Some New Locally Optimal Control Laws for Sailcraft Dynamics in Heliocentric Orbits
Directory of Open Access Journals (Sweden)
F. A. Abd El-Salam
2013-01-01
Full Text Available The concept of solar sailing and its developing spacecraft is presented. The gravitational and solar radiation forces are considered. The effect of source of radiation pressure and the force due to coronal mass ejections and solar wind on the sailcraft configurations is modeled. Some analytical control laws with some mentioned input constraints for optimizing sailcraft dynamics in heliocentric orbit using lagrange’s planetary equations are obtained. Optimum force vector in a required direction is maximized by deriving optimal sail cone angle. Ignoring the absorbed and diffusely reflected parts of the radiation, some special cases are obtained. New control laws that maximize thrust to obtain certain required maximization in some particular orbital element are obtained.
Dynamic optimization of a dead-end filtration trajectory: Blocking filtration laws
Blankert, B.; Betlem, Bernardus H.L.; Roffel, B.
2006-01-01
An operating model for dead-end membrane filtration is proposed based on the well-known blocking laws. The resulting model contains three parameters representing, the operating strategy, the fouling mechanism and the fouling potential of the feed. The optimal control strategy is determined by
Optimal guidance law in quantum mechanics
International Nuclear Information System (INIS)
Yang, Ciann-Dong; Cheng, Lieh-Lieh
2013-01-01
Following de Broglie’s idea of a pilot wave, this paper treats quantum mechanics as a problem of stochastic optimal guidance law design. The guidance scenario considered in the quantum world is that an electron is the flight vehicle to be guided and its accompanying pilot wave is the guidance law to be designed so as to guide the electron to a random target driven by the Wiener process, while minimizing a cost-to-go function. After solving the stochastic optimal guidance problem by differential dynamic programming, we point out that the optimal pilot wave guiding the particle’s motion is just the wavefunction Ψ(t,x), a solution to the Schrödinger equation; meanwhile, the closed-loop guidance system forms a complex state–space dynamics for Ψ(t,x), from which quantum operators emerge naturally. Quantum trajectories under the action of the optimal guidance law are solved and their statistical distribution is shown to coincide with the prediction of the probability density function Ψ ∗ Ψ. -- Highlights: •Treating quantum mechanics as a pursuit-evasion game. •Reveal an interesting analogy between guided flight motion and guided quantum motion. •Solve optimal quantum guidance problem by dynamic programming. •Gives a formal proof of de Broglie–Bohm’s idea of a pilot wave. •The optimal pilot wave is shown to be a wavefunction solved from Schrödinger equation
Optimal guidance law in quantum mechanics
Energy Technology Data Exchange (ETDEWEB)
Yang, Ciann-Dong, E-mail: cdyang@mail.ncku.edu.tw; Cheng, Lieh-Lieh, E-mail: leo8101@hotmail.com
2013-11-15
Following de Broglie’s idea of a pilot wave, this paper treats quantum mechanics as a problem of stochastic optimal guidance law design. The guidance scenario considered in the quantum world is that an electron is the flight vehicle to be guided and its accompanying pilot wave is the guidance law to be designed so as to guide the electron to a random target driven by the Wiener process, while minimizing a cost-to-go function. After solving the stochastic optimal guidance problem by differential dynamic programming, we point out that the optimal pilot wave guiding the particle’s motion is just the wavefunction Ψ(t,x), a solution to the Schrödinger equation; meanwhile, the closed-loop guidance system forms a complex state–space dynamics for Ψ(t,x), from which quantum operators emerge naturally. Quantum trajectories under the action of the optimal guidance law are solved and their statistical distribution is shown to coincide with the prediction of the probability density function Ψ{sup ∗}Ψ. -- Highlights: •Treating quantum mechanics as a pursuit-evasion game. •Reveal an interesting analogy between guided flight motion and guided quantum motion. •Solve optimal quantum guidance problem by dynamic programming. •Gives a formal proof of de Broglie–Bohm’s idea of a pilot wave. •The optimal pilot wave is shown to be a wavefunction solved from Schrödinger equation.
Pozo, Carlos; Marín-Sanguino, Alberto; Alves, Rui; Guillén-Gosálbez, Gonzalo; Jiménez, Laureano; Sorribas, Albert
2011-08-25
Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
Directory of Open Access Journals (Sweden)
Sorribas Albert
2011-08-01
Full Text Available Abstract Background Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
Relativistic dynamics without conservation laws
Rothenstein, Bernhard; Popescu, Stefan
2006-01-01
We show that relativistic dynamics can be approached without using conservation laws (conservation of momentum, of energy and of the centre of mass). Our approach avoids collisions that are not easy to teach without mnemonic aids. The derivations are based on the principle of relativity and on its direct consequence, the addition law of relativistic velocities.
Optimal enforcement of competition law
Motchenkova, E.
2005-01-01
Despite the recent theoretical developments in the field of antitrust law enforcement, much still needs to be done in order to prevent collusion and price-fixing in the major indiustries. Although penalties were recently increased considerably and new instruments of cartel deterrence such as
Temperature Scaling Law for Quantum Annealing Optimizers.
Albash, Tameem; Martin-Mayor, Victor; Hen, Itay
2017-09-15
Physical implementations of quantum annealing unavoidably operate at finite temperatures. We point to a fundamental limitation of fixed finite temperature quantum annealers that prevents them from functioning as competitive scalable optimizers and show that to serve as optimizers annealer temperatures must be appropriately scaled down with problem size. We derive a temperature scaling law dictating that temperature must drop at the very least in a logarithmic manner but also possibly as a power law with problem size. We corroborate our results by experiment and simulations and discuss the implications of these to practical annealers.
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......), is applied to the same problem as a benchmark. RDO and PT turn out to produce solutions of similar quality for similar numerical effort, but RDO is simpler to program and additionally yields geometrical information on the system’s configuration space which is of interest in many applications. In particular...
Do dynamical systems follow Benford's law?
International Nuclear Information System (INIS)
Tolle, Charles R.; Budzien, Joanne L.; LaViolette, Randall A.
2000-01-01
Data compiled from a variety of sources follow Benford's law, which gives a monotonically decreasing distribution of the first digit (1 through 9). We examine the frequency of the first digit of the coordinates of the trajectories generated by some common dynamical systems. One-dimensional cellular automata fulfill the expectation that the frequency of the first digit is uniform. The molecular dynamics of fluids, on the other hand, provides trajectories that follow Benford's law. Finally, three chaotic systems are considered: Lorenz, Henon, and Roessler. The Lorenz system generates trajectories that follow Benford's law. The Henon system generates trajectories that resemble neither the uniform distribution nor Benford's law. Finally, the Roessler system generates trajectories that follow the uniform distribution for some parameters choices, and Benford's law for others. (c) 2000 American Institute of Physics
English Law Terms: Optimizing Education Process
Directory of Open Access Journals (Sweden)
Alexandra G. Anisimova
2014-01-01
Full Text Available The article focuses on the terminology of English law as a system. It deals with the main specific characteristics of the English legal terminology and studies the systemic nature of the terminology of Criminal Law. Nowadays, an increasing role of the study of professional language (Language for Specific Purposes is obvious since it is a means of dissemination and exchange of professional information and a means of communication in the professional discourse. It is a system of terms that constitutes the core of the Language for Specific Purposes. The study of terminology is of paramount importance for the legal sphere of human activity where the accuracy of interpretation plays a very substantial part. Legal terms have a number of specific characteristics, such as: abstract nature of legal notions; introduction of new terms by regulatory organizations; an important role of judicial interpretation in constituting shades of meaning of a legal terminological unit; and the fact that a legal term may belong to a particular area of Law, which makes it possible to refer it to the category of general legal, branch-wise, or inter-branch vocabulary. Every term has its particular place among other elements of a system and is related to them in a particular way. A terminological system should be considered as a whole, and there are particular hierarchical relations between its elements. Within a terminological system, it is possible to seta hierarchy of generic and specific terms that can form the so-called semantic field. One of the features demonstrating the systemic links within a terminology is the existence of some typical structural models, according to which terms are coined. An important criterion is the predominance ofterminological word-combinations of a certain type. For example, in the terminology of Criminal Law the models Noun + Preposition + Noun and Adjective + Noun are the most common structural models. Another important criterion of a
Optimization with Extremal Dynamics
International Nuclear Information System (INIS)
Boettcher, Stefan; Percus, Allon G.
2001-01-01
We explore a new general-purpose heuristic for finding high-quality solutions to hard discrete optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. Extremal optimization successively updates extremely undesirable variables of a single suboptimal solution, assigning them new, random values. Large fluctuations ensue, efficiently exploring many local optima. We use extremal optimization to elucidate the phase transition in the 3-coloring problem, and we provide independent confirmation of previously reported extrapolations for the ground-state energy of ±J spin glasses in d=3 and 4
Truncated Wigner dynamics and conservation laws
Drummond, Peter D.; Opanchuk, Bogdan
2017-10-01
Ultracold Bose gases can be used to experimentally test many-body theory predictions. Here we point out that both exact conservation laws and dynamical invariants exist in the topical case of the one-dimensional Bose gas, and these provide an important validation of methods. We show that the first four quantum conservation laws are exactly conserved in the approximate truncated Wigner approach to many-body quantum dynamics. Center-of-mass position variance is also exactly calculable. This is nearly exact in the truncated Wigner approximation, apart from small terms that vanish as N-3 /2 as N →∞ with fixed momentum cutoff. Examples of this are calculated in experimentally relevant, mesoscopic cases.
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...
Fundamental laws of relativistic classical dynamics revisited
International Nuclear Information System (INIS)
Blaquiere, Augustin
1977-01-01
By stating that a linear differential form, whose coefficients are the components of the momentum and the energy of a particle, has an antiderivative, the basic equations of the dynamics of points are obtained, in the relativistic case. From the point of view of optimization theory, a connection between our condition and the Bellman-Isaacs equation of dynamic programming is discussed, with a view to extending the theory to relativistic wave mechanics [fr
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 Rather than Mandatory EU Company Law
Hertig, G.; McCahery, J.A.
2006-01-01
A significant debate rages within the EU about whether to give firms the choice to opt in or out of corporate law provisions. Both sides agree that more flexibility and adaptability of legal rules to business needs is crucial. Nevertheless, and not surprisingly, many still view EU mandatory
Direct Optimal Control of Duffing Dynamics
Oz, Hayrani; Ramsey, John K.
2002-01-01
The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.
Genetic Algorithm Optimizes Q-LAW Control Parameters
Lee, Seungwon; von Allmen, Paul; Petropoulos, Anastassios; Terrile, Richard
2008-01-01
A document discusses a multi-objective, genetic algorithm designed to optimize Lyapunov feedback control law (Q-law) parameters in order to efficiently find Pareto-optimal solutions for low-thrust trajectories for electronic propulsion systems. These would be propellant-optimal solutions for a given flight time, or flight time optimal solutions for a given propellant requirement. The approximate solutions are used as good initial solutions for high-fidelity optimization tools. When the good initial solutions are used, the high-fidelity optimization tools quickly converge to a locally optimal solution near the initial solution. Q-law control parameters are represented as real-valued genes in the genetic algorithm. The performances of the Q-law control parameters are evaluated in the multi-objective space (flight time vs. propellant mass) and sorted by the non-dominated sorting method that assigns a better fitness value to the solutions that are dominated by a fewer number of other solutions. With the ranking result, the genetic algorithm encourages the solutions with higher fitness values to participate in the reproduction process, improving the solutions in the evolution process. The population of solutions converges to the Pareto front that is permitted within the Q-law control parameter space.
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...
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.
Dynamical laws of superenergy in general relativity
International Nuclear Information System (INIS)
Gomez-Lobo, Alfonso GarcIa-Parrado
2008-01-01
The Bel and Bel-Robinson tensors were introduced nearly 50 years ago in an attempt to generalize to gravitation the energy-momentum tensor of electromagnetism. This generalization was successful from the mathematical point of view because these tensors share mathematical properties which are remarkably similar to those of the energy-momentum tensor of electromagnetism. However, the physical role of these tensors in general relativity has remained obscure and no interpretation has achieved wide acceptance. In principle, they cannot represent energy and the term superenergy has been coined for the hypothetical physical magnitude lying behind them. In this work, we try to shed light on the true physical meaning of superenergy by following the same procedure which enables us to give an interpretation of the electromagnetic energy. This procedure consists in performing an orthogonal splitting of the Bel and Bel-Robinson tensors and analyzing the different parts resulting from the splitting. In the electromagnetic case such splitting gives rise to the electromagnetic energy density, the Poynting vector and the electromagnetic stress tensor, each of them having a precise physical interpretation which is deduced from the dynamical laws of electromagnetism (Poynting theorem). The full orthogonal splitting of the Bel and Bel-Robinson tensors is more complex but, as expected, similarities with electromagnetism are present. Also the covariant divergence of the Bel tensor is analogous to the covariant divergence of the electromagnetic energy-momentum tensor and the orthogonal splitting of the former is found. The ensuing equations are to the superenergy what the Poynting theorem is to electromagnetism. Some consequences of these dynamical laws of superenergy are explored, among them the possibility of defining superenergy radiative states for the gravitational field
Time Optimal Control Laws for Bilinear Systems
Directory of Open Access Journals (Sweden)
Salim Bichiou
2018-01-01
Full Text Available The aim of this paper is to determine the feedforward and state feedback suboptimal time control for a subset of bilinear systems, namely, the control sequence and reaching time. This paper proposes a method that uses Block pulse functions as an orthogonal base. The bilinear system is projected along that base. The mathematical integration is transformed into a product of matrices. An algebraic system of equations is obtained. This system together with specified constraints is treated as an optimization problem. The parameters to determine are the final time, the control sequence, and the states trajectories. The obtained results via the newly proposed method are compared to known analytical solutions.
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.
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.
Emergence of the second law out of reversible dynamics
Willigenburg, van L.G.; Koning, de W.L.
2009-01-01
Abstract If one demystifies entropy the second law of thermodynamics comes out as an emergent property entirely based on the simple dynamic mechanical laws that govern the motion and energies of system parts on a micro-scale. The emergence of the second law is illustrated in this paper through the
Spatio-temporal optimal law enforcement using Stackelberg games
International Nuclear Information System (INIS)
Naja, R.; Mouawad, N.; Ghandour, A.
2017-01-01
Every year, road accidents claim the lives of around 1.2 million worldwide (USDOT-NHTSA,2012). Deploying speed traps helps bounding vehicles speed and reducing collisions. Nevertheless, deterministic speed traps deployment in both spatial and temporal domains, allow drivers to learn and anticipate covered areas. In thispaper, we present a novel framework that provides randomized speed traps deployment schedule. It uses game theory in order to model drivers and law enforcers behavior. In this context, Stackelberg security game is used to derive best strategies to deploy. The game optimal solution maximizes law enforcer utility. This research work aims to optimize the deployment of speed traps on Lebanese highways according to the accidents probability input data. This work complements the near real time accident map provided by the Lebanese National Council for Scientific Research and designs an optimal speed trap map targeting Lebanese highways.(author)
Optimization of injection law for direct injection diesel engine
International Nuclear Information System (INIS)
Feola, M.; Bella, G.; Pelloni, P.; Casoli, P.; Toderi, G.; Cantore, G.
1992-01-01
This paper describes how different timing and shape of the injection law can influence pollutant emission of a direct injection diesel engine. The study was carried out making use of a multizone thermodynamic model as regards the closed valve phase, and a filling-emptying one as regards the open valve phase. After being calibrated by comparison with experimental data, the abovementioned model was used for injection law optimization as regards minimum pollutant concentration (NO x and soot) in the exhaust gases with the smallest engine performance reduction possible
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 reser...... that the optimization solver, the compiler, and high-performance linear algebra software are all important for e_cient dynamic optimization of UV ash processes....
Preinflationary dynamics in loop quantum cosmology: Power-law potentials
Shahalam, M.; Sharma, Manabendra; Wu, Qiang; Wang, Anzhong
2017-12-01
In this paper, we study the preinflationary dynamics for the power-law potential [V (ϕ )∝ϕn] with n consideration and compare our results with the ones obtained previously for different potentials.
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
Violations of conservation laws in viscous liquid dynamics
DEFF Research Database (Denmark)
Dyre, Jeppe
2007-01-01
The laws expressing conservation of momentum and energy apply to any isolated system, but these laws are violated for highly viscous liquids under laboratory conditions because of the unavoidable interactions with the measuring equipment over the long times needed to study the dynamics. Moreover,......, although particle number conservation applies strictly for any liquid, the solidity of viscous liquids implies that even this conservation law is apparently violated in coarse-grained descriptions of density fluctuations.......The laws expressing conservation of momentum and energy apply to any isolated system, but these laws are violated for highly viscous liquids under laboratory conditions because of the unavoidable interactions with the measuring equipment over the long times needed to study the dynamics. Moreover...
Constrained Dynamic Optimality and Binomial Terminal Wealth
DEFF Research Database (Denmark)
Pedersen, J. L.; Peskir, G.
2018-01-01
with interest rate $r \\in {R}$). Letting $P_{t,x}$ denote a probability measure under which $X^u$ takes value $x$ at time $t,$ we study the dynamic version of the nonlinear optimal control problem $\\inf_u\\, Var{t,X_t^u}(X_T^u)$ where the infimum is taken over admissible controls $u$ subject to $X_t^u \\ge e...... a martingale method combined with Lagrange multipliers, we derive the dynamically optimal control $u_*^d$ in closed form and prove that the dynamically optimal terminal wealth $X_T^d$ can only take two values $g$ and $\\beta$. This binomial nature of the dynamically optimal strategy stands in sharp contrast...... with other known portfolio selection strategies encountered in the literature. A direct comparison shows that the dynamically optimal (time-consistent) strategy outperforms the statically optimal (time-inconsistent) strategy in the problem....
Dynamical System Approaches to Combinatorial Optimization
DEFF Research Database (Denmark)
Starke, Jens
2013-01-01
of large times as an asymptotically stable point of the dynamics. The obtained solutions are often not globally optimal but good approximations of it. Dynamical system and neural network approaches are appropriate methods for distributed and parallel processing. Because of the parallelization......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...... thereof can be used as models for many industrial problems like manufacturing planning and optimization of flexible manufacturing systems. This is illustrated for an example in distributed robotic systems....
Spreading dynamics of power-law fluid droplets
International Nuclear Information System (INIS)
Liang Zhanpeng; Peng Xiaofeng; Wang Xiaodong; Lee, D-J; Su Ay
2009-01-01
This paper aims at providing a summary of the theoretical models available for non-Newtonian fluid spreading dynamics. Experimental findings and model predictions for a Newtonian fluid spreading test are briefly reviewed. Then how the complete wetting and partial wetting power-law fluids spread over a solid substrate is examined. The possible extension of Newtonian fluid models to power-law fluids is also discussed.
THE TAQNIN OF INDONESIAN ISLAMIC LAW DYNAMIC
Directory of Open Access Journals (Sweden)
M. Noor Harisudin
2015-06-01
Full Text Available Taqnin with the meaning of legislation on Islamic aspects actually has been a long story in Indonesia. It can be traced in Islamic courts in the archipelago. In the colonial era, the Dutch once accommodated certain aspects of Islamic law, until they decided to limit it. It especially can be seen in the institution of religious court. After the independence, the taqnin was reintroduced. It can be seen from the Piagam Jakarta (Jakarta Charter which included the statement of “Belief in God Almighty by following the sharia for its adherents”. However, this statement was edited to accommodate the aspiration of non-Muslims and the nationalists. In the following periods, legislation of certain aspects of Islam gained momentum in the late period of the New Order after Suharto sought political supports from Muslims. In the reformation era, the democratic atmosphere has opened a wider space for the efforts of taqnin.
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
Dynamic intersectoral models with power-law memory
Tarasova, Valentina V.; Tarasov, Vasily E.
2018-01-01
Intersectoral dynamic models with power-law memory are proposed. The equations of open and closed intersectoral models, in which the memory effects are described by the Caputo derivatives of non-integer orders, are derived. We suggest solutions of these equations, which have the form of linear combinations of the Mittag-Leffler functions and which are characterized by different effective growth rates. Examples of intersectoral dynamics with power-law memory are suggested for two sectoral cases. We formulate two principles of intersectoral dynamics with memory: the principle of changing of technological growth rates and the principle of domination change. It has been shown that in the input-output economic dynamics the effects of fading memory can change the economic growth rate and dominant behavior of economic sectors.
Scaling Laws for Dynamic Aperture due to Chromatic Sextupoles
Scandale, Walter
1997-01-01
Scaling laws for the dynamic aperture due to chromatic sextupoles are investigated. The problem is addressed in a simplified lattice model containing 4 N identical cells and one linear betatron phase shifter to break the overall cell-lattice symmetry. Two families of chromatic sextupoles are used to compensate the natural chromaticity. Analytical formulae for the dynamic apertur as a function of the number of cells and of the cell length are found and confirmed through computer tracking.
Dynamic programming for QFD in PES optimization
Energy Technology Data Exchange (ETDEWEB)
Sorrentino, R. [Mediterranean Univ. of Reggio Calabria, Reggio Calabria (Italy). Dept. of Computer Science and Electrical Technology
2008-07-01
Quality function deployment (QFD) is a method for linking the needs of the customer with design, development, engineering, manufacturing, and service functions. In the electric power industry, QFD is used to help designers concentrate on the most important technical attributes to develop better electrical services. Most optimization approaches used in QFD analysis have been based on integer or linear programming. These approaches perform well in certain circumstances, but there are problems that hinder their practical use. This paper proposed an approach to optimize Power and Energy Systems (PES). A dynamic programming approach was used along with an extended House of Quality to gather information. Dynamic programming was used to allocate the limited resources to the technical attributes. The approach integrated dynamic programming into the electrical service design process. The dynamic programming approach did not require the full relationship curve between technical attributes and customer satisfaction, or the relationship between technical attributes and cost. It only used a group of discrete points containing information about customer satisfaction, technical attributes, and the cost to find the optimal product design. Therefore, it required less time and resources than other approaches. At the end of the optimization process, the value of each technical attribute, the related cost, and the overall customer satisfaction were obtained at the same time. It was concluded that compared with other optimization methods, the dynamic programming method requires less information and the optimal results are more relevant. 21 refs., 2 tabs., 2 figs.
Milgrom's revision of Newton's laws: Dynamical and cosmological consequences
International Nuclear Information System (INIS)
Felten, J.E.; and University of Maryland, College Park)
1984-01-01
Milgrom's recent revision of Newtonian dynamics was introduced to eliminate the inference that large quantities of invisible mass exist in galaxies. I show by simple examples that a Milgrom acceleration, in the form presented so far, implies other far-reaching changes in dynamics. The momentum of an isolated system is not conserved, and the usual theorem for center-of-mass motion of any system does not hold. Naive applications require extreme caution. The model fails to provide a complete description of particle dynamics and should be thought of as a revision of Kepler's laws rather than Newton's
Dynamic optimization and adaptive controller design
Inamdar, S. R.
2010-10-01
In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.
Efficient dynamic optimization of logic programs
Laird, Phil
1992-01-01
A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.
Magnetohydrodynamics and fluid dynamics action principles and conservation laws
Webb, Gary
2018-01-01
This text focuses on conservation laws in magnetohydrodynamics, gasdynamics and hydrodynamics. A grasp of new conservation laws is essential in fusion and space plasmas, as well as in geophysical fluid dynamics; they can be used to test numerical codes, or to reveal new aspects of the underlying physics, e.g., by identifying the time history of the fluid elements as an important key to understanding fluid vorticity or in investigating the stability of steady flows. The ten Galilean Lie point symmetries of the fundamental action discussed in this book give rise to the conservation of energy, momentum, angular momentum and center of mass conservation laws via Noether’s first theorem. The advected invariants are related to fluid relabeling symmetries – so-called diffeomorphisms associated with the Lagrangian map – and are obtained by applying the Euler-Poincare approach to Noether’s second theorem. The book discusses several variants of helicity including kinetic helicity, cross helicity, magnetic helici...
Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions
Miller, Christopher J.
2011-01-01
A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.
Optimal Rules of Negligent Misrepresentation in Insurance Contract Law
DEFF Research Database (Denmark)
Lando, Henrik
2016-01-01
Rules of misrepresentation in insurance contract law differ widely between jurisdictions. When the insured has negligently misrepresented a fact prior to contracting, common law allows the insurer to rescind the contract if the misrepresentation was material, while civil law countries apply more...
Kernel optimization for short-range molecular dynamics
Hu, Changjun; Wang, Xianmeng; Li, Jianjiang; He, Xinfu; Li, Shigang; Feng, Yangde; Yang, Shaofeng; Bai, He
2017-02-01
To optimize short-range force computations in Molecular Dynamics (MD) simulations, multi-threading and SIMD optimizations are presented in this paper. With respect to multi-threading optimization, a Partition-and-Separate-Calculation (PSC) method is designed to avoid write conflicts caused by using Newton's third law. Serial bottlenecks are eliminated with no additional memory usage. The method is implemented by using the OpenMP model. Furthermore, the PSC method is employed on Intel Xeon Phi coprocessors in both native and offload models. We also evaluate the performance of the PSC method under different thread affinities on the MIC architecture. In the SIMD execution, we explain the performance influence in the PSC method, considering the "if-clause" of the cutoff radius check. The experiment results show that our PSC method is relatively more efficient compared to some traditional methods. In double precision, our 256-bit SIMD implementation is about 3 times faster than the scalar version.
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.
Triadic closure dynamics drives scaling laws in social multiplex networks
International Nuclear Information System (INIS)
Klimek, Peter; Thurner, Stefan
2013-01-01
Social networks exhibit scaling laws for several structural characteristics, such as degree distribution, scaling of the attachment kernel and clustering coefficients as a function of node degree. A detailed understanding if and how these scaling laws are inter-related is missing so far, let alone whether they can be understood through a common, dynamical principle. We propose a simple model for stationary network formation and show that the three mentioned scaling relations follow as natural consequences of triadic closure. The validity of the model is tested on multiplex data from a well-studied massive multiplayer online game. We find that the three scaling exponents observed in the multiplex data for the friendship, communication and trading networks can simultaneously be explained by the model. These results suggest that triadic closure could be identified as one of the fundamental dynamical principles in social multiplex network formation. (paper)
Role of controllability in optimizing quantum dynamics
International Nuclear Information System (INIS)
Wu Rebing; Hsieh, Michael A.; Rabitz, Herschel
2011-01-01
This paper reveals an important role that controllability plays in the complexity of optimizing quantum control dynamics. We show that the loss of controllability generally leads to multiple locally suboptimal controls when gate fidelity in a quantum control system is maximized, which does not happen if the system is controllable. Such local suboptimal controls may attract an optimization algorithm into a local trap when a global optimal solution is sought, even if the target gate can be perfectly realized. This conclusion results from an analysis of the critical topology of the corresponding quantum control landscape, which refers to the gate fidelity objective as a functional of the control fields. For uncontrollable systems, due to SU(2) and SU(3) dynamical symmetries, the control landscape corresponding to an implementable target gate is proven to possess multiple locally optimal critical points, and its ruggedness can be further increased if the target gate is not realizable. These results imply that the optimization of quantum dynamics can be seriously impeded when operating with local search algorithms under these conditions, and thus full controllability is demanded.
Dynamic analysis on magnetic fluid interface validated by physical laws
Energy Technology Data Exchange (ETDEWEB)
Mizuta, Yo, E-mail: yomizuta@eng.hokudai.ac.jp
2017-06-01
Numerical analyses of magnetic fluid especially for fast phenomena such as the transition among interface profiles require rigorous as well as efficient method under arbitrary interface profiles and applied magnetic field distributions. Preceded by the magnetic analysis for this purpose, the present research has attempted to investigate interface dynamic phenomena. As an example of these phenomena, this paper shows the wavenumber spectrum of the interface profile and the sum of interface stresses changing in time, since the change of the balance among the interface stresses causing the transition can be observed conveniently. As time advances, wavenumber components increase due to the nonlinear interaction of waves. It is further argued that such analyses should be validated by the law of conservation of energy, the relation between the interface energy density and the interface stress, and the magnetic laws. - Highlights: • Numerical analysis for dynamic interface phenomena of magnetic fluid is attempted. • This analysis intends fast processes during transition of interface profile. • Wavenumber spectra of interface elevation and sum of stresses are shown. • Under magnetic field close to transition, components increase drastically in time. • Validation rules by physical laws of energy and magnetic field are shown.
Dynamic coordinated control laws in multiple agent models
International Nuclear Information System (INIS)
Morgan, David S.; Schwartz, Ira B.
2005-01-01
We present an active control scheme of a kinetic model of swarming. It has been shown previously that the global control scheme for the model, presented in [Systems Control Lett. 52 (2004) 25], gives rise to spontaneous collective organization of agents into a unified coherent swarm, via steering controls and utilizing long-range attractive and short-range repulsive interactions. We extend these results by presenting control laws whereby a single swarm is broken into independently functioning subswarm clusters. The transition between one coordinated swarm and multiple clustered subswarms is managed simply with a homotopy parameter. Additionally, we present as an alternate formulation, a local control law for the same model, which implements dynamic barrier avoidance behavior, and in which swarm coherence emerges spontaneously
Directory of Open Access Journals (Sweden)
Claudiu Ramon D. Butculescu
2016-12-01
Full Text Available This article is studying the dynamics of the relationship between legal positivism and the two divisions of law, respectively private law and public law. Legal positivism, envisions concepts of human intervention in the creation and application of the law, and so it finds application in both public law and private law. However, in private law, there are several principles which can be deduced from the doctrine of natural law, such as substitution, reversibility and others. To the contrary, in public law, legal positivism is all present, manifesting itself in all its branches. It is not, however, an exclusive presence, because there is a balance between natural law and legal positivism in each of the divisions of law. The two orientations of law, namely natural law and legal positivism coexist in each of the divisions and branches of the law, but with a different structure, dynamic or static, depending on specific branches of law. This paper presents in an analytical manner, the static and dynamic manifestations of legal positivism within the framework of the two divisions of law, namely private law and public law.
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.
Optimal reduction of flexible dynamic system
International Nuclear Information System (INIS)
Jankovic, J.
1994-01-01
Dynamic system reduction is basic procedure in various problems of active control synthesis of flexible structures. In this paper is presented direct method for system reduction by explicit extraction of modes included in reduced model form. Criterion for optimal system discrete approximation in synthesis reduced dynamic model is also presented. Subjected method of system decomposition is discussed in relation to the Schur method of solving matrix algebraic Riccati equation as condition for system reduction. By using exposed method procedure of flexible system reduction in addition with corresponding example is presented. Shown procedure is powerful in problems of active control synthesis of flexible system vibrations
Molecular Dynamics Simulations for Resolving Scaling Laws of Polyethylene Melts
Directory of Open Access Journals (Sweden)
Kazuaki Z. Takahashi
2017-01-01
Full Text Available Long-timescale molecular dynamics simulations were performed to estimate the actual physical nature of a united-atom model of polyethylene (PE. Several scaling laws for representative polymer properties are compared to theoretical predictions. Internal structure results indicate a clear departure from theoretical predictions that assume ideal chain statics. Chain motion deviates from predictions that assume ideal motion of short chains. With regard to linear viscoelasticity, the presence or absence of entanglements strongly affects the duration of the theoretical behavior. Overall, the results indicate that Gaussian statics and dynamics are not necessarily established for real atomistic models of PE. Moreover, the actual physical nature should be carefully considered when using atomistic models for applications that expect typical polymer behaviors.
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.
Structural optimization for nonlinear dynamic response
DEFF Research Database (Denmark)
Dou, Suguang; Strachan, B. Scott; Shaw, Steven W.
2015-01-01
by a single vibrating mode, or by a pair of internally resonant modes. The approach combines techniques from nonlinear dynamics, computational mechanics and optimization, and it allows one to relate the geometric and material properties of structural elements to terms in the normal form for a given resonance......Much is known about the nonlinear resonant response of mechanical systems, but methods for the systematic design of structures that optimize aspects of these responses have received little attention. Progress in this area is particularly important in the area of micro-systems, where nonlinear...... 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...
Digitally Controlled Converter with Dynamic Change of Control Law and Power Throughput
DEFF Research Database (Denmark)
Nesgaard, Carsten; Andersen, Michael Andreas E.; Nielsen, Nils
2003-01-01
the substitution of analog controllers with their digital counterparts are considered. The outline of the paper is divided into two segments – the first being an experimental analysis of the timing behavior by means of code optimization – the second being an examination of the dynamics of incorporating two control......With the continuous development of faster and cheaper microprocessors the field of applications for digital control is constantly expanding. Based on this trend the paper at hand describes the analysis and implementation of multiple control laws within the same controller. Also, implemented within...
Haseli, Y.
2013-01-01
The idea is to find out whether 2nd law efficiency optimization may be a suitable trade-off between maximum work output and maximum 1st law efficiency designs for a regenerative gas turbine engine operating on the basis of an open Brayton cycle. The primary emphasis is placed on analyzing the ideal
VMAT optimization with dynamic collimator rotation.
Lyu, Qihui; O'Connor, Daniel; Ruan, Dan; Yu, Victoria; Nguyen, Dan; Sheng, Ke
2018-04-16
Although collimator rotation is an optimization variable that can be exploited for dosimetric advantages, existing Volumetric Modulated Arc Therapy (VMAT) optimization uses a fixed collimator angle in each arc and only rotates the collimator between arcs. In this study, we develop a novel integrated optimization method for VMAT, accounting for dynamic collimator angles during the arc motion. Direct Aperture Optimization (DAO) for Dynamic Collimator in VMAT (DC-VMAT) was achieved by adding to the existing dose fidelity objective an anisotropic total variation term for regulating the fluence smoothness, a binary variable for forming simple apertures, and a group sparsity term for controlling collimator rotation. The optimal collimator angle for each beam angle was selected using the Dijkstra's algorithm, where the node costs depend on the estimated fluence map at the current iteration and the edge costs account for the mechanical constraints of multi-leaf collimator (MLC). An alternating optimization strategy was implemented to solve the DAO and collimator angle selection (CAS). Feasibility of DC-VMAT using one full-arc with dynamic collimator rotation was tested on a phantom with two small spherical targets, a brain, a lung and a prostate cancer patient. The plan was compared against a static collimator VMAT (SC-VMAT) plan using three full arcs with 60 degrees of collimator angle separation in patient studies. With the same target coverage, DC-VMAT achieved 20.3% reduction of R50 in the phantom study, and reduced the average max and mean OAR dose by 4.49% and 2.53% of the prescription dose in patient studies, as compared with SC-VMAT. The collimator rotation co-ordinated with the gantry rotation in DC-VMAT plans for deliverability. There were 13 beam angles in the single-arc DC-VMAT plan in patient studies that requires slower gantry rotation to accommodate multiple collimator angles. The novel DC-VMAT approach utilizes the dynamic collimator rotation during arc
Optimal Rules of Negligent Misrepresentation in Insurance Law
DEFF Research Database (Denmark)
Lando, Henrik
This article analyzes rules for negligent misrepresentation in insurance contract law. Before contract signature, the applicant can be asked by the insurer to fill in a questionnaire concerning the risk, and may then omit or make untrue statements about facts. Such misrepresentation is considered...... negligent by the court when it is unclear the misrepresentation was due to a mistake or intentional. Rules of negligent misrepresentation differ significantly across jurisdictions. For example, the rule of common law allows the insurer to rescind the contract, whereas the German rule does not allow...... of these rules through an analysis of the degree to which the insured should be allowed to lower coverage in case of negligent misrepresentation. On the one hand, a strict rule renders it easier for an insurer to separate different types of risk without having to use other costly means of separation...
Milgrom's revision of cosmic dynamics: Amending Newton's laws or Keplers
International Nuclear Information System (INIS)
Felten, J.E.
1983-12-01
Milgrom's recent revision of Newtonian dynamics was introduced to eliminate the inference that large quantities of invisible mass exist in galaxies. Simple examples show that a Milgrom acceleration, in the form presented so far, imply other far-reaching changes in dynamics. The momentum of an isolated system is not conserved, and the usual theorem for center-of-mass motion of any system does not hold. Naive applications require extreme caution. The model fails to provide a complete description of particle dynamics and should be thought of as a revision of Kepler's laws rather than Newton's. The Milgrom acceleration also implies fundamental changes in cosmology. A quasi-Newtonian calculation adapted from Newtonian cosmology suggests that a Milgrom universe will recollapse even if the classical closure parameter theta is less than 1. The solution, however, fails to satisfy the cosmological principle. Reasons for the breakdown of this calculation are examined. A theory of gravitation needed before the behavior of a Milgrom universe can be predicted
Milgrom's revision of Newton's laws - Dynamical and cosmological consequences
Felten, J. E.
1984-01-01
Milgrom's (1983) recent revision of Newtonian dynamics was introduced to eliminate the inference that large quantities of invisible mass exist in galaxies. It is shown by simple examples that a Milgrom acceleration, in the form presented so far, implies other far-reaching changes in dynamics. The momentum of an isolated system is not conserved, and the usual theorem for center-of-mass motion of any system does not hold. Naive applications require extreme caution. The model fails to provide a complete description of particle dynamics and should be thought of as a revision of Kepler's laws rather than Newton's. The Milgrom acceleration also implies fundamental changes in cosmology. A quasi-Newtonian calculation adapted from Newtonian cosmology suggests that a 'Milgrom universe' will recollapse even if the classical closure parameter Omega is much less than unity. The solution, however, fails to satisfy the cosmological principle. Reasons for the breakdown of this calculation are examined. A new theory of gravitation will be needed before the behavior of a Milgrom universe can be predicted.
Milgrom's revision of cosmic dynamics: Amending Newton's laws or Keplers?
Felten, J. E.
1983-01-01
Milgrom's recent revision of Newtonian dynamics was introduced to eliminate the inference that large quantities of invisible mass exist in galaxies. Simple examples show that a Milgrom acceleration, in the form presented so far, imply other far-reaching changes in dynamics. The momentum of an isolated system is not conserved, and the usual theorem for center-of-mass motion of any system does not hold. Naive applications require extreme caution. The model fails to provide a complete description of particle dynamics and should be thought of as a revision of Kepler's laws rather than Newton's. The Milgrom acceleration also implies fundamental changes in cosmology. A quasi-Newtonian calculation adapted from Newtonian cosmology suggests that a Milgrom universe will recollapse even if the classical closure parameter theta is less than 1. The solution, however, fails to satisfy the cosmological principle. Reasons for the breakdown of this calculation are examined. A theory of gravitation needed before the behavior of a Milgrom universe can be predicted.
Comparative study of flare control laws. [optimal control of b-737 aircraft approach and landing
Nadkarni, A. A.; Breedlove, W. J., Jr.
1979-01-01
A digital 3-D automatic control law was developed to achieve an optimal transition of a B-737 aircraft between various initial glid slope conditions and the desired final touchdown condition. A discrete, time-invariant, optimal, closed-loop control law presented for a linear regulator problem, was extended to include a system being acted upon by a constant disturbance. Two forms of control laws were derived to solve this problem. One method utilized the feedback of integral states defined appropriately and augmented with the original system equations. The second method formulated the problem as a control variable constraint, and the control variables were augmented with the original system. The control variable constraint control law yielded a better performance compared to feedback control law for the integral states chosen.
A Nonlinear Fuel Optimal Reaction Jet Control Law
National Research Council Canada - National Science Library
Breitfeller, Eric
2002-01-01
We derive a nonlinear fuel optimal attitude control system (ACS) that drives the final state to the desired state according to a cost function that weights the final state angular error relative to the angular rate error...
Optimization of motion control laws for tether crawler or elevator systems
Swenson, Frank R.; Von Tiesenhausen, Georg
1988-01-01
Based on the proposal of a motion control law by Lorenzini (1987), a method is developed for optimizing motion control laws for tether crawler or elevator systems in terms of the performance measures of travel time, the smoothness of acceleration and deceleration, and the maximum values of velocity and acceleration. The Lorenzini motion control law, based on powers of the hyperbolic tangent function, is modified by the addition of a constant-velocity section, and this modified function is then optimized by parameter selections to minimize the peak acceleration value for a selected travel time or to minimize travel time for the selected peak values of velocity and acceleration. It is shown that the addition of a constant-velocity segment permits further optimization of the motion control law performance.
Dynamical scaling law in the development of drift wave turbulence
International Nuclear Information System (INIS)
Watanabe, T.; Fujisaka, H.; Iwayama, T.
1997-01-01
The Charney-Hasegawa-Mima equation, with random forcing at the narrow band wave-number region, which is set to be slightly larger than the characteristic wave number λ, evaluating the inverse ion Larmor radius in plasma, is numerically studied. It is shown that the Fourier spectrum of the potential vorticity fluctuation in the development of turbulence with an initial condition of quiescent state obeys a dynamic scaling law for k 1/2 ε 5/4 t 7/4 F(k/bar k(t))[bar k(t)∼λ 3/4 ε -1/8 t -3/8 ] with a scaling function F(x), which turns out to be in good agreement with numerical experiments. copyright 1997 The American Physical Society
Cosmological Ohm's law and dynamics of non-minimal electromagnetism
International Nuclear Information System (INIS)
Hollenstein, Lukas; Jain, Rajeev Kumar; Urban, Federico R.
2013-01-01
The origin of large-scale magnetic fields in cosmic structures and the intergalactic medium is still poorly understood. We explore the effects of non-minimal couplings of electromagnetism on the cosmological evolution of currents and magnetic fields. In this context, we revisit the mildly non-linear plasma dynamics around recombination that are known to generate weak magnetic fields. We use the covariant approach to obtain a fully general and non-linear evolution equation for the plasma currents and derive a generalised Ohm law valid on large scales as well as in the presence of non-minimal couplings to cosmological (pseudo-)scalar fields. Due to the sizeable conductivity of the plasma and the stringent observational bounds on such couplings, we conclude that modifications of the standard (adiabatic) evolution of magnetic fields are severely limited in these scenarios. Even at scales well beyond a Mpc, any departure from flux freezing behaviour is inhibited
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
Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.
Mazandarani, Mehran; Pariz, Naser
2018-05-01
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.
Optimal Dynamics of Intermittent Water Supply
Lieb, Anna; Wilkening, Jon; Rycroft, Chris
2014-11-01
In many urban areas of the developing world, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability.
Optimal growth entails risky localization in population dynamics
Gueudré, Thomas; Martin, David G.
2018-03-01
Essential to each other, growth and exploration are jointly observed in alive and inanimate entities, such as animals, cells or goods. But how the environment's structural and temporal properties weights in this balance remains elusive. We analyze a model of stochastic growth with time correlations and diffusive dynamics that sheds light on the way populations grow and spread over general networks. This model suggests natural explanations of empirical facts in econo-physics or ecology, such as the risk-return trade-off and the Zipf law. We conclude that optimal growth leads to a localized population distribution, but such risky position can be mitigated through the space geometry. These results have broad applicability and are subsequently illustrated over an empirical study of financial data.
Dynamic optimization of combined harvesting of a two-species fishery
International Nuclear Information System (INIS)
Chaudhuri, K.
1986-06-01
In the present paper, the author considers the problem of dynamic optimization of the exploitation policy connected with the combined harvesting of two competing fish species, each of which obeys the logistic growth law. The singular extremal trajectory in the phase plane is derived by taking the harvesting effort as a dynamic variable. Biological or bioeconomic interpretations of the constraints required for this singular extremal are also given. (author)
Evaluation of 'period-generated' control laws for the time-optimal control of reactor power
International Nuclear Information System (INIS)
Bernard, J.A.
1988-01-01
Time-Optimal control of neutronic power has recently been achieved by developing control laws that determine the actuator mechanism velocity necessary to produce a specified reactor period. These laws are designated as the 'MIT-SNL Period-Generated Minimum Time Control Laws'. Relative to time-optimal response, they function by altering the rate of change of reactivity so that the instantaneous period is stepped from infinity to its minimum allowed value, held at that value until the desired power level is attained, and then stepped back to infinity. The results of a systematic evaluation of these laws are presented. The behavior of each term in the control laws is shown and the capability of these laws to control properly the reactor power is demonstrated. Factors affecting the implementation of these laws, such as the prompt neutron lifetime and the differential reactivity worth of the actuators, are discussed. Finally, the results of an experimental study in which these laws were used to adjust the power of the 5 MWt MIT Research Reactor are shown. The information presented should be of interest to those designing high performance control systems for test, spacecraft, or, in certain instances, commercial reactors
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.
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...... than a buy-and-hold investment in various major stock market indices. This is after accounting for transaction costs, with a one-day delay in the implementation of allocation changes, and with zero-interest cash as the only alternative to the stock indices. Imposing a trading penalty that reduces...
Dynamic bounds for power and efficiency of non-ideal energy converters under nonlinear transfer laws
International Nuclear Information System (INIS)
Sieniutycz, Stanislaw
2009-01-01
We present a thermodynamic approach to simulation and modeling of nonlinear energy converters, in particular radiation engines. Novel results are obtained especially for dynamical engines when the temperature of the propelling medium decreases in time due to a continual decrease of the medium's internal energy caused by the power production. Basic thermodynamic principles determine the converter's efficiency and work limits in terms of the entropy production. The real work is a cumulative effect obtained in a system of a resource fluid, a sequence of engines, and an infinite bath. Nonlinear modeling involves dynamic optimization in which the classical expression for efficiency at maximum power is generalized to endoirreversible machines and nonlinear transfer laws. The primary result is a finite-rate generalization of the classical, reversible work potential (exergy). The generalized work function depends on thermal coordinates and a dissipation index, h, i.e. a Hamiltonian of the minimum entropy production problem. This generalized work function implies stronger bounds on work delivered or supplied than the reversible work potential. The role of the nonlinear analyses and dynamic optimization is shown especially for radiation engines. As an example of the kinetic work limit, generalized exergy of radiation fluid is estimated in terms of finite rates, quantified by the Hamiltonian h
Logistics of radioactive materials: optimization of laws and regulations
International Nuclear Information System (INIS)
Akakiev, B.V.; Makarevich, I.M.; Nesterov, V.P.
2009-01-01
The article considers the problems of the Russian authorization system in the field of radioactive materials (RM) logistics which does not meet the needs of their application in medicine, science and industry. To correct the situation, first of all, it is necessary to revise the licensing system. For optimization of licensing in the field of RM transportation, a radical revision is needed for the Regulations of transportation of dangerous cargoes by automobiles, sanitary regulations, the GOST Dangerous Cargoes, numerous federal codes and norms issued by Rostekhnadzor in recent years. It is also necessary to review and coordinate various sanitary regulations for radiation safety, develop the Agreement on transit transportation of RM between the countries of the CIS [ru
The Wigner semi-circle law in quantum electro dynamics
International Nuclear Information System (INIS)
Accardi, L.; Nagoya Univ.; Lu, Y.G.; Nagoya Univ.
