFF Research Database (Denmark)
Wolniakowski, Adam; Kramberger, Aljaz; Gams, Andrej
2016-01-01
Gripper design process is one of the interesting challenges in the context of grasping within industry. Typically, simple parallel-finger grippers, which are easy to install and maintain, are used in platforms for robotic grasping. The context switches in these platforms require frequent exchange......, we have presented a method to automatically compute the optimal finger shapes for defined task contexts in simulation. In this paper, we show the performance of our method in an industrial grasping scenario. We first analyze the uncertainties of the used vision system, which are the major source...
Modelling Data Mining Dynamic Code Attributes with Scheme Definition Technique
Sipayung, Evasaria M; Fiarni, Cut; Tanudjaja, Randy
2014-01-01
Data mining is a technique used in differentdisciplines to search for significant relationships among variablesin large data sets. One of the important steps on data mining isdata preparation. On these step, we need to transform complexdata with more than one attributes into representative format fordata mining algorithm. In this study, we concentrated on thedesigning a proposed system to fetch attributes from a complexdata such as product ID. Then the proposed system willdetermine the basic ...
Moving Target Techniques: Cyber Resilience throught Randomization, Diversity, and Dynamism
2017-03-03
techniques change the static nature of computer systems to increase both the difficulty and the cost (in effort, time, and resources) of mounting...develop a stronger attack by incorporating different exploits against different platforms, but this will increase the cost and workload of the attack...machines at once. This is contrary to many existing systems where if an attacker develops malware , it can successfully compromise millions of machines
Ensinger, Wolfgang
1996-01-01
Influence of plasma density and plasma sheath dynamics on the ion implantation by plasma immersion technique / B. Rauschenbach ... - In: Nuclear instruments and methods in physics research. B. 113. 1996. S. 266-269
Integration of ab-initio nuclear calculation with derivative free optimization technique
Energy Technology Data Exchange (ETDEWEB)
Sharda, Anurag [Iowa State Univ., Ames, IA (United States)
2008-01-01
Optimization techniques are finding their inroads into the field of nuclear physics calculations where the objective functions are very complex and computationally intensive. A vast space of parameters needs searching to obtain a good match between theoretical (computed) and experimental observables, such as energy levels and spectra. Manual calculation defies the scope of such complex calculation and are prone to error at the same time. This body of work attempts to formulate a design and implement it which would integrate the ab initio nuclear physics code MFDn and the VTDIRECT95 code. VTDIRECT95 is a Fortran95 suite of parallel code implementing the derivative-free optimization algorithm DIRECT. Proposed design is implemented for a serial and parallel version of the optimization technique. Experiment with the initial implementation of the design showing good matches for several single-nucleus cases are conducted. Determination and assignment of appropriate number of processors for parallel integration code is implemented to increase the efficiency and resource utilization in the case of multiple nuclei parameter search.
Andriani, Dian; Wresta, Arini; Atmaja, Tinton Dwi; Saepudin, Aep
2014-02-01
Biogas from anaerobic digestion of organic materials is a renewable energy resource that consists mainly of CH4 and CO2. Trace components that are often present in biogas are water vapor, hydrogen sulfide, siloxanes, hydrocarbons, ammonia, oxygen, carbon monoxide, and nitrogen. Considering the biogas is a clean and renewable form of energy that could well substitute the conventional source of energy (fossil fuels), the optimization of this type of energy becomes substantial. Various optimization techniques in biogas production process had been developed, including pretreatment, biotechnological approaches, co-digestion as well as the use of serial digester. For some application, the certain purity degree of biogas is needed. The presence of CO2 and other trace components in biogas could affect engine performance adversely. Reducing CO2 content will significantly upgrade the quality of biogas and enhancing the calorific value. Upgrading is generally performed in order to meet the standards for use as vehicle fuel or for injection in the natural gas grid. Different methods for biogas upgrading are used. They differ in functioning, the necessary quality conditions of the incoming gas, and the efficiency. Biogas can be purified from CO2 using pressure swing adsorption, membrane separation, physical or chemical CO2 absorption. This paper reviews the various techniques, which could be used to optimize the biogas production as well as to upgrade the biogas quality.