1996-01-01
In the present paper, the basic ideas of the stochastic limit of quantum theory are applied to quantum electro-dynamics. This naturally leads to the study of a new type of quantum stochastic calculus on a Hilbert module. Our main result is that in the weak coupling limit of a system composed of a free particle (electron, atom,..) interacting, via the minimal coupling, with the quantum electromagnetic field, a new type of quantum noise arises, living on a Hilbert module rather than a Hilbert space. Moreover we prove that the vacuum distribution of the limiting field operator is not Gaussian, as usual, but a nonlinear deformation of the Wigner semi-circle law. A third new object arising from the present theory, is the so-called interacting Fock space. A kind of Fock space in which the n quanta, in the n-particle space, are not independent, but interact. The origin of all these new features is that we do not introduce the dipole approximation, but we keep the exponential response term, coupling the electron to the quantum electromagnetic field. This produces a nonlinear interaction among all the modes of the limit master field (quantum noise) whose explicit expression, that we find, can be considered as a nonlinear generalization of the Fermi golden rule. (orig.)
Unimodular Einstein-Cartan gravity: Dynamics and conservation laws
Bonder, Yuri; Corral, Cristóbal
2018-04-01
Unimodular gravity is an interesting approach to address the cosmological constant problem, since the vacuum energy density of quantum fields does not gravitate in this framework, and the cosmological constant appears as an integration constant. These features arise as a consequence of considering a constrained volume element 4-form that breaks the diffeomorphisms invariance down to volume preserving diffeomorphisms. In this work, the first-order formulation of unimodular gravity is presented by considering the spin density of matter fields as a source of spacetime torsion. Even though the most general matter Lagrangian allowed by the symmetries is considered, dynamical restrictions arise on their functional dependence. The field equations are obtained and the conservation laws associated with the symmetries are derived. It is found that, analogous to torsion-free unimodular gravity, the field equation for the vierbein is traceless; nevertheless, torsion is algebraically related to the spin density as in standard Einstein-Cartan theory. The particular example of massless Dirac spinors is studied, and comparisons with standard Einstein-Cartan theory are shown.
Topological dynamics of gyroscopic and Floquet lattices from Newton's laws
Lee, Ching Hua; Li, Guangjie; Jin, Guliuxin; Liu, Yuhan; Zhang, Xiao
2018-02-01
Despite intense interest in realizing topological phases across a variety of electronic, photonic, and mechanical platforms, the detailed microscopic origin of topological behavior often remains elusive. To bridge this conceptual gap, we show how hallmarks of topological modes—boundary localization and chirality—emerge from Newton's laws in mechanical topological systems. We first construct a gyroscopic lattice with analytically solvable edge modes, and show how the Lorentz and spring restoring forces conspire to support very robust "dangling bond" boundary modes. The chirality and locality of these modes intuitively emerges from microscopic balancing of restoring forces and cyclotron tendencies. Next, we introduce the highlight of this work, an experimentally realistic mechanical nonequilibrium (Floquet) Chern lattice driven by ac electromagnets. Through appropriate synchronization of the ac driving protocol, the Floquet lattice is "pushed around" by a rotating potential analogous to an object washed ashore by water waves. Besides hosting "dangling bond" chiral modes analogous to the gyroscopic boundary modes, our Floquet Chern lattice also supports peculiar half-period chiral modes with no static analog, i.e., analogs of anomalous Floquet Chern insulators edge modes. With key parameters controlled electronically, our setup has the advantage of being dynamically tunable for applications involving arbitrary Floquet modulations. The physical intuition gleaned from our two prototypical topological systems is applicable not just to arbitrarily complicated mechanical systems, but also photonic and electrical topological setups.
Optimization of multi-response dynamic systems integrating multiple ...
African Journals Online (AJOL)
regression and Taguchi's dynamic signal-to-noise ratio concept ..... algorithm for dynamic multi-response optimization based on goal programming approach. .... problem-solving confirmation, if no grave infringement of model suppositions is ...
NHEG mechanics: laws of near horizon extremal geometry (thermo)dynamics
International Nuclear Information System (INIS)
Hajian, K.; Seraj, A.; Sheikh-Jabbari, M.M.
2014-01-01
Near Horizon Extremal Geometries (NHEG) are solutions to gravity theories with SL(2,ℝ)×U(1) N (for some N) symmetry, are smooth geometries and have no event horizon, unlike black holes. Following the ideas by R. M. Wald, we derive laws of NHEG dynamics, the analogs of laws of black hole dynamics for the NHEG. Despite the absence of horizon in the NHEG, one may associate an entropy to the NHEG, as a Noether-Wald conserved charge. We work out “entropy” and “entropy perturbation” laws, which are respectively universal relations between conserved Noether charges corresponding to the NHEG and a system probing the NHEG. Our entropy law is closely related to Sen’s entropy function. We also discuss whether the laws of NHEG dynamics can be obtained from the laws of black hole thermodynamics in the extremal limit
Directory of Open Access Journals (Sweden)
Julio Michael Stern
2014-03-01
Full Text Available This article presents a simple derivation of optimization models for reaction networks leading to a generalized form of the mass-action law, and compares the formal structure of Minimum Information Divergence, Quadratic Programming and Kirchhoff type network models. These optimization models are used in related articles to develop and illustrate the operation of ontology alignment algorithms and to discuss closely connected issues concerning the epistemological and statistical significance of sharp or precise hypotheses in empirical science.
Shimansky, Yury P; Kang, Tao; He, Jiping
2004-02-01
A computational model of a learning system (LS) is described that acquires knowledge and skill necessary for optimal control of a multisegmental limb dynamics (controlled object or CO), starting from "knowing" only the dimensionality of the object's state space. It is based on an optimal control problem setup different from that of reinforcement learning. The LS solves the optimal control problem online while practicing the manipulation of CO. The system's functional architecture comprises several adaptive components, each of which incorporates a number of mapping functions approximated based on artificial neural nets. Besides the internal model of the CO's dynamics and adaptive controller that computes the control law, the LS includes a new type of internal model, the minimal cost (IM(mc)) of moving the controlled object between a pair of states. That internal model appears critical for the LS's capacity to develop an optimal movement trajectory. The IM(mc) interacts with the adaptive controller in a cooperative manner. The controller provides an initial approximation of an optimal control action, which is further optimized in real time based on the IM(mc). The IM(mc) in turn provides information for updating the controller. The LS's performance was tested on the task of center-out reaching to eight randomly selected targets with a 2DOF limb model. The LS reached an optimal level of performance in a few tens of trials. It also quickly adapted to movement perturbations produced by two different types of external force field. The results suggest that the proposed design of a self-optimized control system can serve as a basis for the modeling of motor learning that includes the formation and adaptive modification of the plan of a goal-directed movement.
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.
Optimization Based Clearance of Flight Control Laws A Civil Aircraft Application
Hansson, Anders; Puyou, Guilhem
2012-01-01
This book summarizes the main achievements of the EC funded 6th Framework Program project COFCLUO – Clearance of Flight Control Laws Using Optimization. This project successfully contributed to the achievement of a top-level objective to meet society’s needs for a more efficient, safer and environmentally friendly air transport by providing new techniques and tools for the clearance of flight control laws. This is an important part of the certification and qualification process of an aircraft – a costly and time-consuming process for the aeronautical industry. The overall objective of the COFCLUO project was to develop and apply optimization techniques to the clearance of flight control laws in order to improve efficiency and reliability. In the book, the new techniques are explained and benchmarked against traditional techniques currently used by the industry. The new techniques build on mathematical criteria derived from the certification and qualification requirements together with suitable models...
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
Prevention of Crime and the Optimal Standard of Proof in Criminal Law
DEFF Research Database (Denmark)
Lando, Henrik
2003-01-01
The standard of proof in criminal law a®ects retributive justice throughthe number of wrong convictions and wrong acquittals. It also a®ects thelevel of crime, since a higher standard of proof implies less deterrence andless incapacitation. This article derives an expression for the optimal...
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.
Model-based dynamic control and optimization of gas networks
Energy Technology Data Exchange (ETDEWEB)
Hofsten, Kai
2001-07-01
by a structured sequential quadratic programming algorithm of Newton type. Each open loop problem is specified using a nonlinear prediction model. For each iteration of the quadratic programming procedure, a linear time variant prediction model is formulated. The suggested controller also handles time varying source capacity. Potential problems such as infeasibility and the security of the supply when facing a change in the status of the infrastructure of the transmission system under a transient customer load are treated. Comments on the infeasibility due to errors such as load forecast error, model error and state estimation error are also discussed. A simplified nonlinear model called the creep flow model is used to describe the fluid dynamics inside a natural gas transmission line. Different assumptions and reformulations of this model yield the different control, simulation and optimization models used in this thesis. The control of a single gas transmission line is investigated using linear model predictive control based on instant linearization of the nonlinear model. Model predictive control using a bi quadratic optimization model formulated from the creep flow model is also investigated. A distributed parameter control model of the gas dynamics for a transmission line is formulated. An analytic solution of this model is given with both Neuman boundary conditions and distributed supplies and loads. A transfer function model is developed expressing the dynamics between the defined output and the control and disturbance inputs of the transmission line. Based on the qualitative behaviour observed from the step responses of the solutions of the distributed parameter model formulated in this thesis, simplified transfer function models were developed. These control models expresses the dynamics of a natural gas transmission line with Neuman boundary control and load. Further, these models were used to design a control law, which is a combination of a Smith
Optimal dynamic economic dispatch of generation: A review
International Nuclear Information System (INIS)
Xia, X.; Elaiw, A.M.
2010-01-01
This paper presents a review of the research of the optimal power dynamic dispatch problem. The dynamic dispatch problem differs from the static economic dispatch problem by incorporating generator ramp rate constraints. There are two different formulations of this problem in the literature. The first formulation is the optimal control dynamic dispatch (OCDD) where the power system generation has been modeled as a control system and optimization is done in the optimal control setting with respect to the ramp rates as input variables. The second one is a later formulation known as the dynamic economic dispatch (DED) where optimization is done with respect to the dispatchable powers of the committed generation units. In this paper we first outline the two formulations, then present an overview on the mathematical optimization methods, Artificial Intelligence (AI) techniques and hybrid methods used to solve the problem incorporating extended and complex objective functions or constraints. The DED problem in deregulated electricity markets is also reported. (author)
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.
Directory of Open Access Journals (Sweden)
Oldiges Marco
2009-01-01
Full Text Available Abstract Background To understand the dynamic behavior of cellular systems, mathematical modeling is often necessary and comprises three steps: (1 experimental measurement of participating molecules, (2 assignment of rate laws to each reaction, and (3 parameter calibration with respect to the measurements. In each of these steps the modeler is confronted with a plethora of alternative approaches, e. g., the selection of approximative rate laws in step two as specific equations are often unknown, or the choice of an estimation procedure with its specific settings in step three. This overall process with its numerous choices and the mutual influence between them makes it hard to single out the best modeling approach for a given problem. Results We investigate the modeling process using multiple kinetic equations together with various parameter optimization methods for a well-characterized example network, the biosynthesis of valine and leucine in C. glutamicum. For this purpose, we derive seven dynamic models based on generalized mass action, Michaelis-Menten and convenience kinetics as well as the stochastic Langevin equation. In addition, we introduce two modeling approaches for feedback inhibition to the mass action kinetics. The parameters of each model are estimated using eight optimization strategies. To determine the most promising modeling approaches together with the best optimization algorithms, we carry out a two-step benchmark: (1 coarse-grained comparison of the algorithms on all models and (2 fine-grained tuning of the best optimization algorithms and models. To analyze the space of the best parameters found for each model, we apply clustering, variance, and correlation analysis. Conclusion A mixed model based on the convenience rate law and the Michaelis-Menten equation, in which all reactions are assumed to be reversible, is the most suitable deterministic modeling approach followed by a reversible generalized mass action kinetics
Optimal Stochastic Control Problem for General Linear Dynamical Systems in Neuroscience
Directory of Open Access Journals (Sweden)
Yan Chen
2017-01-01
Full Text Available This paper considers a d-dimensional stochastic optimization problem in neuroscience. Suppose the arm’s movement trajectory is modeled by high-order linear stochastic differential dynamic system in d-dimensional space, the optimal trajectory, velocity, and variance are explicitly obtained by using stochastic control method, which allows us to analytically establish exact relationships between various quantities. Moreover, the optimal trajectory is almost a straight line for a reaching movement; the optimal velocity bell-shaped and the optimal variance are consistent with the experimental Fitts law; that is, the longer the time of a reaching movement, the higher the accuracy of arriving at the target position, and the results can be directly applied to designing a reaching movement performed by a robotic arm in a more general environment.
Complex fluid network optimization and control integrative design based on nonlinear dynamic model
International Nuclear Information System (INIS)
Sui, Jinxue; Yang, Li; Hu, Yunan
2016-01-01
In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.
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.
Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu
2016-01-01
An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.
Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai
2013-09-01
In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.
Of paradox and plausibility: the dynamic of change in medical law.
Harrington, John
2014-01-01
This article develops a model of change in medical law. Drawing on systems theory, it argues that medical law participates in a dynamic of 'deparadoxification' and 'reparadoxification' whereby the underlying contingency of the law is variously concealed through plausible argumentation, or revealed by critical challenge. Medical law is, thus, thoroughly rhetorical. An examination of the development of the law on abortion and on the sterilization of incompetent adults shows that plausibility is achieved through the deployment of substantive common sense and formal stylistic devices. It is undermined where these elements are shown to be arbitrary and constructed. In conclusion, it is argued that the politics of medical law are constituted by this antagonistic process of establishing and challenging provisionally stable normative regimes. © The Author [2014]. Published by Oxford University Press; all rights reserved. For Permissions, please email: journals.permissions@oup.com.
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
Dynamic programming approach to optimization of approximate decision rules
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2013-01-01
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
Dynamic Programming Approach for Exact Decision Rule Optimization
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
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
Optimized controllers for enhancing dynamic performance of PV interface system
Directory of Open Access Journals (Sweden)
Mahmoud A. Attia
2018-05-01
Full Text Available The dynamic performance of PV interface system can be improved by optimizing the gains of the Proportional–Integral (PI controller. In this work, gravitational search algorithm and harmony search algorithm are utilized to optimal tuning of PI controller gains. Performance comparison between the PV system with optimized PI gains utilizing different techniques are carried out. Finally, the dynamic behavior of the system is studied under hypothetical sudden variations in irradiance. The examination of the proposed techniques for optimal tuning of PI gains is conducted using MATLAB/SIMULINK software package. The main contribution of this work is investigating the dynamic performance of PV interfacing system with application of gravitational search algorithm and harmony search algorithm for optimal PI parameters tuning. Keywords: Photovoltaic power systems, Gravitational search algorithm, Harmony search algorithm, Genetic algorithm, Artificial intelligence
Dynamics of a map with a power-law tail
International Nuclear Information System (INIS)
Botella-Soler, V; Ros, J; Oteo, J A
2009-01-01
We analyze a one-dimensional piecewise continuous discrete model proposed originally in studies on population ecology. The map is composed of a linear part and a power-law decreasing piece, and has three parameters. The system presents both regular and chaotic behavior. We study numerically and, in part, analytically different bifurcation structures. Particularly interesting is the description of the abrupt order-to-chaos transition mediated by an attractor made of an infinite number of limit cycles with only a finite number of different periods. It is shown that the power-law piece in the map is at the origin of this type of bifurcation. The system exhibits interior crises and crisis-induced intermittency.
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.
Su, Weixing; Chen, Hanning; Liu, Fang; Lin, Na; Jing, Shikai; Liang, Xiaodan; Liu, Wei
2017-03-01
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.
DYNAMIC OPTIMAL BUDGET ALLOCATION FOR INTEGRATED MARKETING CONSIDERING PERSISTENCE
SHIZHONG AI; RONG DU; QIYING HU
2010-01-01
Aiming at forming dynamic optimal integrated marketing policies, we build a budget allocation model considering both current effects and sustained ones. The model includes multiple time periods and multiple marketing tools which interact through a common resource pool as well as through delayed cross influences on each other's sales, reflecting the nature of "integrated marketing" and its dynamics. In our study, marginal analysis is used to illuminate the structure of optimal policy. We deriv...
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.
Stochastic dynamic programming model for optimal resource ...
Indian Academy of Sciences (India)
M Bhuvaneswari
2018-04-11
Apr 11, 2018 ... handover in VANET; because of high dynamics in net- work topology, collaboration ... containers, doctors, nurses, cash and stocks. Similarly, ... GTBA does not take the resource types and availability into consideration.
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
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.
Airborne Network Optimization with Dynamic Network Update
2015-03-26
source si and a target ti . For each commodity (si, ki) the commodity specifies a non- negative demand di [5]. The objective of the multi-commodity...queue predictions, and network con- gestion [15]. The implementation of the DRQC uses the Kalman filter to predict the state of the network and optimize
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
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 ...
Practical synchronization on complex dynamical networks via optimal pinning control
Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu
2015-07-01
We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.
Asymptotic scaling laws for precision of parameter estimates in dynamical systems
International Nuclear Information System (INIS)
Horbelt, W.; Timmer, J.
2003-01-01
When parameters are estimated from noisy data, the uncertainty of the estimates in terms of their standard deviation typically scales like the inverse square root of the number of data points. In the case of deterministic dynamical systems with added observation noise, superior scaling laws can be achieved. This is demonstrated numerically for the logistic map, the van der Pol oscillator and the Lorenz system, where exponential scaling laws and power laws have been found, depending on the number of degrees of freedom. For some special cases, analytical expressions are derived
New numerical methods for open-loop and feedback solutions to dynamic optimization problems
Ghosh, Pradipto
is that the resulting control law has an algebraic closed-form structure. The proposed method uses an optimal spatial statistical predictor called universal kriging to construct the surrogate model of a feedback controller, which is capable of quickly predicting an optimal control estimate based on current state (and time) information. With universal kriging, an approximation to the optimal feedback map is computed by conceptualizing a set of state-control samples from pre-computed extremals to be a particular realization of a jointly Gaussian spatial process. Feedback policies are computed for a variety of example dynamic optimization problems in order to evaluate the effectiveness of this methodology. This feedback synthesis approach is found to combine good numerical accuracy with low computational overhead, making it a suitable candidate for real-time applications. Particle swarm and universal kriging are combined for a capstone example, a near optimal, near-admissible, full-state feedback control law is computed and tested for the heat-load-limited atmospheric-turn guidance of an aeroassisted transfer vehicle. The performance of this explicit guidance scheme is found to be very promising; initial errors in atmospheric entry due to simulated thruster misfirings are found to be accurately corrected while closely respecting the algebraic state-inequality constraint.
Minimum entropy production principle from a dynamical fluctuation law
Czech Academy of Sciences Publication Activity Database
Maes, C.; Netočný, Karel
2007-01-01
Roč. 48, č. 5 (2007), 053306/1-053306/12 ISSN 0022-2488 R&D Projects: GA ČR GA202/07/0404 Institutional research plan: CEZ:AV0Z10100520 Keywords : dynamical fluctuations * entropy production Subject RIV: BE - Theoretical Physics Impact factor: 1.137, year: 2007
Ohm's law in the fast lane: general relatiivistic charge dynamics
Meier, D.
2004-01-01
Fully relativistic and causal equations for the flow of charge in curved spacetime are derived. It is believed that this is the first set of equations to be published that correctly describes the flow of charge, as well as the evolution of the electromagnetic field, in highly dynamical relativistic environments on timescales much shorter than the collapse time (GM/c3).
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.
Second Law Analysis of the Optimal Fin by Minimum Entropy Generation
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Based on the entropy generation concept of thermodynamics, this paper established a general theoretical model for the analysis of entropy generation to optimize fms, in which the minimum entropy generation was selected as the object to be studied. The irreversibility due to heat transfer and friction was taken into account so that the minimum entropygeneration number has been analyzed with respect to second law of thermodynamics in the forced cross-flow. The optimum dimensions of cylinder pins were discussed. It's found that the minimum entropy generation number depends on parameters related to the fluid and fin physical parameters. Variations of the minimum entropy generation number with different parameters were analyzed.
Gradient-based optimization in nonlinear structural dynamics
DEFF Research Database (Denmark)
Dou, Suguang
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......, 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......, and optimization of nonlinear structural dynamics. In the modelling, nonlinear finite elements are used. In the analysis, nonlinear frequency response and nonlinear normal modes are calculated based on a harmonic balance method with higher-order harmonics. In the characterization, nonlinear modal coupling...
Fuzzy Constrained Predictive Optimal Control of High Speed Train with Actuator Dynamics
Directory of Open Access Journals (Sweden)
Xi Wang
2016-01-01
Full Text Available We investigate the problem of fuzzy constrained predictive optimal control of high speed train considering the effect of actuator dynamics. The dynamics feature of the high speed train is modeled as a cascade of cars connected by flexible couplers, and the formulation is mathematically transformed into a Takagi-Sugeno (T-S fuzzy model. The goal of this study is to design a state feedback control law at each decision step to enhance safety, comfort, and energy efficiency of high speed train subject to safety constraints on the control input. Based on Lyapunov stability theory, the problem of optimizing an upper bound on the cruise control cost function subject to input constraints is reduced to a convex optimization problem involving linear matrix inequalities (LMIs. Furthermore, we analyze the influences of second-order actuator dynamics on the fuzzy constrained predictive controller, which shows risk of potentially deteriorating the overall system. Employing backstepping method, an actuator compensator is proposed to accommodate for the influence of the actuator dynamics. The experimental results show that with the proposed approach high speed train can track the desired speed, the relative coupler displacement between the neighbouring cars is stable at the equilibrium state, and the influence of actuator dynamics is reduced, which demonstrate the validity and effectiveness of the proposed approaches.
Maxwell Prize Talk: Scaling Laws for the Dynamical Plasma Phenomena
Ryutov, Livermore, Ca 94550, Usa, D. D.
2017-10-01
The scaling and similarity technique is a powerful tool for developing and testing reduced models of complex phenomena, including plasma phenomena. The technique has been successfully used in identifying appropriate simplified models of transport in quasistationary plasmas. In this talk, the similarity and scaling arguments will be applied to highly dynamical systems, in which temporal evolution of the plasma leads to a significant change of plasma dimensions, shapes, densities, and other parameters with respect to initial state. The scaling and similarity techniques for dynamical plasma systems will be presented as a set of case studies of problems from various domains of the plasma physics, beginning with collisonless plasmas, through intermediate collisionalities, to highly collisional plasmas describable by the single-fluid MHD. Basic concepts of the similarity theory will be introduced along the way. Among the results discussed are: self-similarity of Langmuir turbulence driven by a hot electron cloud expanding into a cold background plasma; generation of particle beams in disrupting pinches; interference between collisionless and collisional phenomena in the shock physics; similarity for liner-imploded plasmas; MHD similarities with an emphasis on the effect of small-scale (turbulent) structures on global dynamics. Relations between astrophysical phenomena and scaled laboratory experiments will be discussed.
Measurement configuration optimization for dynamic metrology using Stokes polarimetry
Liu, Jiamin; Zhang, Chuanwei; Zhong, Zhicheng; Gu, Honggang; Chen, Xiuguo; Jiang, Hao; Liu, Shiyuan
2018-05-01
As dynamic loading experiments such as a shock compression test are usually characterized by short duration, unrepeatability and high costs, high temporal resolution and precise accuracy of the measurements is required. Due to high temporal resolution up to a ten-nanosecond-scale, a Stokes polarimeter with six parallel channels has been developed to capture such instantaneous changes in optical properties in this paper. Since the measurement accuracy heavily depends on the configuration of the probing beam incident angle and the polarizer azimuth angle, it is important to select an optimal combination from the numerous options. In this paper, a systematic error propagation-based measurement configuration optimization method corresponding to the Stokes polarimeter was proposed. The maximal Frobenius norm of the combinatorial matrix of the configuration error propagating matrix and the intrinsic error propagating matrix is introduced to assess the measurement accuracy. The optimal configuration for thickness measurement of a SiO2 thin film deposited on a Si substrate has been achieved by minimizing the merit function. Simulation and experimental results show a good agreement between the optimal measurement configuration achieved experimentally using the polarimeter and the theoretical prediction. In particular, the experimental result shows that the relative error in the thickness measurement can be reduced from 6% to 1% by using the optimal polarizer azimuth angle when the incident angle is 45°. Furthermore, the optimal configuration for the dynamic metrology of a nickel foil under quasi-dynamic loading is investigated using the proposed optimization method.
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 o...... approach is illustrated using real-scale systems and comparisons with commercial programming solvers. Finally, generalizations to consider other EDS operation problems are also discussed.......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...... of the EDS by setting the values of the controllable variables at each time period. A suitable definition for the stages of the problem makes it possible to represent the optimal ac power flow of radial EDS as a dynamic programming problem, wherein the 'curse of dimensionality' is a minor concern, since...
Evaluation and improvement of dynamic optimality in electrochemical reactors
International Nuclear Information System (INIS)
Vijayasekaran, B.; Basha, C. Ahmed
2005-01-01
A systematic approach for the dynamic optimization problem statement to improve the dynamic optimality in electrochemical reactors is presented in this paper. The formulation takes an account of the diffusion phenomenon in the electrode/electrolyte interface. To demonstrate the present methodology, the optimal time-varying electrode potential for a coupled chemical-electrochemical reaction scheme, that maximizes the production of the desired product in a batch electrochemical reactor with/without recirculation are determined. The dynamic optimization problem statement, based upon this approach, is a nonlinear differential algebraic system, and its solution provides information about the optimal policy. Optimal control policy at different conditions is evaluated using the best-known Pontryagin's maximum principle. The two-point boundary value problem resulting from the application of the maximum principle is then solved using the control vector iteration technique. These optimal time-varying profiles of electrode potential are then compared to the best uniform operation through the relative improvements of the performance index. The application of the proposed approach to two electrochemical systems, described by ordinary differential equations, shows that the existing electrochemical process control strategy could be improved considerably when the proposed method is incorporated
Emergence of robust growth laws from optimal regulation of ribosome synthesis.
Scott, Matthew; Klumpp, Stefan; Mateescu, Eduard M; Hwa, Terence
2014-08-22
Bacteria must constantly adapt their growth to changes in nutrient availability; yet despite large-scale changes in protein expression associated with sensing, adaptation, and processing different environmental nutrients, simple growth laws connect the ribosome abundance and the growth rate. Here, we investigate the origin of these growth laws by analyzing the features of ribosomal regulation that coordinate proteome-wide expression changes with cell growth in a variety of nutrient conditions in the model organism Escherichia coli. We identify supply-driven feedforward activation of ribosomal protein synthesis as the key regulatory motif maximizing amino acid flux, and autonomously guiding a cell to achieve optimal growth in different environments. The growth laws emerge naturally from the robust regulatory strategy underlying growth rate control, irrespective of the details of the molecular implementation. The study highlights the interplay between phenomenological modeling and molecular mechanisms in uncovering fundamental operating constraints, with implications for endogenous and synthetic design of microorganisms. © 2014 The Authors. Published under the terms of the CC BY 4.0 license.
Directory of Open Access Journals (Sweden)
Zhi-Jun Fu
2017-01-01
Full Text Available In view of the performance requirements (e.g., ride comfort, road holding, and suspension space limitation for vehicle suspension systems, this paper proposes an adaptive optimal control method for quarter-car active suspension system by using the approximate dynamic programming approach (ADP. Online optimal control law is obtained by using a single adaptive critic NN to approximate the solution of the Hamilton-Jacobi-Bellman (HJB equation. Stability of the closed-loop system is proved by Lyapunov theory. Compared with the classic linear quadratic regulator (LQR approach, the proposed ADP-based adaptive optimal control method demonstrates improved performance in the presence of parametric uncertainties (e.g., sprung mass and unknown road displacement. Numerical simulation results of a sedan suspension system are presented to verify the effectiveness of the proposed control strategy.
Are there reliable constitutive laws for dynamic friction?
Woodhouse, Jim; Putelat, Thibaut; McKay, Andrew
2015-09-28
Structural vibration controlled by interfacial friction is widespread, ranging from friction dampers in gas turbines to the motion of violin strings. To predict, control or prevent such vibration, a constitutive description of frictional interactions is inevitably required. A variety of friction models are discussed to assess their scope and validity, in the light of constraints provided by different experimental observations. Three contrasting case studies are used to illustrate how predicted behaviour can be extremely sensitive to the choice of frictional constitutive model, and to explore possible experimental paths to discriminate between and calibrate dynamic friction models over the full parameter range needed for real applications. © 2015 The Author(s).
Directory of Open Access Journals (Sweden)
Xiaoxiao Xu
2012-03-01
Full Text Available The subcritical Organic Rankine Cycle (ORC with 28 working fluids for waste heat recovery is discussed in this paper. The effects of the temperature of the waste heat, the critical temperature of working fluids and the pinch temperature difference in the evaporator on the optimal evaporation temperature (OET of the ORC have been investigated. The second law efficiency of the system is regarded as the objective function and the evaporation temperature is optimized by using the quadratic approximations method. The results show that the OET will appear for the temperature ranges investigated when the critical temperatures of working fluids are lower than the waste heat temperatures by 18 ± 5 K under the pinch temperature difference of 5 K in the evaporator. Additionally, the ORC always exhibits the OET when the pinch temperature difference in the evaporator is raised under the fixed waste heat temperature. The maximum second law efficiency will decrease with the increase of pinch temperature difference in the evaporator.
A dynamic global and local combined particle swarm optimization algorithm
International Nuclear Information System (INIS)
Jiao Bin; Lian Zhigang; Chen Qunxian
2009-01-01
Particle swarm optimization (PSO) algorithm has been developing rapidly and many results have been reported. PSO algorithm has shown some important advantages by providing high speed of convergence in specific problems, but it has a tendency to get stuck in a near optimal solution and one may find it difficult to improve solution accuracy by fine tuning. This paper presents a dynamic global and local combined particle swarm optimization (DGLCPSO) algorithm to improve the performance of original PSO, in which all particles dynamically share the best information of the local particle, global particle and group particles. It is tested with a set of eight benchmark functions with different dimensions and compared with original PSO. Experimental results indicate that the DGLCPSO algorithm improves the search performance on the benchmark functions significantly, and shows the effectiveness of the algorithm to solve optimization problems.
Halyo, N.
1976-01-01
A digital automatic control law to capture a steep glideslope and track the glideslope to a specified altitude is developed for the longitudinal/vertical dynamics of a CTOL aircraft using modern estimation and control techniques. The control law uses a constant gain Kalman filter to process guidance information from the microwave landing system, and acceleration from body mounted accelerometer data. The filter outputs navigation data and wind velocity estimates which are used in controlling the aircraft. Results from a digital simulation of the aircraft dynamics and the control law are presented for various wind conditions.
Optimization of a pump-pipe system by dynamic programming
DEFF Research Database (Denmark)
Vidal, Rene Victor Valqui; Ferreira, Jose S.
1984-01-01
In this paper the problem of minimizing the total cost of a pump-pipe system in series is considered. The route of the pipeline and the number of pumping stations are known. The optimization will then consist in determining the control variables, diameter and thickness of the pipe and the size of...... of the pumps. A general mathematical model is formulated and Dynamic Programming is used to find an optimal solution....
Optimal Dynamic Pricing for Perishable Assets with Nonhomogeneous Demand
Wen Zhao; Yu-Sheng Zheng
2000-01-01
We consider a dynamic pricing model for selling a given stock of a perishable product over a finite time horizon. Customers, whose reservation price distribution changes over time, arrive according to a nonhomogeneous Poisson process. We show that at any given time, the optimal price decreases with inventory. We also identify a sufficient condition under which the optimal price decreases over time for a given inventory level. This sufficient condition requires that the willingness of a custom...
Dynamic optimization of a FCC converter unit: numerical analysis
Directory of Open Access Journals (Sweden)
E. Almeida Nt
2011-03-01
Full Text Available Fluidized-bed Catalytic Cracking (FCC is a process subject to frequent variations in the operating conditions (including feed quality and feed rate. The production objectives usually are the maximization of LPG and gasoline production. This fact makes the FCC converter unit an excellent opportunity for real-time optimization. The present work aims to apply a dynamic optimization in an industrial FCC converter unit, using a mechanistic dynamic model, and to carry out a numerical analysis of the solution procedure. A simultaneous approach was used to discretize the system of differential-algebraic equations and the resulting large-scale NLP problem was solved using the IPOPT solver. This study also does a short comparison between the results obtained by a potential dynamic real-time optimization (DRTO against a possible steady-state real-time optimization (RTO application. The results demonstrate that the application of dynamic real-time optimization of a FCC converter unit can bring significant benefits in production.
Optimal Piecewise-Linear Approximation of the Quadratic Chaotic Dynamics
Directory of Open Access Journals (Sweden)
J. Petrzela
2012-04-01
Full Text Available This paper shows the influence of piecewise-linear approximation on the global dynamics associated with autonomous third-order dynamical systems with the quadratic vector fields. The novel method for optimal nonlinear function approximation preserving the system behavior is proposed and experimentally verified. This approach is based on the calculation of the state attractor metric dimension inside a stochastic optimization routine. The approximated systems are compared to the original by means of the numerical integration. Real electronic circuits representing individual dynamical systems are derived using classical as well as integrator-based synthesis and verified by time-domain analysis in Orcad Pspice simulator. The universality of the proposed method is briefly discussed, especially from the viewpoint of the higher-order dynamical systems. Future topics and perspectives are also provided
Interactions of Delta Shock Waves for Zero-Pressure Gas Dynamics with Energy Conservation Law
Wei Cai; Yanyan Zhang
2016-01-01
We study the interactions of delta shock waves and vacuum states for the system of conservation laws of mass, momentum, and energy in zero-pressure gas dynamics. The Riemann problems with initial data of three piecewise constant states are solved case by case, and four different configurations of Riemann solutions are constructed. Furthermore, the numerical simulations completely coinciding with theoretical analysis are shown.
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.
Optimal interdependence enhances the dynamical robustness of complex systems
Singh, Rishu Kumar; Sinha, Sitabhra
2017-08-01
Although interdependent systems have usually been associated with increased fragility, we show that strengthening the interdependence between dynamical processes on different networks can make them more likely to survive over long times. By coupling the dynamics of networks that in isolation exhibit catastrophic collapse with extinction of nodal activity, we demonstrate system-wide persistence of activity for an optimal range of interdependence between the networks. This is related to the appearance of attractors of the global dynamics comprising disjoint sets ("islands") of stable activity.
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.
Solving the dynamic rupture problem with different numerical approaches and constitutive laws
Bizzarri, A.; Cocco, M.; Andrews, D.J.; Boschi, Enzo
2001-01-01
We study the dynamic initiation, propagation and arrest of a 2-D in-plane shear rupture by solving the elastodynamic equation by using both a boundary integral equation method and a finite difference approach. For both methods we adopt different constitutive laws: a slip-weakening (SW) law, with constant weakening rate, and rate- and state-dependent friction laws (Dieterich-Ruina). Our numerical procedures allow the use of heterogeneous distributions of constitutive parameters along the fault for both formulations. We first compare the two solution methods with an SW law, emphasizing the required stability conditions to achieve a good resolution of the cohesive zone and to avoid artificial complexity in the solutions. Our modelling results show that the two methods provide very similar time histories of dynamic source parameters. We point out that, if a careful control of resolution and stability is performed, the two methods yield identical solutions. We have also compared the rupture evolution resulting from an SW and a rate- and state-dependent friction law. This comparison shows that despite the different constitutive formulations, a similar behaviour is simulated during the rupture propagation and arrest. We also observe a crack tip bifurcation and a jump in rupture velocity (approaching the P-wave speed) with the Dieterich-Ruina (DR) law. The rupture arrest at a barrier (high strength zone) and the barrier-healing mechanism are also reproduced by this law. However, this constitutive formulation allows the simulation of a more general and complex variety of rupture behaviours. By assuming different heterogeneous distributions of the initial constitutive parameters, we are able to model a barrier-healing as well as a self-healing process. This result suggests that if the heterogeneity of the constitutive parameters is taken into account, the different healing mechanisms can be simulated. We also study the nucleation phase duration Tn, defined as the time
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
Product quality driven design of bakery operations using dynamic optimization
Hadiyanto, M.; Esveld, D.C.; Boom, R.M.; Straten, van G.; Boxtel, van A.J.B.
2008-01-01
Abstract Quality driven design uses specified product qualities as a starting point for process design. By backward reasoning the required process conditions and processing system were found. In this work dynamic optimization was used as a tool to generate processing solutions for baking processes
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.
Optimization of multi-response dynamic systems integrating multiple ...
African Journals Online (AJOL)
It also results in better optimization performance than back-propagation neural network-based approach and data mining-based approach reported by the past researchers. Keywords: multiple responses, multiple regression, weighted dynamic signal-to-noise ratio, performance measure modelling, response function ...
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.
Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.
Wei, Qinglai; Liu, Derong; Lin, Hanquan
2016-03-01
In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.
Boland, J. S., III
1973-01-01
The conventional six-engine reaction control jet relay attitude control law with deadband is shown to be a good linear approximation to a weighted time-fuel optimal control law. Techniques for evaluating the value of the relative weighting between time and fuel for a particular relay control law is studied along with techniques to interrelate other parameters for the two control laws. Vehicle attitude control laws employing control moment gyros are then investigated. Steering laws obtained from the expression for the reaction torque of the gyro configuration are compared to a total optimal attitude control law that is derived from optimal linear regulator theory. This total optimal attitude control law has computational disadvantages in the solving of the matrix Riccati equation. Several computational algorithms for solving the matrix Riccati equation are investigated with respect to accuracy, computational storage requirements, and computational speed.
Scaling symmetries, conservation laws and action principles in one-dimensional gas dynamics
International Nuclear Information System (INIS)
Webb, G M; Zank, G P
2009-01-01
Scaling symmetries of the planar, one-dimensional gas dynamic equations with adiabatic index γ are used to obtain Lagrangian and Eulerian conservation laws associated with the symmetries. The known Eulerian symmetry operators for the scaling symmetries are converted to the Lagrangian form, in which the Eulerian spatial position of the fluid element is given in terms of the Lagrangian fluid labels. Conditions for a linear combination of the three scaling symmetries to be a divergence or variational symmetry of the action are established. The corresponding Lagrangian and Eulerian form of the conservation laws are determined by application of Noether's theorem. A nonlocal conservation law associated with the scaling symmetries is obtained by applying a nonlocal symmetry operator to the scaling symmetry-conserved vector. An action principle incorporating known conservation laws using Lagrangian constraints is developed. Noether's theorem for the constrained action principle gives the same formulas for the conserved vector as the classical Noether theorem, except that the Lie symmetry vector field now includes the effects of nonlocal potentials. Noether's theorem for the constrained action principle is used to obtain nonlocal conservation laws. The scaling symmetry conservation laws only apply for special forms of the entropy of the gas.
International Nuclear Information System (INIS)
Alves, Lourenco Gobira; Nebra, Silvia Azucena
2004-01-01
One of the proposals to increase the performance of the gas turbines is to improve chemical recuperated cycle. In this cycle, the heat in the turbine exhaust gases is used to heat and modify the chemical characteristics of the fuel. One mixture of natural gas and steam receives heat from the exhaust turbine gases; the mixture components react among themselves producing hot synthesis gas. In this work, an analysis and nonlinear optimization of the cycle were made in order to investigate the temperature and pressure influence on the global cycle performance. The chemical composition in the reformer was assumed according to chemical equilibrium equations, which presents good agreement with data from literature. The mixture of hot gases was treated like ideal gases. The maximum net profit was achieved and a thermodynamic second law analysis was made in order to detect the greatest sources of irreversibility
A test of star formation laws in disk galaxies. II. Dependence on dynamical properties
International Nuclear Information System (INIS)
Suwannajak, Chutipong; Tan, Jonathan C.; Leroy, Adam K.
2014-01-01
We use the observed radial profiles of the mass surface densities of total, Σ g , and molecular, Σ H2 , gas, rotation velocity, and star formation rate (SFR) surface density, Σ sfr , of the molecular-rich (Σ H2 ≥ Σ HI /2) regions of 16 nearby disk galaxies to test several star formation (SF) laws: a 'Kennicutt-Schmidt (K-S)' law, Σ sfr =A g Σ g,2 1.5 ; a 'Constant Molecular' law, Σ sfr = A H2 Σ H2,2 ; the turbulence-regulated laws of Krumholz and McKee (KM05) and Krumholz, McKee, and Tumlinson (KMT09); a 'Gas-Ω' law, Σ sfr =B Ω Σ g Ω; and a shear-driven 'giant molecular cloud (GMC) Collision' law, Σ sfr = B CC Σ g Ω(1-0.7β), where β ≡ d ln v circ /d ln r. If allowed one free normalization parameter for each galaxy, these laws predict the SFR with rms errors of factors of 1.4-1.8. If a single normalization parameter is used by each law for the entire galaxy sample, then rms errors range from factors of 1.5-2.1. Although the Constant Molecular law gives the smallest rms errors, the improvement over the KMT, K-S, and GMC Collision laws is not especially significant, particularly given the different observational inputs that the laws utilize and the scope of included physics, which ranges from empirical relations to detailed treatment of interstellar medium processes. We next search for systematic variation of SF law parameters with local and global galactic dynamical properties of disk shear rate (related to β), rotation speed, and presence of a bar. We demonstrate with high significance that higher shear rates enhance SF efficiency per local orbital time. Such a trend is expected if GMC collisions play an important role in SF, while an opposite trend would be expected if the development of disk gravitational instabilities is the controlling physics.
Li, Yanning
2014-03-01
This article presents a new optimal control framework for transportation networks in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi (H-J) equation and the commonly used triangular fundamental diagram, we pose the problem of controlling the state of the system on a network link, in a finite horizon, as a Linear Program (LP). We then show that this framework can be extended to an arbitrary transportation network, resulting in an LP or a Quadratic Program. Unlike many previously investigated transportation network control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e., discontinuities in the state of the system). As it leverages the intrinsic properties of the H-J equation used to model the state of the system, it does not require any approximation, unlike classical methods that are based on discretizations of the model. The computational efficiency of the method is illustrated on a transportation network. © 2014 IEEE.
Li, Yanning; Canepa, Edward S.; Claudel, Christian
2014-01-01
This article presents a new optimal control framework for transportation networks in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi (H-J) equation and the commonly used triangular fundamental diagram, we pose the problem of controlling the state of the system on a network link, in a finite horizon, as a Linear Program (LP). We then show that this framework can be extended to an arbitrary transportation network, resulting in an LP or a Quadratic Program. Unlike many previously investigated transportation network control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e., discontinuities in the state of the system). As it leverages the intrinsic properties of the H-J equation used to model the state of the system, it does not require any approximation, unlike classical methods that are based on discretizations of the model. The computational efficiency of the method is illustrated on a transportation network. © 2014 IEEE.
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.
Directory of Open Access Journals (Sweden)
Meiping Wang
2016-01-01
Full Text Available We developed an effective intelligent model to predict the dynamic heat supply of heat source. A hybrid forecasting method was proposed based on support vector regression (SVR model-optimized particle swarm optimization (PSO algorithms. Due to the interaction of meteorological conditions and the heating parameters of heating system, it is extremely difficult to forecast dynamic heat supply. Firstly, the correlations among heat supply and related influencing factors in the heating system were analyzed through the correlation analysis of statistical theory. Then, the SVR model was employed to forecast dynamic heat supply. In the model, the input variables were selected based on the correlation analysis and three crucial parameters, including the penalties factor, gamma of the kernel RBF, and insensitive loss function, were optimized by PSO algorithms. The optimized SVR model was compared with the basic SVR, optimized genetic algorithm-SVR (GA-SVR, and artificial neural network (ANN through six groups of experiment data from two heat sources. The results of the correlation coefficient analysis revealed the relationship between the influencing factors and the forecasted heat supply and determined the input variables. The performance of the PSO-SVR model is superior to those of the other three models. The PSO-SVR method is statistically robust and can be applied to practical heating system.
A dynamic inertia weight particle swarm optimization algorithm
International Nuclear Information System (INIS)
Jiao Bin; Lian Zhigang; Gu Xingsheng
2008-01-01
Particle swarm optimization (PSO) algorithm has been developing rapidly and has been applied widely since it was introduced, as it is easily understood and realized. This paper presents an improved particle swarm optimization algorithm (IPSO) to improve the performance of standard PSO, which uses the dynamic inertia weight that decreases according to iterative generation increasing. It is tested with a set of 6 benchmark functions with 30, 50 and 150 different dimensions and compared with standard PSO. Experimental results indicate that the IPSO improves the search performance on the benchmark functions significantly
LQ optimal and reaching law-based sliding modes for inventory management systems
Ignaciuk, Przemysław; Bartoszewicz, Andrzej
2012-01-01
In this article, the theory of discrete sliding-mode control is used to design new supply strategies for periodic-review inventory systems. In the considered systems, the stock used to fulfil an unknown, time-varying demand can be replenished from a single supply source or from multiple suppliers procuring orders with different delays. The proposed strategies guarantee that demand is always entirely satisfied from the on-hand stock (yielding the maximum service level), and the warehouse capacity is not exceeded (which eliminates the cost of emergency storage). In contrast to the classical, stochastic approaches, in this article, we focus on optimising the inventory system dynamics. The parameters of the first control strategy are selected by minimising a quadratic cost functional. Next, it is shown how the system dynamical performance can be improved by applying the concept of a reaching law with the appropriately adjusted reaching phase. The stable, nonoscillatory behaviour of the closed-loop system is demonstrated and the properties of the designed controllers are discussed and strictly proved.
Interactions of Delta Shock Waves for Zero-Pressure Gas Dynamics with Energy Conservation Law
Directory of Open Access Journals (Sweden)
Wei Cai
2016-01-01
Full Text Available We study the interactions of delta shock waves and vacuum states for the system of conservation laws of mass, momentum, and energy in zero-pressure gas dynamics. The Riemann problems with initial data of three piecewise constant states are solved case by case, and four different configurations of Riemann solutions are constructed. Furthermore, the numerical simulations completely coinciding with theoretical analysis are shown.
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...
Optimal dynamic performance for high-precision actuators/stages
International Nuclear Information System (INIS)
Preissner, C.; Lee, S.-H.; Royston, T. J.; Shu, D.
2002-01-01
System dynamic performance of actuator/stage groups, such as those found in optical instrument positioning systems and other high-precision applications, is dependent upon both individual component behavior and the system configuration. Experimental modal analysis techniques were implemented to determine the six degree of freedom stiffnesses and damping for individual actuator components. These experimental data were then used in a multibody dynamic computer model to investigate the effect of stage group configuration. Running the computer model through the possible stage configurations and observing the predicted vibratory response determined the optimal stage group configuration. Configuration optimization can be performed for any group of stages, provided there is stiffness and damping data available for the constituent pieces
How reflected wave fronts dynamically establish Hooke's law in a spring
International Nuclear Information System (INIS)
Fahy, Stephen; O'Riordan, John; O'Sullivan, Colm; Twomey, Patrick
2012-01-01
A simple benchtop experiment in which a moving cart collides with a fixed spring is described. Force-time and force-distance data recorded during the collision display the transit of compression wave fronts through the spring following impact. These data can be used by students to develop a computational model of the dynamics of this simple mass-spring-sensor system using a simple application of the wave equation and thereby develop an intriguing picture of how a spring realizes Hooke's law approximately in this dynamic physical problem. (paper)
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.
Dynamic optimal foraging theory explains vertical migrations of bigeye tuna
DEFF Research Database (Denmark)
Thygesen, Uffe Høgsbro; Sommer, Lene; Evans, Karen
2016-01-01
Bigeye tuna are known for remarkable daytime vertical migrations between deep water, where food is abundant but the water is cold, and the surface, where water is warm but food is relatively scarce. Here we investigate if these dive patterns can be explained by dynamic optimal foraging theory...... behaves such as to maximize its energy gains. The model therefore provides insight into the processes underlying observed behavioral patterns and allows generating predictions of foraging behavior in unobserved environments...