DYNAMIC MAGNETIC RESONANCE IMAGING: PRELIMINARY PRESENTATION OF A TECHNIQUE
Directory of Open Access Journals (Sweden)
BRUNO DA COSTA ANCHESCHI
Full Text Available ABSTRACT Objective: To evaluate morphometric variations of the cervical spine in patients with cervical spondylotic myelopathy (CSM using dynamic magnetic resonance imaging (MRI in neutral, flexion and extension positions. Methods: This is a prospective study of patients with CSM secondary to degenerative disease of the cervical spine. The morphometric parameters were evaluated using T2-weighted MRI sequences in the sagittal plane in neutral, flexion and extension position of the neck. The parameters studied were the anterior length of the spinal cord (ALSC, the posterior length of the spinal cord (PLSC, the diameter of the vertebral canal (DVC and the diameter of the spinal cord (DSC. Results: The ALSC and PLSC were longer in flexion than in extension and neutral position, with statistically significant difference between the flexion and extension position. The DVC and the DSC were greater in flexion than in extension and neutral position, however, there was no statistically significant difference when they were compared in the neutral, flexion and extension positions. Conclusion: Dynamic MRI allows to evaluate morphometric variations in the cervical spinal canal in patients with cervical spondylotic myelopathy.
Optimization models and techniques for implementation and pricing of electricity markets
Madrigal Martinez, Marcelino
Vertically integrated electric power systems extensively use optimization models and solution techniques to guide their optimal operation and planning. The advent of electric power systems re-structuring has created needs for new optimization tools and the revision of the inherited ones from the vertical integration era into the market environment. This thesis presents further developments on the use of optimization models and techniques for implementation and pricing of primary electricity markets. New models, solution approaches, and price setting alternatives are proposed. Three different modeling groups are studied. The first modeling group considers simplified continuous and discrete models for power pool auctions driven by central-cost minimization. The direct solution of the dual problems, and the use of a Branch-and-Bound algorithm to solve the primal, allows to identify the effects of disequilibrium, and different price setting alternatives over the existence of multiple solutions. It is shown that particular pricing rules worsen the conflict of interest that arise when multiple solutions exist under disequilibrium. A price-setting alternative based on dual variables is shown to diminish such conflict. The second modeling group considers the unit commitment problem. An interior-point/cutting-plane method is proposed for the solution of the dual problem. The new method has better convergence characteristics and does not suffer from the parameter tuning drawback as previous methods The robustness characteristics of the interior-point/cutting-plane method, combined with a non-uniform price setting alternative, show that the conflict of interest is diminished when multiple near optimal solutions exist. The non-uniform price setting alternative is compared to a classic average pricing rule. The last modeling group concerns to a new type of linear network-constrained clearing system models for daily markets for power and spinning reserve. A new model and
Optimizing Dynamic Class Composition in a Statically Typed Language
DEFF Research Database (Denmark)
Nielsen, Anders Bach; Ernst, Erik
2008-01-01
this is achieved based on mixins and linearization. In this paper we focus on the virtual machine related challenges of supporting dynamic class composition. In particular we present some core algorithms used for creating new classes, as well as some performance enhancements in these algorithms.......In statically typed languages the set of classes and similar classifiers is commonly fully determined at compile time. Complete classifier representations can then be loaded at run-time, e.g., from a an executable file or a class file. However, some typing constructs-such as virtual classes...
Hernandez, Wilmar
2007-01-01
In this paper a survey on recent applications of optimal signal processing techniques to improve the performance of mechanical sensors is made. Here, a comparison between classical filters and optimal filters for automotive sensors is made, and the current state of the art of the application of robust and optimal control and signal processing techniques to the design of the intelligent (or smart) sensors that today's cars need is presented through several experimental results that show that the fusion of intelligent sensors and optimal signal processing techniques is the clear way to go. However, the switch between the traditional methods of designing automotive sensors and the new ones cannot be done overnight because there are some open research issues that have to be solved. This paper draws attention to one of the open research issues and tries to arouse researcher's interest in the fusion of intelligent sensors and optimal signal processing techniques.
International Nuclear Information System (INIS)
Hosseini-Ashrafi, M.E.; Bagherebadian, H.; Yahaqi, E.
1999-01-01
A method has been developed which, by using the geometric information from treatment sample cases, selects from a given data set an initial treatment plan as a step for treatment plan optimization. The method uses an artificial neural network (ANN) classification technique to select a best matching plan from the 'optimized' ANN database. Separate back-propagation ANN classifiers were trained using 50, 60 and 77 examples for three groups of treatment case classes (up to 21 examples from each class were used). The performance of the classifiers in selecting the correct treatment class was tested using the leave-one-out method; the networks were optimized with respect their architecture. For the three groups used in this study, successful classification fractions of 0.83, 0.98 and 0.93 were achieved by the optimized ANN classifiers. The automated response of the ANN may be used to arrive at a pre-plan where many treatment parameters may be identified and therefore a significant reduction in the steps required to arrive at the optimum plan may be achieved. Treatment planning 'experience' and also results from lengthy calculations may be used for training the ANN. (author)
Optimized Scheduling Technique of Null Subcarriers for Peak Power Control in 3GPP LTE Downlink
Park, Sang Kyu
2014-01-01
Orthogonal frequency division multiple access (OFDMA) is a key multiple access technique for the long term evolution (LTE) downlink. However, high peak-to-average power ratio (PAPR) can cause the degradation of power efficiency. The well-known PAPR reduction technique, dummy sequence insertion (DSI), can be a realistic solution because of its structural simplicity. However, the large usage of subcarriers for the dummy sequences may decrease the transmitted data rate in the DSI scheme. In this paper, a novel DSI scheme is applied to the LTE system. Firstly, we obtain the null subcarriers in single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems, respectively; then, optimized dummy sequences are inserted into the obtained null subcarrier. Simulation results show that Walsh-Hadamard transform (WHT) sequence is the best for the dummy sequence and the ratio of 16 to 20 for the WHT and randomly generated sequences has the maximum PAPR reduction performance. The number of near optimal iteration is derived to prevent exhausted iterations. It is also shown that there is no bit error rate (BER) degradation with the proposed technique in LTE downlink system. PMID:24883376
Optimized scheduling technique of null subcarriers for peak power control in 3GPP LTE downlink.
Cho, Soobum; Park, Sang Kyu
2014-01-01
Orthogonal frequency division multiple access (OFDMA) is a key multiple access technique for the long term evolution (LTE) downlink. However, high peak-to-average power ratio (PAPR) can cause the degradation of power efficiency. The well-known PAPR reduction technique, dummy sequence insertion (DSI), can be a realistic solution because of its structural simplicity. However, the large usage of subcarriers for the dummy sequences may decrease the transmitted data rate in the DSI scheme. In this paper, a novel DSI scheme is applied to the LTE system. Firstly, we obtain the null subcarriers in single-input single-output (SISO) and multiple-input multiple-output (MIMO) systems, respectively; then, optimized dummy sequences are inserted into the obtained null subcarrier. Simulation results show that Walsh-Hadamard transform (WHT) sequence is the best for the dummy sequence and the ratio of 16 to 20 for the WHT and randomly generated sequences has the maximum PAPR reduction performance. The number of near optimal iteration is derived to prevent exhausted iterations. It is also shown that there is no bit error rate (BER) degradation with the proposed technique in LTE downlink system.
Cluster Optimization and Parallelization of Simulations with Dynamically Adaptive Grids
Schreiber, Martin
2013-01-01
The present paper studies solvers for partial differential equations that work on dynamically adaptive grids stemming from spacetrees. Due to the underlying tree formalism, such grids efficiently can be decomposed into connected grid regions (clusters) on-the-fly. A graph on those clusters classified according to their grid invariancy, workload, multi-core affinity, and further meta data represents the inter-cluster communication. While stationary clusters already can be handled more efficiently than their dynamic counterparts, we propose to treat them as atomic grid entities and introduce a skip mechanism that allows the grid traversal to omit those regions completely. The communication graph ensures that the cluster data nevertheless are kept consistent, and several shared memory parallelization strategies are feasible. A hyperbolic benchmark that has to remesh selected mesh regions iteratively to preserve conforming tessellations acts as benchmark for the present work. We discuss runtime improvements resulting from the skip mechanism and the implications on shared memory performance and load balancing. © 2013 Springer-Verlag.
International Nuclear Information System (INIS)
Behrang, M.A.; Assareh, E.; Noghrehabadi, A.R.; Ghanbarzadeh, A.