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
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
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
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.
Energy and ancillary service dispatch through dynamic optimal power flow
International Nuclear Information System (INIS)
Costa, A.L.; Costa, A. Simoes
2007-01-01
This paper presents an approach based on dynamic optimal power flow (DOPF) to clear both energy and spinning reserve day-ahead markets. A competitive environment is assumed, where agents can offer active power for both demand supply and ancillary services. The DOPF jointly determines the optimal solutions for both energy dispatch and reserve allocation. A non-linear representation for the electrical network is employed, which is able to take transmission losses and power flow limits into account. An attractive feature of the proposed approach is that the final optimal solution will automatically meet physical constraints such as generating limits and ramp rate restrictions. In addition, the proposed framework allows the definition of multiple zones in the network for each time interval, in order to ensure a more adequate distribution of reserves throughout the power system. (author)
Optimal protocols for Hamiltonian and Schrödinger dynamics
International Nuclear Information System (INIS)
Schmiedl, Tim; Dieterich, Eckhard; Dieterich, Peter-Simon; Seifert, Udo
2009-01-01
For systems in an externally controllable time dependent potential, the optimal protocol minimizes the mean work spent in a finite time transition between given initial and final values of a control parameter. For an initially thermalized ensemble, we consider both Hamiltonian evolution for classical systems and Schrödinger evolution for quantum systems. In both cases, we show that for harmonic potentials, the optimal work is given by the adiabatic work even in the limit of short transition times. This result is counter-intuitive because the adiabatic work is substantially smaller than the work for an instantaneous jump. We also perform numerical calculations for the optimal protocol for Hamiltonian dynamics in an anharmonic quartic potential. For a two-level spin system, we give examples where the adiabatic work can be reached in either a finite or an arbitrarily short transition time depending on the allowed parameter space
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.
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.
Algorithms for optimal sequencing of dynamic multileaf collimators
International Nuclear Information System (INIS)
Kamath, Srijit; Sahni, Sartaj; Palta, Jatinder; Ranka, Sanjay
2004-01-01
Dynamic multileaf collimator (DMLC) intensity modulated radiation therapy (IMRT) is used to deliver intensity modulated beams using a multileaf collimator (MLC), with the leaves in motion. DMLC-IMRT requires the conversion of a radiation intensity map into a leaf sequence file that controls the movement of the MLC while the beam is on. It is imperative that the intensity map delivered using the leaf sequence file be as close as possible to the intensity map generated by the dose optimization algorithm, while satisfying hardware constraints of the delivery system. Optimization of the leaf-sequencing algorithm has been the subject of several recent investigations. In this work, we present a systematic study of the optimization of leaf-sequencing algorithms for dynamic multileaf collimator beam delivery and provide rigorous mathematical proofs of optimized leaf sequence settings in terms of monitor unit (MU) efficiency under the most common leaf movement constraints that include leaf interdigitation constraint. Our analytical analysis shows that leaf sequencing based on unidirectional movement of the MLC leaves is as MU efficient as bi-directional movement of the MLC leaves
Algorithms for optimal sequencing of dynamic multileaf collimators
Energy Technology Data Exchange (ETDEWEB)
Kamath, Srijit [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Sahni, Sartaj [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Palta, Jatinder [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Ranka, Sanjay [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States)
2004-01-07
Dynamic multileaf collimator (DMLC) intensity modulated radiation therapy (IMRT) is used to deliver intensity modulated beams using a multileaf collimator (MLC), with the leaves in motion. DMLC-IMRT requires the conversion of a radiation intensity map into a leaf sequence file that controls the movement of the MLC while the beam is on. It is imperative that the intensity map delivered using the leaf sequence file be as close as possible to the intensity map generated by the dose optimization algorithm, while satisfying hardware constraints of the delivery system. Optimization of the leaf-sequencing algorithm has been the subject of several recent investigations. In this work, we present a systematic study of the optimization of leaf-sequencing algorithms for dynamic multileaf collimator beam delivery and provide rigorous mathematical proofs of optimized leaf sequence settings in terms of monitor unit (MU) efficiency under the most common leaf movement constraints that include leaf interdigitation constraint. Our analytical analysis shows that leaf sequencing based on unidirectional movement of the MLC leaves is as MU efficient as bi-directional movement of the MLC leaves.
Optimization of Dynamic Aperture of PEP-X Baseline Design
Energy Technology Data Exchange (ETDEWEB)
Wang, Min-Huey; /SLAC; Cai, Yunhai; /SLAC; Nosochkov, Yuri; /SLAC
2010-08-23
SLAC is developing a long-range plan to transfer the evolving scientific programs at SSRL from the SPEAR3 light source to a much higher performing photon source. Storage ring design is one of the possibilities that would be housed in the 2.2-km PEP-II tunnel. The design goal of PEPX storage ring is to approach an optimal light source design with horizontal emittance less than 100 pm and vertical emittance of 8 pm to reach the diffraction limit of 1-{angstrom} x-ray. The low emittance design requires a lattice with strong focusing leading to high natural chromaticity and therefore to strong sextupoles. The latter caused reduction of dynamic aperture. The dynamic aperture requirement for horizontal injection at injection point is about 10 mm. In order to achieve the desired dynamic aperture the transverse non-linearity of PEP-X is studied. The program LEGO is used to simulate the particle motion. The technique of frequency map is used to analyze the nonlinear behavior. The effect of the non-linearity is tried to minimize at the given constrains of limited space. The details and results of dynamic aperture optimization are discussed in this paper.
Optimization of Dynamic Aperture of PEP-X Baseline Design
International Nuclear Information System (INIS)
Wang, Min-Huey
2010-01-01
SLAC is developing a long-range plan to transfer the evolving scientific programs at SSRL from the SPEAR3 light source to a much higher performing photon source. Storage ring design is one of the possibilities that would be housed in the 2.2-km PEP-II tunnel. The design goal of PEPX storage ring is to approach an optimal light source design with horizontal emittance less than 100 pm and vertical emittance of 8 pm to reach the diffraction limit of 1-(angstrom) x-ray. The low emittance design requires a lattice with strong focusing leading to high natural chromaticity and therefore to strong sextupoles. The latter caused reduction of dynamic aperture. The dynamic aperture requirement for horizontal injection at injection point is about 10 mm. In order to achieve the desired dynamic aperture the transverse non-linearity of PEP-X is studied. The program LEGO is used to simulate the particle motion. The technique of frequency map is used to analyze the nonlinear behavior. The effect of the non-linearity is tried to minimize at the given constrains of limited space. The details and results of dynamic aperture optimization are discussed in this paper.
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.
Genetic algorithm enhanced by machine learning in dynamic aperture optimization
Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert
2018-05-01
With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.
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.
Tutcuoglu, A.; Majidi, C.
2014-12-01
Using principles of damped harmonic oscillation with continuous media, we examine electrostatic energy harvesting with a "soft-matter" array of dielectric elastomer (DE) transducers. The array is composed of infinitely thin and deformable electrodes separated by layers of insulating elastomer. During vibration, it deforms longitudinally, resulting in a change in the capacitance and electrical enthalpy of the charged electrodes. Depending on the phase of electrostatic loading, the DE array can function as either an actuator that amplifies small vibrations or a generator that converts these external excitations into electrical power. Both cases are addressed with a comprehensive theory that accounts for the influence of viscoelasticity, dielectric breakdown, and electromechanical coupling induced by Maxwell stress. In the case of a linearized Kelvin-Voigt model of the dielectric, we obtain a closed-form estimate for the electrical power output and a scaling law for DE generator design. For the complete nonlinear model, we obtain the optimal electrostatic voltage input for maximum electrical power output.
Directory of Open Access Journals (Sweden)
Charles A Price
Full Text Available Models that predict the form of hierarchical branching networks typically invoke optimization based on biomechanical similitude, the minimization of impedance to fluid flow, or construction costs. Unfortunately, due to the small size and high number of vein segments found in real biological networks, complete descriptions of networks needed to evaluate such models are rare. To help address this we report results from the analysis of the branching geometry of 349 leaf vein networks comprising over 1.5 million individual vein segments. In addition to measuring the diameters of individual veins before and after vein bifurcations, we also assign vein orders using the Horton-Strahler ordering algorithm adopted from the study of river networks. Our results demonstrate that across all leaves, both radius tapering and the ratio of daughter to parent branch areas for leaf veins are in strong agreement with the expectation from Murray's law. However, as veins become larger, area ratios shift systematically toward values expected under area-preserving branching. Our work supports the idea that leaf vein networks differentiate roles of leaf support and hydraulic supply between hierarchical orders.
The Dynamics of Multiple Pair-Wise Collisions in a Chain for Designing Optimal Shock Amplifiers
Directory of Open Access Journals (Sweden)
Bryan Rodgers
2009-01-01
Full Text Available The major focus of this work is to examine the dynamics of velocity amplification through pair-wise collisions between multiple masses in a chain, in order to develop useful machines. For instance low-cost machines based on this principle could be used for detailed, very-high acceleration shock-testing of MEMS devices. A theoretical basis for determining the number and mass of intermediate stages in such a velocity amplifier, based on simple rigid body mechanics, is proposed. The influence of mass ratios and the coefficient of restitution on the optimisation of the system is identified and investigated. In particular, two cases are examined: in the first, the velocity of the final mass in the chain (that would have the object under test mounted on it is maximised by defining the ratio of adjacent masses according to a power law relationship; in the second, the energy transfer efficiency of the system is maximised by choosing the mass ratios such that all masses except the final mass come to rest following impact. Comparisons are drawn between both cases and the results are used in proposing design guidelines for optimal shock amplifiers. It is shown that for most practical systems, a shock amplifier with mass ratios based on a power law relationship is optimal and can easily yield velocity amplifications of a factor 5–8 times. A prototype shock testing machine that was made using above principles is briefly introduced.
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.
Feedback optimal control of dynamic stochastic two-machine flowshop with a finite buffer
Directory of Open Access Journals (Sweden)
Thang Diep
2010-06-01
Full Text Available This paper examines the optimization of production involving a tandem two-machine system producing a single part type, with each machine being subject to random breakdowns and repairs. An analytical model is formulated with a view to solving an optimal stochastic production problem of the system with machines having up-downtime non-exponential distributions. The model developed is obtained by using a dynamic programming approach and a semi-Markov process. The control problem aims to find the production rates needed by the machines to meet the demand rate, through a minimization of the inventory/shortage cost. Using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation, which depends on time and system states, and ultimately, leads to a feedback control. Consequently, the new model enables us to improve the coefficient of variation (CVup/down to be less than one while it is equal to one in Markov model. Heuristics methods are used to involve the problem because of the difficulty of the analytical model using several states, and to show what control law should be used in each system state (i.e., including Kanban, feedback and CONWIP control. Numerical methods are used to solve the optimality conditions and to show how a machine should produce.
Directory of Open Access Journals (Sweden)
Patrick Piprek
2018-02-01
Full Text Available This paper presents an approach to model a ski jumper as a multi-body system for an optimal control application. The modeling is based on the constrained Newton-Euler-Equations. Within this paper the complete multi-body modeling methodology as well as the musculoskeletal modeling is considered. For the musculoskeletal modeling and its incorporation in the optimization model, we choose a nonlinear dynamic inversion control approach. This approach uses the muscle models as nonlinear reference models and links them to the ski jumper movement by a control law. This strategy yields a linearized input-output behavior, which makes the optimal control problem easier to solve. The resulting model of the ski jumper can then be used for trajectory optimization whose results are compared to literature jumps. Ultimately, this enables the jumper to get a very detailed feedback of the flight. To achieve the maximal jump length, exact positioning of his body with respect to the air can be displayed.
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)
Optimizing spread dynamics on graphs by message passing
Altarelli, F.; Braunstein, A.; Dall'Asta, L.; Zecchina, R.
2013-09-01
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).
Research on Dynamic Optimization for Road-friendly Vehicle Suspension
Directory of Open Access Journals (Sweden)
Lu Yongjie
2014-10-01
Full Text Available The heavy vehicle brings large dynamic loads to the road surface, which would reduce vehicle ride comfort and shorten road service life. The structure characteristic of heavy vehicle suspension has a significant impact on vehicle performance. Based on the D'Alembert principle, the dynamics models of independent and integral balanced suspension are proposed considering mass and inertia of balancing rod. The sprung mass acceleration and the tire dynamic force for two kinds of balanced suspension and the traditional quarter vehicle model are compared in frequency-domain and time-domain respectively. It is concluded that a quarter vehicle model simplified for balanced suspension could be used to evaluate the ride comfort of vehicle well, but it has some limitations in assessing the vehicle road-friendliness. Then, the sprung mass acceleration and the road damage coefficients are also analyzed under different vehicle design and running parameters at detail. Some conclusions are obtained: low suspension stiffness, high suspension damping and low tire stiffness are all favorable to improve vehicle performance; there is a saturation range of suspension damping enhancing vehicle performance; improving the road surface roughness and avoiding the no-load running are two effective methods to accomplish the better ride comfort and road-friendliness. The suspension stiffness and damping parameters are chosen for optimal parameters matching of road friendliness based on the approximation optimization method.
International Nuclear Information System (INIS)
Zhao Gang-Ling; Chen Li-Qun; Fu Jing-Li; Hong Fang-Yu
2013-01-01
In this paper, Noether symmetry and Mei symmetry of discrete nonholonomic dynamical systems with regular and the irregular lattices are investigated. Firstly, the equations of motion of discrete nonholonomic systems are introduced for regular and irregular lattices. Secondly, for cases of the two lattices, based on the invariance of the Hamiltomian functional under the infinitesimal transformation of time and generalized coordinates, we present the quasi-extremal equation, the discrete analogues of Noether identity, Noether theorems, and the Noether conservation laws of the systems. Thirdly, in cases of the two lattices, we study the Mei symmetry in which we give the discrete analogues of the criterion, the theorem, and the conservative laws of Mei symmetry for the systems. Finally, an example is discussed for the application of the results
Optimal diabatic dynamics of Majorana-based quantum gates
Rahmani, Armin; Seradjeh, Babak; Franz, Marcel
2017-08-01
In topological quantum computing, unitary operations on qubits are performed by adiabatic braiding of non-Abelian quasiparticles, such as Majorana zero modes, and are protected from local environmental perturbations. In the adiabatic regime, with timescales set by the inverse gap of the system, the errors can be made arbitrarily small by performing the process more slowly. To enhance the performance of quantum information processing with Majorana zero modes, we apply the theory of optimal control to the diabatic dynamics of Majorana-based qubits. While we sacrifice complete topological protection, we impose constraints on the optimal protocol to take advantage of the nonlocal nature of topological information and increase the robustness of our gates. By using the Pontryagin's maximum principle, we show that robust equivalent gates to perfect adiabatic braiding can be implemented in finite times through optimal pulses. In our implementation, modifications to the device Hamiltonian are avoided. Focusing on thermally isolated systems, we study the effects of calibration errors and external white and 1 /f (pink) noise on Majorana-based gates. While a noise-induced antiadiabatic behavior, where a slower process creates more diabatic excitations, prohibits indefinite enhancement of the robustness of the adiabatic scheme, our fast optimal protocols exhibit remarkable stability to noise and have the potential to significantly enhance the practical performance of Majorana-based information processing.
Numerical Optimization Design of Dynamic Quantizer via Matrix Uncertainty Approach
Directory of Open Access Journals (Sweden)
Kenji Sawada
2013-01-01
Full Text Available In networked control systems, continuous-valued signals are compressed to discrete-valued signals via quantizers and then transmitted/received through communication channels. Such quantization often degrades the control performance; a quantizer must be designed that minimizes the output difference between before and after the quantizer is inserted. In terms of the broadbandization and the robustness of the networked control systems, we consider the continuous-time quantizer design problem. In particular, this paper describes a numerical optimization method for a continuous-time dynamic quantizer considering the switching speed. Using a matrix uncertainty approach of sampled-data control, we clarify that both the temporal and spatial resolution constraints can be considered in analysis and synthesis, simultaneously. Finally, for the slow switching, we compare the proposed and the existing methods through numerical examples. From the examples, a new insight is presented for the two-step design of the existing continuous-time optimal quantizer.
International Nuclear Information System (INIS)
Li Xi; Deng Zhonghua; Wei Dong; Xu Chunshan; Cao Guangyi
2011-01-01
Highlights: →We build up the thermal expressions of PEMFC stack. → The expressions are converted into the affine state space control-oriented model for the VSC strategy. → The NGA is developed to optimize the parameter of thermal-model-oriented control law. → Numerical results demonstrate the effectiveness and rationality of the method proposed. - Abstract: It is critical to understand and manage the thermal effects in optimizing the performance and durability of proton exchange membrane fuel cell (PEMFC) stack. And building up the control-oriented thermal model of PEMFC stack is necessary. The thermal model, a set of differential equations, is established according to the conservation equations of mass and energy, which can be used to reflect truly the actual temperature response of PEMFC stack, however, the expressions of the model are too complicated to be used in the design of control. For this reason, the expressions are converted into the affine state space control-oriented model in detail for the variable structure control (VSC) strategy. Meanwhile, the accurate model must be established for the VSC and the parameters of VSC laws should be optimized. Consequently, a novel genetic algorithm (NGA) is developed to optimize the parameter of thermal-model-oriented control law for PEMFC stack. Finally, numerical test results demonstrate the effectiveness and rationality of the method proposed in this paper. It lays the foundation for the realization of online thermal management of PEMFC stack based on VSC.
A dynamic model of optimal reduction of marine oil pollution
Energy Technology Data Exchange (ETDEWEB)
Deissenberg, C. [CEFI-CNRS, Les Milles (France); Gottinger, H.W. [International Inst. for Environmental Economics and Management, Bad Waldsee (Germany); Gurman, V. [RAS, Program Systems Inst., Pereslavl-Zalessky (Russian Federation); Marinushkin, D. [Pereslavl Univ., Pereslavl-Zalessky (Russian Federation)
2001-07-01
This paper proposes a system of dynamic models to describe the interactive behaviour of different agents (polluters, inspectors, and a principal pollution control agency) involved in the processes of marine oil pollution and of its prevention and purification, under some realistic assumptions, In particular, short- and long-term economic responses of polluters to monitoring efforts, as well as possible collusions between polluters and inspectors, are taken into account. A numerical example is considered using the results of Deissenberg et al., (2001), which show the existence of optimal fines and inspector wage rates that minimize (along with other variables) a simple and visual 'social damage' criterion. (Author)
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.
Dynamic mesh optimization based on the spring analogy
Directory of Open Access Journals (Sweden)
Schmidt Jonas
2014-01-01
Full Text Available We present an implementation of the spring analogy for three dimensional meshes in OpenFOAM. All parameters of the spring system are treated as fields that can either be pre-defined by the user, or updated at each time step according to specified geometrical regions or diffusion equations. The purpose of the method is to provide a pre-processing tool for mesh optimization. We study three simple test cases, a deformed block, an airfoil and a hill, and we analyze the evolution of skewness, non-orthogonality and aspect ratio during the approach of dynamic equilibrium.
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.
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.
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 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.
Power-law Growth and Punctuated Equilibrium Dynamics in Water Resources Systems
Parolari, A.; Katul, G. G.; Porporato, A. M.
2015-12-01
The global rise in population-driven water scarcity and recent appreciation of strong dynamic coupling between human and natural systems has called for new approaches to predict the future sustainability of regional and global water resources systems. The dynamics of coupled human-water systems are driven by a complex set of social, environmental, and technological factors. Present projections of water resources systems range from a finite carrying capacity regulated by accessible freshwater, or `peak renewable water,' to punctuated evolution with new supplied and improved efficiency gained from technological and social innovation. However, these projections have yet to be quantified from observations or in a comprehensive theoretical framework. Using data on global water withdrawals and storage capacity of regional water supply systems, non-trivial dynamics are identified in water resources systems development over time, including power-law growth and punctuated equilibria. Two models are introduced to explain this behavior: (1) a delay differential equation and (2) a power-law with log-periodic oscillations, both of which rely on past conditions (or system memory) to describe the present rate of growth in the system. In addition, extension of the first model demonstrates how system delays and punctuated equilibria can emerge from coupling between human population growth and associated resource demands. Lastly, anecdotal evidence is used to demonstrate the likelihood of power-law growth in global water use from the agricultural revolution 3000 BC to the present. In a practical sense, the presence of these patterns in models with delayed oscillations suggests that current decision-making related to water resources development results from the historical accumulation of resource use decisions, technological and social changes, and their consequences.
Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments
Directory of Open Access Journals (Sweden)
Renata De Paris
2015-01-01
Full Text Available Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.
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.
Doubly Robust Estimation of Optimal Dynamic Treatment Regimes
DEFF Research Database (Denmark)
Barrett, Jessica K; Henderson, Robin; Rosthøj, Susanne
2014-01-01
We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret-regression appro......We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret......-regression approach of Almirall et al. (in Biometrics 66:131-139, 2010) and Henderson et al. (in Biometrics 66:1192-1201, 2010) and demonstrate that it is equivalent to a reduced form of Robins' efficient g-estimation procedure (Robins, in Proceedings of the Second Symposium on Biostatistics. Springer, New York, pp....... 189-326, 2004). Simulation studies suggest that while the regret-regression approach is most efficient when there is no model misspecification, in the presence of misspecification the efficient g-estimation procedure is more robust. The g-estimation method can be difficult to apply in complex...
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.
Quantitative law describing market dynamics before and after interest-rate change
International Nuclear Information System (INIS)
Petersen, Alexander M.; Wang Fengzhong; Stanley, H. Eugene; Havlin, Shlomo
2010-01-01
We study the behavior of U.S. markets both before and after U.S. Federal Open Market Commission meetings and show that the announcement of a U.S. Federal Reserve rate change causes a financial shock, where the dynamics after the announcement is described by an analog of the Omori earthquake law. We quantify the rate n(t) of aftershocks following an interest-rate change at time T and find power-law decay which scales as n(t-T)∼(t-T) -Ω , with Ω positive. Surprisingly, we find that the same law describes the rate n ' (|t-T|) of 'preshocks' before the interest-rate change at time T. This study quantitatively relates the size of the market response to the news which caused the shock and uncovers the presence of quantifiable preshocks. We demonstrate that the news associated with interest-rate change is responsible for causing both the anticipation before the announcement and the surprise after the announcement. We estimate the magnitude of financial news using the relative difference between the U.S. Treasury Bill and the Federal Funds effective rate. Our results are consistent with the 'sign effect', in which 'bad news' has a larger impact than 'good news'. Furthermore, we observe significant volatility aftershocks, confirming a 'market under-reaction' that lasts at least one trading day.
Quantitative law describing market dynamics before and after interest-rate change.
Petersen, Alexander M; Wang, Fengzhong; Havlin, Shlomo; Stanley, H Eugene
2010-06-01
We study the behavior of U.S. markets both before and after U.S. Federal Open Market Commission meetings and show that the announcement of a U.S. Federal Reserve rate change causes a financial shock, where the dynamics after the announcement is described by an analog of the Omori earthquake law. We quantify the rate n(t) of aftershocks following an interest-rate change at time T and find power-law decay which scales as n(t-T)∼(t-T)(-Ω) , with Ω positive. Surprisingly, we find that the same law describes the rate n'(|t-T|) of "preshocks" before the interest-rate change at time T . This study quantitatively relates the size of the market response to the news which caused the shock and uncovers the presence of quantifiable preshocks. We demonstrate that the news associated with interest-rate change is responsible for causing both the anticipation before the announcement and the surprise after the announcement. We estimate the magnitude of financial news using the relative difference between the U.S. Treasury Bill and the Federal Funds effective rate. Our results are consistent with the "sign effect," in which "bad news" has a larger impact than "good news." Furthermore, we observe significant volatility aftershocks, confirming a "market under-reaction" that lasts at least one trading day.