2011-01-01
PSO (particle swarm optimization) technique is applied to estimate monthly average daily GSR (global solar radiation) on horizontal surface for different regions of Iran. To achieve this, five new models were developed as well as six models were chosen from the literature. First, for each city, the empirical coefficients for all models were separately determined using PSO technique. The results indicate that new models which are presented in this study have better performance than existing models in the literature for 10 cities from 17 considered cities in this study. It is also shown that the empirical coefficients found for a given latitude can be generalized to estimate solar radiation in cities at similar latitude. Some case studies are presented to demonstrate this generalization with the result showing good agreement with the measurements. More importantly, these case studies further validate the models developed, and demonstrate the general applicability of the models developed. Finally, the obtained results of PSO technique were compared with the obtained results of SRTs (statistical regression techniques) on Angstrom model for all 17 cities. The results showed that obtained empirical coefficients for Angstrom model based on PSO have more accuracy than SRTs for all 17 cities. -- Highlights: → The first study to apply an intelligent optimization technique to more accurately determine empirical coefficients in solar radiation models. → New models which are presented in this study have better performance than existing models. → The empirical coefficients found for a given latitude can be generalized to estimate solar radiation in cities at similar latitude. → A fair comparison between the performance of PSO and SRTs on GSR modeling.
The use of the partial coherence function technique for the investigation of BWR noise dynamics
International Nuclear Information System (INIS)
Kostic, Lj.
1983-01-01
The extensive experimental investigations, at the last time, indicate that the partial coherence function technique can be a powerful method of the investigation of BWR noise dynamics. Symple BWR noise dynamics model for the global noise study, based on different noise phenomena, is proposed in this paper. (author)
Directory of Open Access Journals (Sweden)
Maria Oksa
2011-09-01
Full Text Available In this work High Velocity Oxy-fuel (HVOF thermal spray techniques, spraying process optimization, and characterization of coatings are reviewed. Different variants of the technology are described and the main differences in spray conditions in terms of particle kinetics and thermal energy are rationalized. Methods and tools for controlling the spray process are presented as well as their use in optimizing the coating process. It will be shown how the differences from the starting powder to the final coating formation affect the coating microstructure and performance. Typical properties of HVOF sprayed coatings and coating performance is described. Also development of testing methods used for the evaluation of coating properties and current status of standardization is presented. Short discussion of typical applications is done.
Directory of Open Access Journals (Sweden)
G. Senthilkumar
2014-09-01
Full Text Available In this work, transesterification of sunflower oil for obtaining biodiesel was studied. Taguchi’s methodology (L9 orthogonal array was selected to optimize the most significant variables (methanol, catalyst concentration and stirrer speed in transesterification process. Experiments have conducted based on development of L9 orthogonal array by using Taguchi technique. Analysis of Variance (ANOVA and the regression equations were used to find the optimum yield of sunflower methyl ester under the influence of methanol, catalyst & stirrer speed. The study resulted in a maximum yield of sun flower methyl ester as 96% with the optimal conditions of methanol 110 ml with 0.5% by wt. of sodium hydroxide (NaOH stirred at 1200 rpm. The yield was analyzed on the basis of “larger is better”. Finally, confirmation tests were carried out to verify the experimental results.
Monte Carlo techniques for real-time quantum dynamics
International Nuclear Information System (INIS)
Dowling, Mark R.; Davis, Matthew J.; Drummond, Peter D.; Corney, Joel F.
2007-01-01
The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the 'weight', and its magnitude is related to the importance of the stochastic trajectory. We investigate the use of Monte Carlo algorithms to improve the sampling of the weighted trajectories and thus reduce sampling error in a simulation of quantum dynamics. The method can be applied to calculations in real time, as well as imaginary time for which Monte Carlo algorithms are more-commonly used. The Monte-Carlo algorithms are applicable when the weight is guaranteed to be real, and we demonstrate how to ensure this is the case. Examples are given for the anharmonic oscillator, where large improvements over stochastic sampling are observed
Nonlinear systems techniques for dynamical analysis and control
Lefeber, Erjen; Arteaga, Ines
2017-01-01
This treatment of modern topics related to the control of nonlinear systems is a collection of contributions celebrating the work of Professor Henk Nijmeijer and honoring his 60th birthday. It addresses several topics that have been the core of Professor Nijmeijer’s work, namely: the control of nonlinear systems, geometric control theory, synchronization, coordinated control, convergent systems and the control of underactuated systems. The book presents recent advances in these areas, contributed by leading international researchers in systems and control. In addition to the theoretical questions treated in the text, particular attention is paid to a number of applications including (mobile) robotics, marine vehicles, neural dynamics and mechanical systems generally. This volume provides a broad picture of the analysis and control of nonlinear systems for scientists and engineers with an interest in the interdisciplinary field of systems and control theory. The reader will benefit from the expert participan...
A wave dynamics criterion for optimization of mammalian cardiovascular system.
Pahlevan, Niema M; Gharib, Morteza
2014-05-07
The cardiovascular system in mammals follows various optimization criteria covering the heart, the vascular network, and the coupling of the two. Through a simple dimensional analysis we arrived at a non-dimensional number (wave condition number) that can predict the optimum wave state in which the left ventricular (LV) pulsatile power (LV workload) is minimized in a mammalian cardiovascular system. This number is also universal among all mammals independent of animal size maintaining a value of around 0.1. By utilizing a unique in vitro model of human aorta, we tested our hypothesis against a wide range of aortic compliance (pulse wave velocity). We concluded that the optimum value of the wave condition number remains to be around 0.1 for a wide range of aorta compliance that we could simulate in our in-vitro system. Copyright © 2014 Elsevier Ltd. All rights reserved.
Optimizing Grippers for Compensating Pose Uncertainties by Dynamic Simulation
DEFF Research Database (Denmark)
Wolniakowski, Adam; Kramberger, Aljaž; Gams, Andrej
2017-01-01
, we have presented a method to automatically compute the optimal finger shapes for defined task contexts in simulation. In this paper, we show the performance of our method in an industrial grasping scenario. We first analyze the uncertainties of the used vision system, which are the major source......Gripper design process is one of the interesting challenges in the context of grasping within industry. Typically, simple parallel-finger grippers, which are easy to install and maintain, are used in platforms for robotic grasping. The context switches in these platforms require frequent exchange...... of gripper fingers to accommodate grasping of new products, while subjected to numerous constraints, such as workcell uncertainties due to the vision systems used. The design of these fingers consumes the man-hours of experienced engineers, and involves a lot of trial-and-error testing. In our previous work...
Performance optimization of ERP-based BCIs using dynamic stopping.
Schreuder, Martijn; Hohne, Johannes; Treder, Matthias; Blankertz, Benjamin; Tangermann, Michael
2011-01-01
Brain-computer interfaces based on event-related potentials face a trade-off between the speed and accuracy of the system, as both depend on the number of iterations. Increasing the number of iterations leads to a higher accuracy but reduces the speed of the system. This trade-off is generally dealt with by finding a fixed number of iterations that give a good result on the calibration data. We show here that this method is sub optimal and increases the performance significantly in only one out of five datasets. Several alternative methods have been described in literature, and we test the generalization of four of them. One method, called rank diff, significantly increased the performance over all datasets. These findings are important, as they show that 1) one should be cautious when reporting the potential performance of a BCI based on post-hoc offline performance curves and 2) simple methods are available that do boost performance.
International Nuclear Information System (INIS)
Giniyatulin, R.N.; Komarov, V.L.; Kuzmin, E.G.; Makhankov, A.N.; Mazul, I.V.; Yablokov, N.A.; Zhuk, A.N.
2002-01-01
Joining of tungsten with copper-based cooling structure and armour geometry optimization are the major aspects in development of the tungsten-armoured plasma facing components (PFC). Fabrication techniques and high heat flux (HHF) tests of tungsten-armoured components have to reflect different PFC designs and acceptable manufacturing cost. The authors present the recent results of tungsten-armoured mock-ups development based on manufacturing and HHF tests. Two aspects were investigated--selection of armour geometry and examination of tungsten-copper bonding techniques. Brazing and casting tungsten-copper bonding techniques were used in small mock-ups. The mock-ups with armour tiles (20x5x10, 10x10x10, 20x20x10, 27x27x10) mm 3 in dimensions were tested by cyclic heat fluxes in the range of (5-20) MW/m 2 , the number of thermal cycles varied from hundreds to several thousands for each mock-up. The results of the tests show the applicability of different geometry and different bonding technique to corresponding heat loading. A medium-scale mock-up 0.6-m in length was manufactured and tested. HHF tests of the medium-scale mock-up have demonstrated the applicability of the applied bonding techniques and armour geometry for full-scale PFC's manufacturing
Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics
Energy Technology Data Exchange (ETDEWEB)
Liu, Guodong [ORNL; Li, Zhi [ORNL; Starke, Michael R. [ORNL; Ollis, Ben [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)
2017-07-01
This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.
Aziz, Jonathan D.; Parker, Jeffrey S.; Scheeres, Daniel J.; Englander, Jacob A.