Quantitative law describing market dynamics before and after interest-rate change
Petersen, Alexander M.; Wang, Fengzhong; Havlin, Shlomo; Stanley, H. Eugene
2010-06-01
We study the behavior of U.S. markets both before and after U.S. Federal Open Market Commission meetings and show that the announcement of a U.S. Federal Reserve rate change causes a financial shock, where the dynamics after the announcement is described by an analog of the Omori earthquake law. We quantify the rate n(t) of aftershocks following an interest-rate change at time T and find power-law decay which scales as n(t-T)˜(t-T)-Ω , with Ω positive. Surprisingly, we find that the same law describes the rate n'(|t-T|) of “preshocks” before the interest-rate change at time T . This study quantitatively relates the size of the market response to the news which caused the shock and uncovers the presence of quantifiable preshocks. We demonstrate that the news associated with interest-rate change is responsible for causing both the anticipation before the announcement and the surprise after the announcement. We estimate the magnitude of financial news using the relative difference between the U.S. Treasury Bill and the Federal Funds effective rate. Our results are consistent with the “sign effect,” in which “bad news” has a larger impact than “good news.” Furthermore, we observe significant volatility aftershocks, confirming a “market under-reaction” that lasts at least one trading day.
Directory of Open Access Journals (Sweden)
Jui-Teng Lin
2014-02-01
Full Text Available We present a modeling study of photoinitiated polymerization in a thick polymer-absorbing medium using a focused UV laser. Transient profiles of the initiator concentration at various focusing conditions are analyzed to define the polymerization boundary. Furthermore, we demonstrate the optimal focusing conditions that yield more uniform polymerization over a larger volume than the collimated or non-optimal cases. Too much focusing with the focal length f < f* (an optimal focal length yields a fast process; however, it provides a smaller polymerization volume at a given time than in the optimal focusing case. Finally, a scaling law is derived and shows that f* is inverse proportional to the product of the extinction coefficient and the initiator initial concentration. The scaling law provides useful guidance for the prediction of optimal conditions for photoinitiated polymerization under a focused UV laser irradiation. The focusing technique also provides a novel and unique means for obtaining uniform photo-polymerization within a limited irradiation time.
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.
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
Hsiang, J-T; Chou, C H; Subaşı, Y; Hu, B L
2018-01-01
In a series of papers, we intend to take the perspective of open quantum systems and examine from their nonequilibrium dynamics the conditions when the physical quantities, their relations, and the laws of thermodynamics become well defined and viable for quantum many-body systems. We first describe how an open-system nonequilibrium dynamics (ONEq) approach is different from the closed combined system + environment in a global thermal state (CGTs) setup. Only after the open system equilibrates will it be amenable to conventional thermodynamics descriptions, thus quantum thermodynamics (QTD) comes at the end rather than assumed in the beginning. The linkage between the two comes from the reduced density matrix of ONEq in that stage having the same form as that of the system in the CGTs. We see the open-system approach having the advantage of dealing with nonequilibrium processes as many experiments in the near future will call for. Because it spells out the conditions of QTD's existence, it can also aid us in addressing the basic issues in quantum thermodynamics from first principles in a systematic way. We then study one broad class of open quantum systems where the full nonequilibrium dynamics can be solved exactly, that of the quantum Brownian motion of N strongly coupled harmonic oscillators, interacting strongly with a scalar-field environment. In this paper, we focus on the internal energy, heat capacity, and the third law. We show for this class of physical models, amongst other findings, the extensive property of the internal energy, the positivity of the heat capacity, and the validity of the third law from the perspective of the behavior of the heat capacity toward zero temperature. These conclusions obtained from exact solutions and quantitative analysis clearly disprove claims of negative specific heat in such systems and dispel allegations that in such systems the validity of the third law of thermodynamics relies on quantum entanglement. They are
Viscous-elastic dynamics of power-law fluids within an elastic cylinder
Boyko, Evgeniy; Bercovici, Moran; Gat, Amir D.
2017-07-01
In a wide range of applications, microfluidic channels are implemented in soft substrates. In such configurations, where fluidic inertia and compressibility are negligible, the propagation of fluids in channels is governed by a balance between fluid viscosity and elasticity of the surrounding solid. The viscous-elastic interactions between elastic substrates and non-Newtonian fluids are particularly of interest due to the dependence of viscosity on the state of the system. In this work, we study the fluid-structure interaction dynamics between an incompressible non-Newtonian fluid and a slender linearly elastic cylinder under the creeping flow regime. Considering power-law fluids and applying the thin shell approximation for the elastic cylinder, we obtain a nonhomogeneous p-Laplacian equation governing the viscous-elastic dynamics. We present exact solutions for the pressure and deformation fields for various initial and boundary conditions for both shear-thinning and shear-thickening fluids. We show that in contrast to Stokes' problem where a compactly supported front is obtained for shear-thickening fluids, here the role of viscosity is inversed and such fronts are obtained for shear-thinning fluids. Furthermore, we demonstrate that for the case of a step in inlet pressure, the propagation rate of the front has a tn/n +1 dependence on time (t ), suggesting the ability to indirectly measure the power-law index (n ) of shear-thinning liquids through measurements of elastic deformation.
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.
An optimal strategy for functional mapping of dynamic trait loci.
Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling
2010-02-01
As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.
Li, Shan; Lin, Ruokuang; Bian, Chunhua; Ma, Qianli D Y; Ivanov, Plamen Ch
2016-01-01
Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.
Directory of Open Access Journals (Sweden)
Shan Li
Full Text Available Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.
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.
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.
Dynamic Optimization Design of Cranes Based on Human–Crane–Rail System Dynamics and Annoyance Rate
Directory of Open Access Journals (Sweden)
Yunsheng Xin
2017-01-01
Full Text Available The operators of overhead traveling cranes experience discomfort as a result of the vibrations of crane structures. These vibrations are produced by defects in the rails on which the cranes move. To improve the comfort of operators, a nine-degree-of-freedom (nine-DOF mathematical model of a “human–crane–rail” system was constructed. Based on the theoretical guidance provided in ISO 2631-1, an annoyance rate model was established, and quantization results were determined. A dynamic optimization design method for overhead traveling cranes is proposed. A particle swarm optimization (PSO algorithm was used to optimize the crane structural design, with the structure parameters as the basic variables, the annoyance rate model as the objective function, and the acceleration amplitude and displacement amplitude of the crane as the constraint conditions. The proposed model and method were used to optimize the design of a double-girder 100 t–28.5 m casting crane, and the optimal parameters are obtained. The results show that optimization decreases the human annoyance rate from 28.3% to 9.8% and the root mean square of the weighted acceleration of human vibration from 0.59 m/s2 to 0.38 m/s2. These results demonstrate the effectiveness and practical applicability of the models and method proposed in this paper.
Framework for optimal power flow incorporating dynamic system security
International Nuclear Information System (INIS)
El-Kady, M.A.; Owayedh, M.S.
2006-01-01
This paper introduces a novel framework and methodologies which are capable of tackling the complex issue of power system economy versus security in a practical and effective manner. At heart of achieving such a challenging and far-reaching objective is the incorporation of the Dyanamic Security Assessment (DSA) into production optimization techniques using the Transient Energy Function (TEF) method. In addition, and in parallel with the already well established concept of the system security, two new concepts pertaining to power system performance will be introduced in this paper, namely the concept of system dynamic susceptibility, which measures the level of systems weakness to a particular contingency and the concept of system consequent restorability, which measures the extent of contingency severity in terms of the required subsequent system restoration work should a particular contingency occur. (author)
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.
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.
Dynamic control of biped locomotion robot using optimal regulator
International Nuclear Information System (INIS)
Sano, Akihito; Furusho, Junji
1988-01-01
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. (author)
Optimal dispatch in dynamic security constrained open power market
International Nuclear Information System (INIS)
Singh, S.N.; David, A.K.
2002-01-01
Power system security is a new concern in the competitive power market operation, because the integration of the system controller and the generation owner has been broken. This paper presents an approach for dynamic security constrained optimal dispatch in restructured power market environment. The transient energy margin using transient energy function (TEF) approach has been used to calculate the stability margin of the system and a hybrid method is applied to calculate the approximate unstable equilibrium point (UEP) that is used to calculate the exact UEP and thus, the energy margin using TEF. The case study results illustrated on two systems shows that the operating mechanisms are compatible with the new business environment. (author)
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 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)
Dynamic programming approach for partial decision rule optimization
Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata
2012-01-01
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.
The optimal filtering of a class of dynamic multiscale systems
Institute of Scientific and Technical Information of China (English)
PAN Quan; ZHANG Lei; CUI Peiling; ZHANG Hongcai
2004-01-01
This paper discusses the optimal filtering of a class of dynamic multiscale systems (DMS), which are observed independently by several sensors distributed at different resolution spaces. The system is subject to known dynamic system model. The resolution and sampling frequencies of the sensors are supposed to decrease by a factor of two. By using the Haar wavelet transform to link the state nodes at each of the scales within a time block, a discrete-time model of this class of multiscale systems is given, and the conditions for applying Kalman filtering are proven. Based on the linear time-invariant system, the controllability and observability of the system and the stability of the Kalman filtering is studied, and a theorem is given. It is proved that the Kalman filter is stable if only the system is controllable and observable at the finest scale. Finally, a constant-velocity process is used to obtain insight into the efficiencies offered by our model and algorithm.
Scaling Laws in the Transient Dynamics of Firefly-like Oscillators
International Nuclear Information System (INIS)
Rubido, N; Cabeza, C; Marti, A; Ramirez Avila, G M
2011-01-01
Fireflies constitute a paradigm of pulse-coupled oscillators. In order to tackle the problems related to synchronisation transients of pulse-coupled oscillators, a Light-Controlled Oscillator (LCO) model is presented. A single LCO constitutes a one-dimensional relaxation oscillator described by two distinct time-scales meant to mimic fireflies in the sense that: it is capable of emitting light in a pulse-like fashion and detect the emitted by others in order to adjust its oscillation. We present dynamical results for two interacting LCOs in the torus for all possible coupling configurations. Transient times to the synchronous limit cycle are obtained experimentally and numerically as a function of initial conditions and coupling strengths. Scaling laws are found based on dimensional analysis and critical exponents calculated, thus, global dynamic is restricted. Furthermore, an analytical orthogonal transformation that allows to calculate Floquet multipliers directly from the time series is presented. As a consequence, local dynamics is also fully characterized. This transformation can be easily extended to a system with an arbitrary number of interacting LCOs.
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 pro......-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....
Chakraborty, Ahana; Sensarma, Rajdeep
2018-03-01
The Born-Markov approximation is widely used to study the dynamics of open quantum systems coupled to external baths. Using Keldysh formalism, we show that the dynamics of a system of bosons (fermions) linearly coupled to a noninteracting bosonic (fermionic) bath falls outside this paradigm if the bath spectral function has nonanalyticities as a function of frequency. In this case, we show that the dissipative and noise kernels governing the dynamics have distinct power-law tails. The Green's functions show a short-time "quasi"-Markovian exponential decay before crossing over to a power-law tail governed by the nonanalyticity of the spectral function. We study a system of bosons (fermions) hopping on a one-dimensional lattice, where each site is coupled linearly to an independent bath of noninteracting bosons (fermions). We obtain exact expressions for the Green's functions of this system, which show power-law decay ˜|t - t'|-3 /2 . We use these to calculate the density and current profile, as well as unequal-time current-current correlators. While the density and current profiles show interesting quantitative deviations from Markovian results, the current-current correlators show qualitatively distinct long-time power-law tails |t - t'|-3 characteristic of non-Markovian dynamics. We show that the power-law decays survive in the presence of interparticle interaction in the system, but the crossover time scale is shifted to larger values with increasing interaction strength.
Puosi, F; Pasturel, A; Jakse, N; Leporini, D
2018-04-07
The breakdown of the Stokes-Einstein (SE) law in fragile glassformers is examined by Molecular-Dynamics simulations of atomic liquids and polymers and consideration of the experimental data concerning the archetypical ortho-terphenyl glassformer. All the four systems comply with the universal scaling between the viscosity (or the structural relaxation) and the Debye-Waller factor ⟨u 2 ⟩, the mean square amplitude of the particle rattling in the cage formed by the surrounding neighbors. It is found that the SE breakdown is scaled in a master curve by a reduced ⟨u 2 ⟩. Two approximated expressions of the latter, with no and one adjustable parameter, respectively, are derived.
Civitani, Marta; Djalal, Sophie; Chipaux, Remi
2009-08-01
In a X-ray telescope in formation flight configuration, the optics and the focal-plane detectors reside in two different spacecraft. The dynamics of the detector spacecraft (DSC) with respect to the mirror spacecraft (MSC, carrying the mirrors of the telescope) changes continuously the arrival positions of the photons on the detectors. In this paper we analyze this issue for the case of the SIMBOL-X hard X-ray mission, extensively studied by CNES and ASI until 2009 spring. Due to the existing gaps between pixels and between detector modules, the dynamics of the system may produce a relevant photometric effect. The aim of this work is to present the optimization study of the control-law algorithm with respect to the detector's geometry. As the photometric effect may vary depending upon position of the source image on the detector, the analysis-carried out using the simuLOS (INAF, CNES, CEA) simulation tool-is extended over the entire SIMBOL-X field of view.
An Optimization Method for Virtual Globe Ocean Surface Dynamic Visualization
Directory of Open Access Journals (Sweden)
HUANG Wumeng
2016-12-01
Full Text Available The existing visualization method in the virtual globe mainly uses the projection grid to organize the ocean grid. This special grid organization has the defects in reflecting the difference characteristics of different ocean areas. The method of global ocean visualization based on global discrete grid can make up the defect of the projection grid method by matching with the discrete space of the virtual globe, so it is more suitable for the virtual ocean surface simulation application.But the available global discrete grids method has many problems which limiting its application such as the low efficiency of rendering and loading, the need of repairing grid crevices. To this point, we propose an optimization for the global discrete grids method. At first, a GPU-oriented multi-scale grid model of ocean surface which develops on the foundation of global discrete grids was designed to organize and manage the ocean surface grids. Then, in order to achieve the wind-drive wave dynamic rendering, this paper proposes a dynamic wave rendering method based on the multi-scale ocean surface grid model to support real-time wind field updating. At the same time, considering the effect of repairing grid crevices on the system efficiency, this paper presents an efficient method for repairing ocean surface grid crevices based on the characteristics of ocean grid and GPU technology. At last, the feasibility and validity of the method are verified by the comparison experiment. The experimental results show that the proposed method is efficient, stable and fast, and can compensate for the lack of function of the existing methods, so the application range is more extensive.
Terenji, Albert; Willmann, Stefan; Osterholz, Jens; Hering, Peter; Schwarzmaier, Hans-Joachim
2005-06-01
During heating, the optical properties of biological tissues change with the coagulation state. In this study, we propose a technique, which uses these changes to monitor the coagulation process during laser-induced interstitial thermotherapy (LITT). Untreated and coagulated (water bath, temperatures between 35 degrees C and 90 degrees C for 20 minutes.) samples of bovine liver tissue were examined using a Nd:YAG (lambda = 1064 nm) frequency-domain reflectance spectrometer. We determined the time integrated intensities (I(DC)) and the phase shifts (Phi) of the photon density waves after migration through the tissue. From these measured quantities, the time of flight (TOF) of the photons and the absorption coefficients of the samples were derived using the modified microscopic Beer-Lambert law. The absorption coefficients of the liver samples decreased significantly with the temperature in the range between 50 degrees C and 70 degrees C. At the same time, the TOF of the investigated photos was found increased indicating an increased scattering. The coagulation dynamics could be well described using the Arrhenius formalism with the activation energy of 106 kJ/mol and the frequency factor of 1.59 x 10(13)/second. Frequency-domain reflectance spectroscopy in combination with the modified microscopic Beer-Lambert (MBL) is suitable to measure heat induced changes in the absorption and scattering properties of bovine liver in vitro. The technique may be used to monitor the coagulation dynamics during local thermo-coagulation in vivo. Copyright 2005 Wiley-Liss, Inc.
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.
Optimal spectral tracking--adapting to dynamic regime change.
Brittain, John-Stuart; Halliday, David M
2011-01-30
Real world data do not always obey the statistical restraints imposed upon them by sophisticated analysis techniques. In spectral analysis for instance, an ergodic process--the interchangeability of temporal for spatial averaging--is assumed for a repeat-trial design. Many evolutionary scenarios, such as learning and motor consolidation, do not conform to such linear behaviour and should be approached from a more flexible perspective. To this end we previously introduced the method of optimal spectral tracking (OST) in the study of trial-varying parameters. In this extension to our work we modify the OST routines to provide an adaptive implementation capable of reacting to dynamic transitions in the underlying system state. In so doing, we generalise our approach to characterise both slow-varying and rapid fluctuations in time-series, simultaneously providing a metric of system stability. The approach is first applied to a surrogate dataset and compared to both our original non-adaptive solution and spectrogram approaches. The adaptive OST is seen to display fast convergence and desirable statistical properties. All three approaches are then applied to a neurophysiological recording obtained during a study on anaesthetic monitoring. Local field potentials acquired from the posterior hypothalamic region of a deep brain stimulation patient undergoing anaesthesia were analysed. The characterisation of features such as response delay, time-to-peak and modulation brevity are considered. Copyright © 2010 Elsevier B.V. All rights reserved.
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)
Optimal design and dynamic impact tests of removable bollards
Chen, Suwen; Liu, Tianyi; Li, Guoqiang; Liu, Qing; Sun, Jianyun
2017-10-01
Anti-ram bollard systems, which are installed around buildings and infrastructure, can prevent unauthorized vehicles from entering, maintain distance from vehicle-borne improvised explosive devices (VBIED) and reduce the corresponding damage. Compared with a fixed bollard system, a removable bollard system provides more flexibility as it can be removed when needed. This paper first proposes a new type of K4-rated removable anti-ram bollard system. To simulate the collision of a vehicle hitting the bollard system, a finite element model was then built and verified through comparison of numerical simulation results and existing experimental results. Based on the orthogonal design method, the factors influencing the safety and economy of this proposed system were examined and sorted according to their importance. An optimal design scheme was then produced. Finally, to validate the effectiveness of the proposed design scheme, four dynamic impact tests, including two front impact tests and two side impact tests, have been conducted according to BSI Specifications. The residual rotation angles of the specimen are smaller than 30º and satisfy the requirements of the BSI Specification.
Anonymous birth law saves babies--optimization, sustainability and public awareness.
Grylli, Chryssa; Brockington, Ian; Fiala, Christian; Huscsava, Mercedes; Waldhoer, Thomas; Klier, Claudia M
2016-04-01
The aims of this study are to assess the impact of Austria's anonymous birth law from the time relevant statistical records are available and to evaluate the use of hatches versus anonymous hospital delivery. This study is a complete census of police-reported neonaticides (1975-2012) as well as anonymous births including baby hatches in Austria during 2002-2012. The time trends of neonaticide rates, anonymous births and baby hatches were analysed by means of Poisson and logistic regression model. Predicted and observed rates were derived and compared using a Bayesian Poisson regression model. Predicted numbers of neonaticides for the period of the active awareness campaign, 2002-2004, were more than three times larger than the observed number (p = 0.0067). Of the 365 women who benefitted from this legislation, only 11.5% chose to put their babies in a baby hatch. Since the law was introduced, a significant decreasing tendency of numbers of anonymous births (p = 047) was observed, while there was significant increase of neonaticide rates (p = 0.0001). The implementation of the anonymous delivery law is associated with a decrease in the number of police-reported neonaticides. The subsequent significantly decreasing numbers of anonymous births with an accompanying increase of neonaticides represents additional evidence for the effectiveness of the measure.
Directory of Open Access Journals (Sweden)
Muammar Arafat Yusmad
2015-12-01
Full Text Available he development of national banking nowadays are growing fast, competitive and integrative. One problem of Indonesian banking system related with practicing law arrangement which is a harmonization process toward legislations. The focus problems are: law arrangement in banking governance, the procedure of the law arrangement in achieving national bank industry which are healthy and dynamic. As intermediary institutions, bank should be in a healthy condition in order to gain public confidence and deserve to increase national economic growth. Based on the conceptual discussion, obtained arguments are: (1 The law arrangement of national banking should be done coodinately between Otoritas Jasa Keuangan (OJK and Bank Indonesia (BI; (2 Procedure of law arrangement according to the function and authority of OJK and BI which the urgent subjects are to avoid conflict of norm, overlapping policies and limited validity of norm of the law case which happen and will be happen; (3 banking law arrangement include bank arrangement and supervision system, strengthening internal condition of the bank, empowering and protecting consumer with complaints mechanism and follow-up which are clear and measurable.
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.
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.
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)
Elsays, Mostafa A.; Naguib Aly, M.; Badawi, Alya A.
2009-01-01
In this paper, the Particle Swarm Optimization (PSO) algorithm is modified to deal with Multiobjective Optimization Problems (MOPs). A mathematical model for predicting the dynamic response of the H. B. Robinson nuclear power plant, which represents an Initial Value Problem (IVP) of Ordinary Differential Equations (ODEs), is solved using Runge-Kutta formula. The resulted data values are represented as a system of nonlinear algebraic equations by interpolation schemes for data fitting. This system of fitted nonlinear algebraic equations represents a nonlinear multiobjective optimization problem. A Multiobjective Particle Swarm Optimizer (MOPSO) which is based on the Pareto optimality concept is developed and applied to maximize the above mentioned problem. Results show that MOPSO efficiently cope with the problem and finds multiple Pareto optimal solutions. (orig.)
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)
Numerical static state feedback laws for closed-loop singular optimal control
Graaf, de S.C.; Stigter, J.D.; Straten, van G.
2005-01-01
Singular and non-singular control trajectories of agricultural and (bio) chemical processes may need to be recalculated from time to time for use in closed-loop optimal control, because of unforeseen changes in state values and noise. This is time consuming. As an alternative, in this paper,
Lan, C. Edward; Ge, Fuying
1989-01-01
Control system design for general nonlinear flight dynamic models is considered through numerical simulation. The design is accomplished through a numerical optimizer coupled with analysis of flight dynamic equations. The general flight dynamic equations are numerically integrated and dynamic characteristics are then identified from the dynamic response. The design variables are determined iteratively by the optimizer to optimize a prescribed objective function which is related to desired dynamic characteristics. Generality of the method allows nonlinear effects to aerodynamics and dynamic coupling to be considered in the design process. To demonstrate the method, nonlinear simulation models for an F-5A and an F-16 configurations are used to design dampers to satisfy specifications on flying qualities and control systems to prevent departure. The results indicate that the present method is simple in formulation and effective in satisfying the design objectives.
Macroscopic law of conservation revealed in the population dynamics of Toll-like receptor signaling
Directory of Open Access Journals (Sweden)
Selvarajoo Kumar
2011-04-01
Full Text Available Abstract Stimulating the receptors of a single cell generates stochastic intracellular signaling. The fluctuating response has been attributed to the low abundance of signaling molecules and the spatio-temporal effects of diffusion and crowding. At population level, however, cells are able to execute well-defined deterministic biological processes such as growth, division, differentiation and immune response. These data reflect biology as a system possessing microscopic and macroscopic dynamics. This commentary discusses the average population response of the Toll-like receptor (TLR 3 and 4 signaling. Without requiring detailed experimental data, linear response equations together with the fundamental law of information conservation have been used to decipher novel network features such as unknown intermediates, processes and cross-talk mechanisms. For single cell response, however, such simplicity seems far from reality. Thus, as observed in any other complex systems, biology can be considered to possess order and disorder, inheriting a mixture of predictable population level and unpredictable single cell outcomes.