2018-01-01
Low-thrust trajectories about planetary bodies characteristically span a high count of orbital revolutions. Directing the thrust vector over many revolutions presents a challenging optimization problem for any conventional strategy. This paper demonstrates the tractability of low-thrust trajectory optimization about planetary bodies by applying a Sundman transformation to change the independent variable of the spacecraft equations of motion to an orbit angle and performing the optimization with differential dynamic programming. Fuel-optimal geocentric transfers are computed with the transfer duration extended up to 2000 revolutions. The flexibility of the approach to higher fidelity dynamics is shown with Earth's J 2 perturbation and lunar gravity included for a 500 revolution transfer.
Zainal Ariffin, S.; Razlan, A.; Ali, M. Mohd; Efendee, A. M.; Rahman, M. M.
2018-03-01
Background/Objectives: The paper discusses about the optimum cutting parameters with coolant techniques condition (1.0 mm nozzle orifice, wet and dry) to optimize surface roughness, temperature and tool wear in the machining process based on the selected setting parameters. The selected cutting parameters for this study were the cutting speed, feed rate, depth of cut and coolant techniques condition. Methods/Statistical Analysis Experiments were conducted and investigated based on Design of Experiment (DOE) with Response Surface Method. The research of the aggressive machining process on aluminum alloy (A319) for automotive applications is an effort to understand the machining concept, which widely used in a variety of manufacturing industries especially in the automotive industry. Findings: The results show that the dominant failure mode is the surface roughness, temperature and tool wear when using 1.0 mm nozzle orifice, increases during machining and also can be alternative minimize built up edge of the A319. The exploration for surface roughness, productivity and the optimization of cutting speed in the technical and commercial aspects of the manufacturing processes of A319 are discussed in automotive components industries for further work Applications/Improvements: The research result also beneficial in minimizing the costs incurred and improving productivity of manufacturing firms. According to the mathematical model and equations, generated by CCD based RSM, experiments were performed and cutting coolant condition technique using size nozzle can reduces tool wear, surface roughness and temperature was obtained. Results have been analyzed and optimization has been carried out for selecting cutting parameters, shows that the effectiveness and efficiency of the system can be identified and helps to solve potential problems.
International Nuclear Information System (INIS)
Liu, Xingrang; Bansal, R.C.
2014-01-01
Highlights: • A coal fired power plant boiler combustion process model based on real data. • We propose multi-objective optimization with CFD to optimize boiler combustion. • The proposed method uses software CORBA C++ and ANSYS Fluent 14.5 with AI. • It optimizes heat flux transfers and maintains temperature to avoid ash melt. - Abstract: The dominant role of electricity generation and environment consideration have placed strong requirements on coal fired power plants, requiring them to improve boiler combustion efficiency and decrease carbon emission. Although neural network based optimization strategies are often applied to improve the coal fired power plant boiler efficiency, they are limited by some combustion related problems such as slagging. Slagging can seriously influence heat transfer rate and decrease the boiler efficiency. In addition, it is difficult to measure slag build-up. The lack of measurement for slagging can restrict conventional neural network based coal fired boiler optimization, because no data can be used to train the neural network. This paper proposes a novel method of integrating non-dominated sorting genetic algorithm (NSGA II) based multi-objective optimization with computational fluid dynamics (CFD) to decrease or even avoid slagging inside a coal fired boiler furnace and improve boiler combustion efficiency. Compared with conventional neural network based boiler optimization methods, the method developed in the work can control and optimize the fields of flue gas properties such as temperature field inside a boiler by adjusting the temperature and velocity of primary and secondary air in coal fired power plant boiler control systems. The temperature in the vicinity of water wall tubes of a boiler can be maintained within the ash melting temperature limit. The incoming ash particles cannot melt and bond to surface of heat transfer equipment of a boiler. So the trend of slagging inside furnace is controlled. Furthermore, the
Modeling Illicit Drug Use Dynamics and Its Optimal Control Analysis
Directory of Open Access Journals (Sweden)
Steady Mushayabasa
2015-01-01
Full Text Available The global burden of death and disability attributable to illicit drug use, remains a significant threat to public health for both developed and developing nations. This paper presents a new mathematical modeling framework to investigate the effects of illicit drug use in the community. In our model the transmission process is captured as a social “contact” process between the susceptible individuals and illicit drug users. We conduct both epidemic and endemic analysis, with a focus on the threshold dynamics characterized by the basic reproduction number. Using our model, we present illustrative numerical results with a case study in Cape Town, Gauteng, Mpumalanga and Durban communities of South Africa. In addition, the basic model is extended to incorporate time dependent intervention strategies.
A three-stage strategy for optimal price offering by a retailer based on clustering techniques
International Nuclear Information System (INIS)
Mahmoudi-Kohan, N.; Shayesteh, E.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.
2010-01-01
In this paper, an innovative strategy for optimal price offering to customers for maximizing the profit of a retailer is proposed. This strategy is based on load profile clustering techniques and includes three stages. For the purpose of clustering, an improved weighted fuzzy average K-means is proposed. Also, in this paper a new acceptance function for increasing the profit of the retailer is proposed. The new method is evaluated by implementation on a group of 300 customers of a 20 kV distribution network. (author)
Reconstruction of plasma current profile of tokamaks using combinatorial optimization techniques
International Nuclear Information System (INIS)
Kishimoto, Maki; Sakasai, Kaoru; Ara, Katuyuki; Suzuki, Yasuo; Fujita, Takaaki
1996-01-01
New methods to reconstruct plasma shape and plasma current distribution from magnetic measurements are proposed. The reconstruction of plasma current profile from magnetic measurements is regarded as an optimum allocation problem of currents into cross section of the vacuum vessel of the tokamak. For solving this optimization problem, the authors use two types of solutions: a genetic algorithm and a combined method of a Hopfield neural network and a genetic algorithm. The effectiveness of these methods is shown by the application of these techniques to JT-60U plasmas
Energy Technology Data Exchange (ETDEWEB)
Guarino, Vincenzo, E-mail: vguarino@unina.it; Altobelli, Rosaria; Cirillo, Valentina; Ambrosio, Luigi [Institute for Polymers, Composites and Biomaterials, Department of Chemical Sciences & Materials Technology, National Research Council of Italy, V.le Kennedy 54, Naples (Italy)
2015-12-17
A large variety of processes and tools is continuously investigated to discover new solutions to design instructive materials with controlled chemical, physical and biological properties for tissue engineering and drug delivery. Among them, electro fluido dynamic techniques (EFDTs) are emerging as an interesting strategy, based on highly flexible and low-cost processes, to revisit old biomaterial’s manufacturing approach by utilizing electrostatic forces as the driving force for the fabrication of 3D architectures with controlled physical and chemical functionalities to guide in vitro and in vivo cell activities. By a rational selection of polymer solution properties and process conditions, EFDTs allow to produce fibres and/or particles at micro and/or nanometric size scale which may be variously assembled by tailored experimental setups, thus giving the chance to generate a plethora of different 3D devices able to incorporate biopolymers (i.e., proteins, polysaccharides) or active molecules (e.g., drugs) for different applications. Here, we focus on the optimization of basic EFDTs - namely electrospinning, electrospraying and electrodynamic atomization - to develop active platforms (i.e., monocomponent, protein and drug loaded scaffolds and µ-scaffolds) made of synthetic (PCL, PLGA) or natural (chitosan, alginate) polymers. In particular, we investigate how to set materials and process parameters to impart specific morphological, biochemical or physical cues to trigger all the fundamental cell–biomaterial and cell– cell cross-talking elicited during regenerative processes, in order to reproduce the complex microenvironment of native or pathological tissues.
A dynamic optimization on economic energy efficiency in development: A numerical case of China
International Nuclear Information System (INIS)
Wang, Dong
2014-01-01
This paper is based on dynamic optimization methodology to investigate the economic energy efficiency issues in developing countries. The paper introduces some definitions about energy efficiency both in economics and physics, and establishes a quantitative way for measuring the economic energy efficiency. The linkage between economic energy efficiency, energy consumption and other macroeconomic variables is demonstrated primarily. Using the methodology of dynamic optimization, a maximum problem of economic energy efficiency over time, which is subjected to the extended Solow growth model and instantaneous investment rate, is modelled. In this model, the energy consumption is set as a control variable and the capital is regarded as a state variable. The analytic solutions can be derived and the diagrammatic analysis provides saddle-point equilibrium. A numerical simulation based on China is also presented; meanwhile, the optimal paths of investment and energy consumption can be drawn. The dynamic optimization encourages governments in developing countries to pursue higher economic energy efficiency by controlling the energy consumption and regulating the investment state as it can conserve energy without influencing the achievement of steady state in terms of Solow model. If that, a sustainable development will be achieved. - Highlights: • A new definition on economic energy efficiency is proposed mathematically. • A dynamic optimization modelling links economic energy efficiency with other macroeconomic variables in long run. • Economic energy efficiency is determined by capital stock level and energy consumption. • Energy saving is a key solution for improving economic energy efficiency
Optimal dynamic premium control in non-life insurance. Maximizing dividend pay-outs
DEFF Research Database (Denmark)
Højgaard, Bjarne
2002-01-01
loading with the possibility of gaining or loosing customers. It distributes dividends according to a 'barrier strategy' and the objective of the company is to find an optimal premium policy and dividend barrier maximizing the expected total, discounted pay-out of dividends. In the case of exponential......In this paper we consider the problem of finding optimal dynamic premium policies in non-life insurance. The reserve of a company is modeled using the classical Cramér-Lundberg model with premium rates calculated via the expected value principle. The company controls dynamically the relative safety...