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
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.
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.
The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model
Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan
2016-05-01
Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.
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.
Dynamic optimization of dead-end membrane filtration
Blankert, B.; Betlem, Bernardus H.L.; Roffel, B.; Marquardt, Wolfgang; Pantelides, Costas
2006-01-01
An operating strategy aimed at minimizing the energy consumption during the filtration phase of dead-end membrane filtration has been formulated. A method allowing fast calculation of trajectories is used to allow incorporation in a hierarchical optimization scheme. The optimal trajectory can be
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.
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...
Computing the optimal path in stochastic dynamical systems
International Nuclear Information System (INIS)
Bauver, Martha; Forgoston, Eric; Billings, Lora
2016-01-01
In stochastic systems, one is often interested in finding the optimal path that maximizes the probability of escape from a metastable state or of switching between metastable states. Even for simple systems, it may be impossible to find an analytic form of the optimal path, and in high-dimensional systems, this is almost always the case. In this article, we formulate a constructive methodology that is used to compute the optimal path numerically. The method utilizes finite-time Lyapunov exponents, statistical selection criteria, and a Newton-based iterative minimizing scheme. The method is applied to four examples. The first example is a two-dimensional system that describes a single population with internal noise. This model has an analytical solution for the optimal path. The numerical solution found using our computational method agrees well with the analytical result. The second example is a more complicated four-dimensional system where our numerical method must be used to find the optimal path. The third example, although a seemingly simple two-dimensional system, demonstrates the success of our method in finding the optimal path where other numerical methods are known to fail. In the fourth example, the optimal path lies in six-dimensional space and demonstrates the power of our method in computing paths in higher-dimensional spaces.
Dynamic evaluation of seismic hazard and risks based on the Unified Scaling Law for Earthquakes
Kossobokov, V. G.; Nekrasova, A.
2016-12-01
We continue applying the general concept of seismic risk analysis in a number of seismic regions worldwide by constructing seismic hazard maps based on the Unified Scaling Law for Earthquakes (USLE), i.e. log N(M,L) = A + B•(6 - M) + C•log L, where N(M,L) is the expected annual number of earthquakes of a certain magnitude M within an seismically prone area of linear dimension L, A characterizes the average annual rate of strong (M = 6) earthquakes, B determines the balance between magnitude ranges, and C estimates the fractal dimension of seismic locus in projection to the Earth surface. The parameters A, B, and C of USLE are used to assess, first, the expected maximum magnitude in a time interval at a seismically prone cell of a uniform grid that cover the region of interest, and then the corresponding expected ground shaking parameters. After a rigorous testing against the available seismic evidences in the past (e.g., the historically reported macro-seismic intensity or paleo data), such a seismic hazard map is used to generate maps of specific earthquake risks for population, cities, and infrastructures. The hazard maps for a given territory change dramatically, when the methodology is applied to a certain size moving time window, e.g. about a decade long for an intermediate-term regional assessment or exponentially increasing intervals for a daily local strong aftershock forecasting. The of dynamical seismic hazard and risks assessment is illustrated by applications to the territory of Greater Caucasus and Crimea and the two-year series of aftershocks of the 11 October 2008 Kurchaloy, Chechnya earthquake which case-history appears to be encouraging for further systematic testing as potential short-term forecasting tool.
Rule of Law Dynamics in an Era of International and Transnational Governance
Zürn, M.; Nollkaemper, A.; Peerenboom, R.
2011-01-01
The international and transnational nature of modern governance presents major challenges for the rule of law promotion agenda, at a time when the less than stellar results of traditional state-oriented rule of law promotion have led to increased doubts about the wisdom and feasibility of the
Language Management Theory as a Basis for the Dynamic Concept of EU Language Law
Dovalil, Vít
2015-01-01
Language law is a tool used to manage problems of linguistic diversity in the EU. The paper analyzes the processes in which language law is found in the discursive practice of agents addressing the Court of Justice of the European Union with their language problems. The theoretical-methodological basis for the research is Language Management…
Energy Technology Data Exchange (ETDEWEB)
Rana, A.; Ravichandran, R. [School of Mechanical and Aerospace Engineering, Gyeongsang National University, Jinju, Gyeongnam 52828 (Korea, Republic of); Park, J. H.; Myong, R. S., E-mail: myong@gnu.ac.kr [School of Mechanical and Aerospace Engineering, Gyeongsang National University, Jinju, Gyeongnam 52828 (Korea, Republic of); Research Center for Aircraft Parts Technology, Gyeongsang National University, Jinju, Gyeongnam 52828 (Korea, Republic of)
2016-08-15
The second-order non-Navier-Fourier constitutive laws, expressed in a compact algebraic mathematical form, were validated for the force-driven Poiseuille gas flow by the deterministic atomic-level microscopic molecular dynamics (MD). Emphasis is placed on how completely different methods (a second-order continuum macroscopic theory based on the kinetic Boltzmann equation, the probabilistic mesoscopic direct simulation Monte Carlo, and, in particular, the deterministic microscopic MD) describe the non-classical physics, and whether the second-order non-Navier-Fourier constitutive laws derived from the continuum theory can be validated using MD solutions for the viscous stress and heat flux calculated directly from the molecular data using the statistical method. Peculiar behaviors (non-uniform tangent pressure profile and exotic instantaneous heat conduction from cold to hot [R. S. Myong, “A full analytical solution for the force-driven compressible Poiseuille gas flow based on a nonlinear coupled constitutive relation,” Phys. Fluids 23(1), 012002 (2011)]) were re-examined using atomic-level MD results. It was shown that all three results were in strong qualitative agreement with each other, implying that the second-order non-Navier-Fourier laws are indeed physically legitimate in the transition regime. Furthermore, it was shown that the non-Navier-Fourier constitutive laws are essential for describing non-zero normal stress and tangential heat flux, while the classical and non-classical laws remain similar for shear stress and normal heat flux.
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...
Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems
Directory of Open Access Journals (Sweden)
Sergei A. Soldatenko
2017-01-01
Full Text Available The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.
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 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.
Optimal Pricing Strategies for New Products in Dynamic Oligopolies
Engelbert Dockner; Steffen Jørgensen
1988-01-01
This paper deals with the determination of optimal pricing policies for firms in oligopolistic markets. The problem is studied as a differential game and optimal pricing policies are established as Nash open-loop controls. Cost learning effects are assumed such that unit costs are decreasing with cumulative output. Discounting of future profits is also taken into consideration. Initially, the problem is addressed in a general framework, and we proceed to study some specific cases that are rel...
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)
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.
Dynamic optimization and robust explicit model predictive control of hydrogen storage tank
Panos, C.; Kouramas, K.I.; Georgiadis, M.C.; Pistikopoulos, E.N.
2010-01-01
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.
Optimizing Dynamic Class Composition in a Statically Typed Language
DEFF Research Database (Denmark)
Nielsen, Anders Bach; Ernst, Erik
2008-01-01
-enable a type safe treatment of classifiers and their associated types and instances, even in the case where classifiers are created dynamically. This opens the opportunity to make dynamic class computations available as an integrated part of the language semantics. The language gbeta is an example where...... 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....
International Nuclear Information System (INIS)
Yoshino, Hironori; Wada, Kenji; Horinaka, Hiromichi; Cho, Yoshio; Umeda, Tokuo; Osawa, Masahiko.
1995-01-01
The Lambert-Beer law holding for pulsed lights transmitted through a scattering medium was examined using a streak camera. The Lambert-Beer law dynamic range is found to be limited by floor levels that are caused by scattered photons and are controllable by the use of a temporal gate on the transmitted pulse. The dynamic range improvement obtained for a scattering medium of 2.8 cm -1 scattering coefficient of a thickness of 80 mm by a temporal gate of 60 ps was as much as 50 dB and the Lambert-Beer law dynamic rang reached to 140 dB. (author)
Optimal Route Searching with Multiple Dynamical Constraints—A Geometric Algebra Approach
Directory of Open Access Journals (Sweden)
Dongshuang Li
2018-05-01
Full Text Available The process of searching for a dynamic constrained optimal path has received increasing attention in traffic planning, evacuation, and personalized or collaborative traffic service. As most existing multiple constrained optimal path (MCOP methods cannot search for a path given various types of constraints that dynamically change during the search, few approaches for dynamic multiple constrained optimal path (DMCOP with type II dynamics are available for practical use. In this study, we develop a method to solve the DMCOP problem with type II dynamics based on the unification of various types of constraints under a geometric algebra (GA framework. In our method, the network topology and three different types of constraints are represented by using algebraic base coding. With a parameterized optimization of the MCOP algorithm based on a greedy search strategy under the generation-refinement paradigm, this algorithm is found to accurately support the discovery of optimal paths as the constraints of numerical values, nodes, and route structure types are dynamically added to the network. The algorithm was tested with simulated cases of optimal tourism route searches in China’s road networks with various combinations of constraints. The case study indicates that our algorithm can not only solve the DMCOP with different types of constraints but also use constraints to speed up the route filtering.
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)
Bang Chul Jung
2017-07-01
Full Text Available We introduce a distributed protocol to achieve multiuser diversity in a multicell multiple-input multiple-output (MIMO uplink network, referred to as a MIMO interfering multiple-access channel (IMAC. Assuming both no information exchange among base stations (BS and local channel state information at the transmitters for the MIMO IMAC, we propose a joint beamforming and user scheduling protocol, and then show that the proposed protocol can achieve the optimal multiuser diversity gain, i.e., KMlog(SNRlog N, as long as the number of mobile stations (MSs in a cell, N, scales faster than SNR K M − L 1 − ϵ for a small constant ϵ > 0, where M, L, K, and SNR denote the number of receive antennas at each BS, the number of transmit antennas at each MS, the number of cells, and the signal-to-noise ratio, respectively. Our result indicates that multiuser diversity can be achieved in the presence of intra-cell and inter-cell interference even in a distributed fashion. As a result, vital information on how to design distributed algorithms in interference-limited cellular environments is provided.
Optimization of Algorithms Using Extensions of Dynamic Programming
AbouEisha, Hassan M.
2017-01-01
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
The Dynamics of Marriage Law and Custom in the United States
Directory of Open Access Journals (Sweden)
Elizabeth Ann Wilson Whetmore
2013-02-01
Full Text Available This article examines changes in marriage laws and related cultural norms and values in the United States across the last several decades, and discusses correlating worldview shifts. It appears that the “traditional” worldview produced earlier laws, cultural norms and values, and changes to these have corresponded with a cultural worldview shift, first into “modernism” and then towards “postmodernism.” The implications of these worldview shifts for ongoing change to marriage law and custom are also analyzed.
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)
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.
Dynamic programming for optimization of timber production and grazing in ponderosa pine
Kurt H. Riitters; J. Douglas Brodie; David W. Hann
1982-01-01
Dynamic programming procedures are presented for optimizing thinning and rotation of even-aged ponderosa pine by using the four descriptors: age, basal area, number of trees, and time since thinning. Because both timber yield and grazing yield are functions of stand density, the two outputs-forage and timber-can both be optimized. The soil expectation values for single...
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...
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.
The Value of Optimization in Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta
N.A.H. Agatz (Niels); A. Erera (Alan); M.W.P. Savelsbergh (Martin); X. Wang (Xing)
2010-01-01
textabstractSmartphone technology enables dynamic ride-sharing systems that bring together people with similar itineraries and time schedules to share rides on short-notice. This paper considers the problem of matching drivers and riders in this dynamic setting. We develop optimization-based
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
Energy-Aware Routing Optimization in Dynamic GMPLS Controlled Optical Networks
DEFF Research Database (Denmark)
Wang, Jiayuan; Ricciardi, Sergio; Fagertun, Anna Manolova
2012-01-01
In this paper, routing optimizations based on energy sources are proposed in dynamic GMPLS controlled optical networks. The influences of re-routing and load balancing factors on the algorithm are evaluated, with a focus on different re-routing thresholds. Results from dynamic network simulations...
Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei
2016-08-03
Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic.
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.
Multiple-Optimizing Dynamic Sensor Networks with MIMO Technology (PREPRINT)
2010-06-01
cluster edge is always d and never changes. A backbone is a rooted tree formed by cluster heads. The transmission distance for a backbone-edge...optimization considerations and algorithms,” IEEE Transactions on Mobile Computing, 2004. 15. T. Tang, M. Park, R. W. Heath, Jr. and Scott M. Nettles , “A
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
Optimal Charging of Electric Drive Vehicles: A Dynamic Programming Approach
DEFF Research Database (Denmark)
Delikaraoglou, Stefanos; Capion, Karsten Emil; Juul, Nina
2013-01-01
, therefore, we propose an ex ante vehicle aggregation approach. We illustrate the results in a Danish case study and find that, although optimal management of the vehicles does not allow for storage and day-to-day flexibility in the electricity system, the market provides incentive for intra-day flexibility....
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…
International Nuclear Information System (INIS)
Huang, Xiaobiao; Safranek, James
2014-01-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications
Energy Technology Data Exchange (ETDEWEB)
Huang, Xiaobiao, E-mail: xiahuang@slac.stanford.edu; Safranek, James
2014-09-01
Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.
Dynamic Aperture Optimization for Low Emittance Light Sources
Kramer, Stephen L
2005-01-01
State of the art low emittance light source lattices, require small bend angle dipole magnets and strong quadrupoles. This in turn creates large chromaticity and small value of dispersion in the lattice. To counter the high chromaticity strong sextupoles are required which limit the dynamic aperture. Traditional methods for expanding the dynamic aperture use harmonic sextupoles to counter the tune shift with amplitude. This has been successful up to now, but is non-deterministic and limited as the sextupole strength increases, driving higher order nonlinearities. We have taken a different approach that makes use of the tune flexibility of a TBA lattice to minimize the lowest order nonlinearities, freeing the harmonic sextupoles to counter the higher order nonlinearities. This procedure is being used to improve the nonlinear dynamics of the NSLS-II lattice.
An optimal dynamic interval preventive maintenance scheduling for series systems
International Nuclear Information System (INIS)
Gao, Yicong; Feng, Yixiong; Zhang, Zixian; Tan, Jianrong
2015-01-01
This paper studies preventive maintenance (PM) with dynamic interval for a multi-component system. Instead of equal interval, the time of PM period in the proposed dynamic interval model is not a fixed constant, which varies from interval-down to interval-up. It is helpful to reduce the outage loss on frequent repair parts and avoid lack of maintenance of the equipment by controlling the equipment maintenance frequency, when compared to a periodic PM scheme. According to the definition of dynamic interval, the reliability of system is analyzed from the failure mechanisms of its components and the different effects of non-periodic PM actions on the reliability of the components. Following the proposed model of reliability, a novel framework for solving the non-periodical PM schedule with dynamic interval based on the multi-objective genetic algorithm is proposed. The framework denotes the strategies include updating strategy, deleting strategy, inserting strategy and moving strategy, which is set to correct the invalid population individuals of the algorithm. The values of the dynamic interval and the selections of PM action for the components on every PM stage are determined by achieving a certain level of system availability with the minimum total PM-related cost. Finally, a typical rotary table system of NC machine tool is used as an example to describe the proposed method. - Highlights: • A non-periodic preventive maintenance scheduling model is proposed. • A framework for solving the non-periodical PM schedule problem is developed. • The interval of non-periodic PM is flexible and schedule can be better adjusted. • Dynamic interval leads to more efficient solutions than fixed interval does
Large Portfolio Risk Management and Optimal Portfolio Allocation with Dynamic Copulas
Thorsten Lehnert; Xisong Jin
2011-01-01
Previous research focuses on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, available dynamic models are not easily applied for 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 like Value at Ris...
Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications
International Nuclear Information System (INIS)
Bourgeois, F.; Labeau, P.E.
2001-01-01
On one hand, PSA results are increasingly used in decision making, system management and optimization of system design. On the other hand, when severe accidental transients are considered, dynamic reliability appears appropriate to account for the complex interaction between the transitions between hardware configurations, the operator behavior and the dynamic evolution of the system. This paper presents an exploratory work in which the estimation of the system unreliability in a dynamic context is coupled with an optimization algorithm to determine the 'best' safety policy. Because some reliability parameters are likely to be distributed, the cost function to be minimized turns out to be a random variable. Stochastic programming techniques are therefore envisioned to determine an optimal strategy. Monte Carlo simulation is used at all stages of the computations, from the estimation of the system unreliability to that of the stochastic quasi-gradient. The optimization algorithm is illustrated on a HNO 3 supply system
Topology optimization of continuum structure with dynamic constraints using mode identification
International Nuclear Information System (INIS)
Li, Jianhongyu; Chen, Shenyan; Huang, Hai
2015-01-01
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.
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.
Dynamic thread assignment in web server performance optimization
van der Weij, W.; Bhulai, S.; van der Mei, R.D.
2009-01-01
Popular web sites are expected to handle huge number of requests concurrently within a reasonable time frame. The performance of these web sites is largely dependent on effective thread management of their web servers. Although the implementation of static and dynamic thread policies is common
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 Modeling, Optimization, and Advanced Control for Large Scale Biorefineries
DEFF Research Database (Denmark)
Prunescu, Remus Mihail
with a complex conversion route. Computational fluid dynamics is used to model transport phenomena in large reactors capturing tank profiles, and delays due to plug flows. This work publishes for the first time demonstration scale real data for validation showing that the model library is suitable...
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...
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
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.
Dynamics of underactuated multibody systems modeling, control and optimal design
Seifried, Robert
2014-01-01
Underactuated multibody systems are intriguing mechatronic systems, as they possess fewer control inputs than degrees of freedom. Some examples are modern light-weight flexible robots and articulated manipulators with passive joints. This book investigates such underactuated multibody systems from an integrated perspective. This includes all major steps from the modeling of rigid and flexible multibody systems, through nonlinear control theory, to optimal system design. The underlying theories and techniques from these different fields are presented using a self-contained and unified approach and notation system. Subsequently, the book focuses on applications to large multibody systems with multiple degrees of freedom, which require a combination of symbolical and numerical procedures. Finally, an integrated, optimization-based design procedure is proposed, whereby both structural and control design are considered concurrently. Each chapter is supplemented by illustrated examples.
Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.
Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha
2017-09-01
Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.
Optimization of CW Fiber Lasers With Strong Nonlinear Cavity Dynamics
Shtyrina, O. V.; Efremov, S. A.; Yarutkina, I. A.; Skidin, A. S.; Fedoruk, M. P.
2018-04-01
In present work the equation for the saturated gain is derived from one-level gain equations describing the energy evolution inside the laser cavity. It is shown how to derive the parameters of the mathematical model from the experimental results. The numerically-estimated energy and spectrum of the signal are in good agreement with the experiment. Also, the optimization of the output energy is performed for a given set of model parameters.
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.
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.
International Nuclear Information System (INIS)
Sarazhinskii, D S
2004-01-01
We consider a dynamical system generated by a shift in the space of finite-valued one-sided sequences. We study spectral properties of Perron-Frobenius operators associated with this system, whose potentials on the number of the term of the sequence have power-law dependence. Using these operators, we construct a family of equilibrium probability measures in the phase space having the property of power-law mixing. For these measures we prove a central limit theorem for functions in phase space and a Cramer-type theorem for the probabilities of large deviations. Similar results for the significantly simpler case of exponential decay in the dependence of the potentials on the number of the term of the sequence were previously obtained by the author.
On the equivalent static loads approach for dynamic response structural optimization
DEFF Research Database (Denmark)
Stolpe, Mathias
2014-01-01
The equivalent static loads algorithm is an increasingly popular approach to solve dynamic response structural optimization problems. The algorithm is based on solving a sequence of related static response structural optimization problems with the same objective and constraint functions...... as the original problem. The optimization theoretical foundation of the algorithm is mainly developed in Park and Kang (J Optim Theory Appl 118(1):191–200, 2003). In that article it is shown, for a certain class of problems, that if the equivalent static loads algorithm terminates then the KKT conditions...
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...
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)
An Approximate Dynamic Programming Mode for Optimal MEDEVAC Dispatching
2015-03-26
over the myopic policy. This indicates the ADP policy is efficiently managing resources by 28 not immediately sending the nearest available MEDEVAC...DISPATCHING THESIS Presented to the Faculty Department of Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology...medical evacuation (MEDEVAC) dispatch policies. To solve the MDP, we apply an ap- proximate dynamic programming (ADP) technique. The problem of deciding
Role of optimization in the human dynamics of task execution
Cajueiro, Daniel O.; Maldonado, Wilfredo L.
2008-03-01
In order to explain the empirical evidence that the dynamics of human activity may not be well modeled by Poisson processes, a model based on queuing processes was built in the literature [A. L. Barabasi, Nature (London) 435, 207 (2005)]. The main assumption behind that model is that people execute their tasks based on a protocol that first executes the high priority item. In this context, the purpose of this paper is to analyze the validity of that hypothesis assuming that people are rational agents that make their decisions in order to minimize the cost of keeping nonexecuted tasks on the list. Therefore, we build and analytically solve a dynamic programming model with two priority types of tasks and show that the validity of this hypothesis depends strongly on the structure of the instantaneous costs that a person has to face if a given task is kept on the list for more than one period. Moreover, one interesting finding is that in one of the situations the protocol used to execute the tasks generates complex one-dimensional dynamics.
On the dynamics of the power law inflation due to an exponential potential
International Nuclear Information System (INIS)
Yokohama, Jun'ichi; Maeda, Kei-ichi; Tokyo Univ.
1988-01-01
The power law inflationary universe model induced by a scalar field with an exponential potential is studied. A dissipation term due to particle creation is introduced in the inflation's classical equation of motion. It is shown that the power index of the inflation increases prominently with an adequate viscosity. Consequently, even in theories with a rather steep exponential such as some supergravity or superstring models, it turns out that a 'realistic' power law inflation (with a power index p> or approx.10) is possible. (orig.)
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.
Lu, Lihao; Zhang, Jianxiong; Tang, Wansheng
2016-04-01
An inventory system for perishable items with limited replenishment capacity is introduced in this paper. The demand rate depends on the stock quantity displayed in the store as well as the sales price. With the goal to realise profit maximisation, an optimisation problem is addressed to seek for the optimal joint dynamic pricing and replenishment policy which is obtained by solving the optimisation problem with Pontryagin's maximum principle. A joint mixed policy, in which the sales price is a static decision variable and the replenishment rate remains to be a dynamic decision variable, is presented to compare with the joint dynamic policy. Numerical results demonstrate the advantages of the joint dynamic one, and further show the effects of different system parameters on the optimal joint dynamic policy and the maximal total profit.
Optimizing Grippers for Compensating Pose Uncertainties by Dynamic Simulation
DEFF Research Database (Denmark)
Wolniakowski, Adam; Kramberger, Aljaž; Gams, Andrej
2017-01-01
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...
Time-limited optimal dynamics beyond the Quantum Speed Limit
DEFF Research Database (Denmark)
Gajdacz, Miroslav; Das, Kunal K.; Arlt, Jan
2015-01-01
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......-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...
Directory of Open Access Journals (Sweden)
Wang Qing
2015-04-01
Full Text Available In order to alleviate the dynamic stall effects in helicopter rotor, the sequential quadratic programming (SQP method is employed to optimize the characteristics of airfoil under dynamic stall conditions based on the SC1095 airfoil. The geometry of airfoil is parameterized by the class-shape-transformation (CST method, and the C-topology body-fitted mesh is then automatically generated around the airfoil by solving the Poisson equations. Based on the grid generation technology, the unsteady Reynolds-averaged Navier-Stokes (RANS equations are chosen as the governing equations for predicting airfoil flow field and the highly-efficient implicit scheme of lower–upper symmetric Gauss–Seidel (LU-SGS is adopted for temporal discretization. To capture the dynamic stall phenomenon of the rotor more accurately, the Spalart–Allmaras turbulence model is employed to close the RANS equations. The optimized airfoil with a larger leading edge radius and camber is obtained. The leading edge vortex and trailing edge separation of the optimized airfoil under unsteady conditions are obviously weakened, and the dynamic stall characteristics of optimized airfoil at different Mach numbers, reduced frequencies and angles of attack are also obviously improved compared with the baseline SC1095 airfoil. It is demonstrated that the optimized method is effective and the optimized airfoil is suitable as the helicopter rotor airfoil.