Zilberman, David
2014-01-01
This volume explores the emerging and current, cutting-edge theories and methods of modeling, optimization, dynamics and bioeconomy. It provides an overview of the main issues, results and open questions in these fields as well as covers applications to biology, economy, energy, industry, physics, psychology and finance. The majority of the contributed papers for this volume come from the participants of the International Conference on Modeling, Optimization and Dynamics (ICMOD 2010), a satellite conference of EURO Mathematical Physics and MathematicsIV Lisbon 2010, which took place at Faculty of Sciences of University of Porto, Portugal, and from the Berkeley Bioeconomy Conference 2012, at the University of California, Berkeley, USA.
Analysis of Ant Colony Optimization and Population-Based Evolutionary Algorithms on Dynamic Problems
DEFF Research Database (Denmark)
Lissovoi, Andrei
the dynamic optimum for finite alphabets up to size μ, while MMAS is able to do so for any finite alphabet size. Parallel Evolutionary Algorithms on Maze. We prove that while a (1 + λ) EA is unable to track the optimum of the dynamic fitness function Maze for offspring population size up to λ = O(n1-ε......This thesis presents new running time analyses of nature-inspired algorithms on various dynamic problems. It aims to identify and analyse the features of algorithms and problem classes which allow efficient optimization to occur in the presence of dynamic behaviour. We consider the following...... settings: λ-MMAS on Dynamic Shortest Path Problems. We investigate how in-creasing the number of ants simulated per iteration may help an ACO algorithm to track optimum in a dynamic problem. It is shown that while a constant number of ants per-vertex is sufficient to track some oscillations, there also...
Directory of Open Access Journals (Sweden)
Anish Pandey
2017-02-01
Full Text Available This article introduces a singleton type-1 fuzzy logic system (T1-SFLS controller and Fuzzy-WDO hybrid for the autonomous mobile robot navigation and collision avoidance in an unknown static and dynamic environment. The WDO (Wind Driven Optimization algorithm is used to optimize and tune the input/output membership function parameters of the fuzzy controller. The WDO algorithm is working based on the atmospheric motion of infinitesimal small air parcels navigates over an N-dimensional search domain. The performance of this proposed technique has compared through many computer simulations and real-time experiments by using Khepera-III mobile robot. As compared to the T1-SFLS controller the Fuzzy-WDO algorithm is found good agreement for mobile robot navigation.
Biswas, Abhishek; Ranjan, Desh; Zubair, Mohammad; He, Jing
2015-09-01
The determination of secondary structure topology is a critical step in deriving the atomic structures from the protein density maps obtained from electron cryomicroscopy technique. This step often relies on matching the secondary structure traces detected from the protein density map to the secondary structure sequence segments predicted from the amino acid sequence. Due to inaccuracies in both sources of information, a pool of possible secondary structure positions needs to be sampled. One way to approach the problem is to first derive a small number of possible topologies using existing matching algorithms, and then find the optimal placement for each possible topology. We present a dynamic programming method of Θ(Nq(2)h) to find the optimal placement for a secondary structure topology. We show that our algorithm requires significantly less computational time than the brute force method that is in the order of Θ(q(N) h).
Use of System Dynamics Techniques in the Garrison Health Modelling Tool
2010-11-01
Joint Health Command (JHC) tasked DSTO to develop techniques for modelling Defence health service delivery both in a Garrison environment in Australia ...UNCLASSIFIED UNCLASSIFIED Use of System Dynamics Techniques in the Garrison Health Modelling Tool Mark Burnett, Kerry Clifford and...Garrison Health Modelling Tool, a prototype software package designed to provide decision-support to JHC health officers and managers in a garrison