Mathematical analysis of the global dynamics of a power law model ...
African Journals Online (AJOL)
We analyze a mathematical power law model that describes HIV infection of CD4+ T cells. We report that the number of critical points depends on , where is a positive integer. We show that for any positive integer the infection – free equilibrium is asymptotically stable if the reproduction number R0 1.
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.
A Runtime Analysis of Parallel Evolutionary Algorithms in Dynamic Optimization
DEFF Research Database (Denmark)
Lissovoi, Andrei; Witt, Carsten
2017-01-01
A simple island model with (Formula presented.) islands and migration occurring after every (Formula presented.) iterations is studied on the dynamic fitness function Maze. This model is equivalent to a (Formula presented.) EA if (Formula presented.), i. e., migration occurs during every iteratio.......). The relationship of (Formula presented.), and the ability of the island model to track the optimum is then investigated more closely. Finally, experiments are performed to supplement the asymptotic results, and investigate the impact of the migration topology.......A simple island model with (Formula presented.) islands and migration occurring after every (Formula presented.) iterations is studied on the dynamic fitness function Maze. This model is equivalent to a (Formula presented.) EA if (Formula presented.), i. e., migration occurs during every iteration....... It is proved that even for an increased offspring population size up to (Formula presented.), the (Formula presented.) EA is still not able to track the optimum of Maze. If the migration interval is chosen carefully, the algorithm is able to track the optimum even for logarithmic (Formula presented...
Cluster Optimization and Parallelization of Simulations with Dynamically Adaptive Grids
Schreiber, Martin; Weinzierl, Tobias; Bungartz, Hans-Joachim
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.
Discrete Adjoint-Based Design Optimization of Unsteady Turbulent Flows on Dynamic Unstructured Grids
Nielsen, Eric J.; Diskin, Boris; Yamaleev, Nail K.
2009-01-01
An adjoint-based methodology for design optimization of unsteady turbulent flows on dynamic unstructured grids is described. The implementation relies on an existing unsteady three-dimensional unstructured grid solver capable of dynamic mesh simulations and discrete adjoint capabilities previously developed for steady flows. The discrete equations for the primal and adjoint systems are presented for the backward-difference family of time-integration schemes on both static and dynamic grids. The consistency of sensitivity derivatives is established via comparisons with complex-variable computations. The current work is believed to be the first verified implementation of an adjoint-based optimization methodology for the true time-dependent formulation of the Navier-Stokes equations in a practical computational code. Large-scale shape optimizations are demonstrated for turbulent flows over a tiltrotor geometry and a simulated aeroelastic motion of a fighter jet.
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.
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
OPTIMIZING THE DYNAMIC APERTURE FOR TRIPLE BEND ACHROMATIC LATTICES
International Nuclear Information System (INIS)
KRAMER, S.L.; BENGTSSON, J.
2006-01-01
The Triple Bend Achromatic (TBA) lattice has the potential for lower natural emittance per period than the Double Bend Achromatic (DBA) lattice for high brightness light sources. However, the DBA has been chosen for 3rd generation light sources more often due to the higher number of undulator straight section available for a comparable emittance. The TBA has considerable flexibility in linear optics tuning while maintaining this emittance advantage. We have used the tune and chromaticity flexibility of a TBA lattice to minimize the lowest order nonlinearities to implement a 3rd order achromatic tune, while maintaining a constant emittance. This frees the geometric sextupoles to counter the higher order nonlinearities. This procedure is being used to improve the nonlinear dynamics of the TBA as a proposed lattice for NSLS-II facility. The flexibility of the TBA lattice will also provide for future upgrade capabilities of the beam parameters
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...... to λ=O(n1-ε), the (1+λ) EA is still not able to track the optimum of Maze. If the migration interval is increased, the algorithm is able to track the optimum even for logarithmic λ. Finally, the relationship of τ, λ, and the ability of the island model to track the optimum is investigated more closely....
Optimized chaotic Brillouin dynamic grating with filtered optical feedback.
Zhang, Jianzhong; Li, Zhuping; Wu, Yuan; Zhang, Mingjiang; Liu, Yi; Li, Mengwen
2018-01-16
Chaotic Brillouin dynamic gratings (BDGs) have special advantages such as the creation of single, permanent and localized BDG. However, the periodic signals induced by conventional optical feedback (COF) in chaotic semiconductor lasers can lead to the generation of spurious BDGs, which will limit the application of chaotic BDGs. In this paper, filtered optical feedback (FOF) is proposed to eliminate spurious BDGs. By controlling the spectral width of the optical filter and its detuning from the laser frequency, semiconductor lasers with FOF operate in the suppression region of the time-delay signature, and chaotic outputs serving as pump waves are then utilized to generate the chaotic BDG in a polarization maintaining fiber. Through comparative analysis of the COF and FOF schemes, it has been demonstrated that spurious BDGs are effectively eliminated and that the reflection characterization of the chaotic BDG is improved. The influence of FOF on the reflection and gain spectra of the chaotic BDG is analyzed as well.
Size optimization and dynamics studies for a heliac stellarators reactor
International Nuclear Information System (INIS)
Perez-Navarro, A.; Fraguas, A.L.; Ochando, M.A.; Garcia Gonzalo, L.
1995-01-01
Design studies for a stellarator reactor based on a heliac configuration have been addressed to determine the minimum size requirements and operational techniques for plasma start-up and run-down. Assuming constraints derived from the available technologies and plasma parameter limitations, a device with a major radius of 15 m and a plasma radius of 2 m is obtained, for a magnetic field of 5 T and a power output around 1 GW(e). A coil system with enough space for blanket and shielding has been defined. Finally it is proved that by a continuous use of a modest amount of auxiliary power, all dynamical process of the plant operation can be eased. 13 refs
International Nuclear Information System (INIS)
Breuer, R.A.; Rudolph, E.
1982-01-01
The force between two well-separated bodies is calculated in a fully dynamic system of two extended bodies up to and including the second post-Newtonian approximation (PNA). The iteration procedure as formulated by Anderson and Decanio is used in a version whose divergences have been pushed to the third PNA. The following are shown: (i) The force law assumes the ''Newtonian form'' if a second approximation in 1/(separation of the bodies) is made; (ii) the mass terms appearing in the force law are the (Tolman) masses of the individual bodies expanded up the second PNA; the internal masses equal the (passive and active) gravitational masses of the bodies in order considered; they are all constants of the motion; (iii) the self-fields of the bodies vanish in the second PNA; hence there is no Nordvedt effect in the second PNA; (iv) the compactness of the bodies, i.e., (gravitational radius)/(body size), does not appear in the force law; only the relation between mass and the matter variables is changed in the PNA as compared with the corresponding Newtonian result. (author)
Nonlinear Dynamic Analysis and Optimization of Closed-Form Planetary Gear System
Directory of Open Access Journals (Sweden)
Qilin Huang
2013-01-01
Full Text Available A nonlinear purely rotational dynamic model of a multistage closed-form planetary gear set formed by two simple planetary stages is proposed in this study. The model includes time-varying mesh stiffness, excitation fluctuation and gear backlash nonlinearities. The nonlinear differential equations of motion are solved numerically using variable step-size Runge-Kutta. In order to obtain function expression of optimization objective, the nonlinear differential equations of motion are solved analytically using harmonic balance method (HBM. Based on the analytical solution of dynamic equations, the optimization mathematical model which aims at minimizing the vibration displacement of the low-speed carrier and the total mass of the gear transmission system is established. The optimization toolbox in MATLAB program is adopted to obtain the optimal solution. A case is studied to demonstrate the effectiveness of the dynamic model and the optimization method. The results show that the dynamic properties of the closed-form planetary gear transmission system have been improved and the total mass of the gear set has been decreased significantly.
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
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.
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.
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.
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...
Dynamic Portfolio Optimization with Transaction Costs and State-Dependent Drift
DEFF Research Database (Denmark)
Palczewski, Jan; Poulsen, Rolf; Schenk-Hoppe, Klaus Reiner
2015-01-01
The problem of dynamic portfolio choice with transaction costs is often addressed by constructing a Markov Chain approximation of the continuous time price processes. Using this approximation, we present an efficient numerical method to determine optimal portfolio strategies under time- and state......-dependent drift and proportional transaction costs. This scenario arises when investors have behavioral biases or the actual drift is unknown and needs to be estimated. Our numerical method solves dynamic optimal portfolio problems with an exponential utility function for time-horizons of up to 40 years....... It is applied to measure the value of information and the loss from transaction costs using the indifference principle....
Optimal dynamic premium control in non-life insurance. Maximizing dividend pay-outs
DEFF Research Database (Denmark)
Højgaard, Bjarne
2002-01-01
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...... 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...
Dynamic verification of newton's law and the principal limits in measuring intermediate-range forces
International Nuclear Information System (INIS)
Kolosnitsyn, N.I.; Luo Jun; Melnikov, V.N.
1992-01-01
According to the controversial results of recent experiments for fifth force, a classification of all possible types of theories leading to non-Newtonian forces is presented. The theoretical analysis shows that if the interaction potential differs from the Newton's law the interactions of macro-and micro-bodies are in general distinguishable. The calculation also shows that Long's result can be improved by several orders if the new method proposed is used
The Dynamics of Power laws: Fitness and Aging in Preferential Attachment Trees
Garavaglia, Alessandro; van der Hofstad, Remco; Woeginger, Gerhard
2017-09-01
Continuous-time branching processes describe the evolution of a population whose individuals generate a random number of children according to a birth process. Such branching processes can be used to understand preferential attachment models in which the birth rates are linear functions. We are motivated by citation networks, where power-law citation counts are observed as well as aging in the citation patterns. To model this, we introduce fitness and age-dependence in these birth processes. The multiplicative fitness moderates the rate at which children are born, while the aging is integrable, so that individuals receives a finite number of children in their lifetime. We show the existence of a limiting degree distribution for such processes. In the preferential attachment case, where fitness and aging are absent, this limiting degree distribution is known to have power-law tails. We show that the limiting degree distribution has exponential tails for bounded fitnesses in the presence of integrable aging, while the power-law tail is restored when integrable aging is combined with fitness with unbounded support with at most exponential tails. In the absence of integrable aging, such processes are explosive.
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...
Energy Technology Data Exchange (ETDEWEB)
Jawad, Abdul [COMSATS Institute of Information Technology, Department of Mathematics, Lahore (Pakistan); Videla, Nelson [FCFM, Universidad de Chile, Departamento de Fisica, Santiago (Chile); Gulshan, Faiza [Lahore Leads University, Department of Mathematics, Lahore (Pakistan)
2017-05-15
In the present work, we study the consequences of considering a new family of single-field inflation models, called power-law plateau inflation, in the warm inflation framework. We consider the inflationary expansion is driven by a standard scalar field with a decay ratio Γ having a generic power-law dependence with the scalar field φ and the temperature of the thermal bath T given by Γ(φ,T) = C{sub φ}(T{sup a})/(φ{sup a-1}). Assuming that our model evolves according to the strong dissipative regime, we study the background and perturbative dynamics, obtaining the most relevant inflationary observable as the scalar power spectrum, the scalar spectral index and its running and the tensor-to-scalar ratio. The free parameters characterizing our model are constrained by considering the essential condition for warm inflation, the conditions for the model evolves according to the strong dissipative regime and the 2015 Planck results through the n{sub s}-r plane. For completeness, we study the predictions in the n{sub s}-dn{sub s}/d ln k plane. The model is consistent with a strong dissipative dynamics and predicts values for the tensor-to-scalar ratio and for the running of the scalar spectral index consistent with current bounds imposed by Planck and we conclude that the model is viable. (orig.)
International Nuclear Information System (INIS)
Jawad, Abdul; Videla, Nelson; Gulshan, Faiza
2017-01-01
In the present work, we study the consequences of considering a new family of single-field inflation models, called power-law plateau inflation, in the warm inflation framework. We consider the inflationary expansion is driven by a standard scalar field with a decay ratio Γ having a generic power-law dependence with the scalar field φ and the temperature of the thermal bath T given by Γ(φ,T) = C_φ(T"a)/(φ"a"-"1). Assuming that our model evolves according to the strong dissipative regime, we study the background and perturbative dynamics, obtaining the most relevant inflationary observable as the scalar power spectrum, the scalar spectral index and its running and the tensor-to-scalar ratio. The free parameters characterizing our model are constrained by considering the essential condition for warm inflation, the conditions for the model evolves according to the strong dissipative regime and the 2015 Planck results through the n_s-r plane. For completeness, we study the predictions in the n_s-dn_s/d ln k plane. The model is consistent with a strong dissipative dynamics and predicts values for the tensor-to-scalar ratio and for the running of the scalar spectral index consistent with current bounds imposed by Planck and we conclude that the model is viable. (orig.)
An optimal maintenance policy for machine replacement problem using dynamic programming
Mohsen Sadegh Amalnik; Morteza Pourgharibshahi
2017-01-01
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 inc...
Emittance compensation with dynamically optimized photoelectron beam profiles
Energy Technology Data Exchange (ETDEWEB)
Rosenzweig, J.B. [Department of Physics and Astronomy, UCLA, 405 Hilgard Avenue, Los Angeles, CA 90095 (United States)]. E-mail: rosen@physics.ucla.edu; Cook, A.M. [Department of Physics and Astronomy, UCLA, 405 Hilgard Avenue, Los Angeles, CA 90095 (United States); England, R.J. [Department of Physics and Astronomy, UCLA, 405 Hilgard Avenue, Los Angeles, CA 90095 (United States); Dunning, M. [Department of Physics and Astronomy, UCLA, 405 Hilgard Avenue, Los Angeles, CA 90095 (United States); Anderson, S.G. [Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA 94550 (United States); Ferrario, Massimo [Istituto Nazionale di Fisica Nucleare, Laboratori Nazionale di Frascati, Via E. Fermi 41, Frascati, Rome (Italy)
2006-02-01
Much of the theory and experimentation concerning creation of a high-brightness electron beam from a photocathode, and then applying emittance compensation techniques, assumes that one must strive for a uniform density electron beam, having a cylindrical shape. On the other hand, this shape has large nonlinearities in the space-charge field profiles near the beam's longitudinal extrema. These nonlinearities are known to produce both transverse and longitudinal emittance growth. On the other hand, it has recently been shown by Luiten that by illuminating the cathode with an ultra-short laser pulse of appropriate transverse profile, a uniform density, ellipsoidally shaped bunch is dynamically formed, which then has linear space-charge fields in all dimensions inside of the bunch. We study here this process, and its marriage to the standard emittance compensation scenario that is implemented in most recent photoinjectors. It is seen that the two processes are compatible, with simulations indicating a very high brightness beam can be obtained. The robustness of this scheme to systematic errors is examined. Prospects for experimental tests of this scheme are discussed.
Emittance compensation with dynamically optimized photoelectron beam profiles
International Nuclear Information System (INIS)
Rosenzweig, J.B.; Cook, A.M.; England, R.J.; Dunning, M.; Anderson, S.G.; Ferrario, Massimo
2006-01-01
Much of the theory and experimentation concerning creation of a high-brightness electron beam from a photocathode, and then applying emittance compensation techniques, assumes that one must strive for a uniform density electron beam, having a cylindrical shape. On the other hand, this shape has large nonlinearities in the space-charge field profiles near the beam's longitudinal extrema. These nonlinearities are known to produce both transverse and longitudinal emittance growth. On the other hand, it has recently been shown by Luiten that by illuminating the cathode with an ultra-short laser pulse of appropriate transverse profile, a uniform density, ellipsoidally shaped bunch is dynamically formed, which then has linear space-charge fields in all dimensions inside of the bunch. We study here this process, and its marriage to the standard emittance compensation scenario that is implemented in most recent photoinjectors. It is seen that the two processes are compatible, with simulations indicating a very high brightness beam can be obtained. The robustness of this scheme to systematic errors is examined. Prospects for experimental tests of this scheme are discussed
International Nuclear Information System (INIS)
Porteus, E.
1982-01-01
The study of infinite-horizon nonstationary dynamic programs using the operator approach is continued. The point of view here differs slightly from that taken by others, in that Denardo's local income function is not used as a starting point. Infinite-horizon values are defined as limits of finite-horizon values, as the horizons get long. Two important conditions of an earlier paper are weakened, yet the optimality equations, the optimality criterion, and the existence of optimal ''structured'' strategies are still obtained
Energy Technology Data Exchange (ETDEWEB)
Kim, Jong Woo; Choi, Go Bong; Lee, Jong Min [Seoul National University, Seoul (Korea, Republic of); Suh, Jung Chul [Samchully Corporation, Seoul (Korea, Republic of)
2016-01-15
This paper proposes a Markov decision process (MDP) based approach to derive an optimal schedule of maintenance, rehabilitation and replacement of the water main system. The scheduling problem utilizes auxiliary information of a pipe such as the current state, cost, and deterioration model. The objective function and detailed algorithm of dynamic programming are modified to solve the periodic replacement problem. The optimal policy evaluated by the proposed algorithm is compared to several existing policies via Monte Carlo simulations. The proposed decision framework provides a systematic way to obtain an optimal policy.
Directory of Open Access Journals (Sweden)
Vimal J. Savsani
2017-04-01
The static and dynamic responses to the TTO problems are challenging due to its search space, which is implicit, non-convex, non-linear, and often leading to divergence. Modified meta-heuristics are effective optimization methods to handle such problems in actual fact. In this paper, modified versions of Teaching–Learning-Based Optimization (TLBO, Heat Transfer Search (HTS, Water Wave Optimization (WWO, and Passing Vehicle Search (PVS are proposed by integrating the random mutation-based search technique with them. This paper compares the performance of four modified and four basic meta-heuristics to solve discrete TTO problems.
Numerical Simulation of a Tumor Growth Dynamics Model Using Particle Swarm Optimization.
Wang, Zhijun; Wang, Qing
Tumor cell growth models involve high-dimensional parameter spaces that require computationally tractable methods to solve. To address a proposed tumor growth dynamics mathematical model, an instance of the particle swarm optimization method was implemented to speed up the search process in the multi-dimensional parameter space to find optimal parameter values that fit experimental data from mice cancel cells. The fitness function, which measures the difference between calculated results and experimental data, was minimized in the numerical simulation process. The results and search efficiency of the particle swarm optimization method were compared to those from other evolutional methods such as genetic algorithms.
Directory of Open Access Journals (Sweden)
Andrey Fyodorovich Shorikov
2013-06-01
Full Text Available This paper reviews a methodical approach to solve multi-step dynamic problem of optimal integrated adaptive management of a product portfolio structure of the enterprise. For the organization of optimal adaptive terminal control of the system the recurrent algorithm, which reduces an initial multistage problem to the realization of the final sequence of problems of optimal program terminal control is offered. In turn, the decision of each problem of optimal program terminal control is reduced to the realization of the final sequence only single-step operations in the form of the problems solving of linear and convex mathematical programming. Thus, the offered approach allows to develop management solutions at current information support, which consider feedback, and which create the optimal structure of an enterprise’s product lines, contributing to optimising of profits, as well as maintenance of the desired level of profit for a long period of time
Wang, Wu; Huang, Wei; Zhang, Yongjun
2018-03-01
The grid-integration of Photovoltaic-Storage System brings some undefined factors to the network. In order to make full use of the adjusting ability of Photovoltaic-Storage System (PSS), this paper puts forward a reactive power optimization model, which are used to construct the objective function based on power loss and the device adjusting cost, including energy storage adjusting cost. By using Cataclysmic Genetic Algorithm to solve this optimization problem, and comparing with other optimization method, the result proved that: the method of dynamic extended reactive power optimization this article puts forward, can enhance the effect of reactive power optimization, including reducing power loss and device adjusting cost, meanwhile, it gives consideration to the safety of voltage.
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
Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining
Hussain, Shahid
2016-01-01
This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.
Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining
Hussain, Shahid
2016-07-10
This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.
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
The General Laws of Chemical Elements Composition Dynamics in the Biosphere
Korzh, Vyacheslav D.
2013-04-01
The key point of investigation of the specificity of the biosphere elemental composition formation is determination of patterns of redistribution of elemental average concentrations among various phases, like solid - liquid ( the lithosphere - the hydrosphere), which occurs as a result of a global continuous processing of inert matter by living substances. Our task here is to investigate this process in the system "lithosphere - hydrosphere" in view of the integrated involvement of living material in it. This process is most active in biogeochemical barriers, i.e. in places of "the life condensation" and runs under a nonlinear regularity that has been unknown before. It is established that this process results in a general relative increase in concentrations of chemical elements in the solid phase in proportion as their prevalence in the environment is reduced. This process running in various natural systems has practically the same parameter of nonlinearity (v) approximately equal to 0.7. For proto-lithosphere -"living material" - soil v = 0.75. For river - "living material" - ocean v = 0.67. For the contemporary factual awareness level these estimations of nonlinearity indices are practically negligible. Hence, it is for the first time that the existence of a universal constant of nonlinearity of elemental composition evolution in the biosphere has been proved and its quantitative evaluation has been made. REFERENCES 1. Korzh V.D. 1974. Some general laws governing the turnover of substance within the ocean-atmosphere-continent-ocean cycle. // Journal de Recherches Atmospheriques. Vol. 8. P. 653-660. 2. Korzh V.D. 2008. The general laws in the formation of the elemental composition of the Hydrosphere and Biosphere.// J. Ecologica, Vol. XV, P. 13-21. 3. Korzh V.D. 2012. Determination of general laws of elemental composition in Hydrosphere // Water: chemistry & ecology, Journal of water science and its practical application. # 1, P.56-62.
Optimization in Mobile IPv6 with Dynamic DNS
塩津, 達郎
2005-01-01
機器の高性能化により、モバイル端末においてもインターネットを利用した様々なアプリケーションを利用する要求が増え、無線通信環境の充実により、モバイル端末への通信を継続する仕組みが求められるようになった。 移動中の継続的な通信を可能とする技術の一つとして Mobile IPv6 がある。Mobile IPv6 にり、端末が移動しても通信を継続できる移動透過性が提供される。この移動透過性を実現するために、Mobile IPv6 では移動する端末とその端末と通信をしている端末の仲介役となる Home Agent が必要になる。ところが、仲介役となる必要のない場合でも Home Agent が仲介役として動き、無駄なパケットがインターネット上に流れてしまう。 本論文では、Mobile IPv6 という技術に加えて、Dynamic DNS という技術を用いて、Mobile IPv6 ネットワークの最適化を行う手法を提案し、性能評価を行った。...
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
International Nuclear Information System (INIS)
Song Ruizhuo; Wei Qinglai
2017-01-01
We develop an optimal tracking control method for chaotic system with unknown dynamics and disturbances. The method allows the optimal cost function and the corresponding tracking control to update synchronously. According to the tracking error and the reference dynamics, the augmented system is constructed. Then the optimal tracking control problem is defined. The policy iteration (PI) is introduced to solve the min-max optimization problem. The off-policy adaptive dynamic programming (ADP) algorithm is then proposed to find the solution of the tracking Hamilton–Jacobi–Isaacs (HJI) equation online only using measured data and without any knowledge about the system dynamics. Critic neural network (CNN), action neural network (ANN), and disturbance neural network (DNN) are used to approximate the cost function, control, and disturbance. The weights of these networks compose the augmented weight matrix, and the uniformly ultimately bounded (UUB) of which is proven. The convergence of the tracking error system is also proven. Two examples are given to show the effectiveness of the proposed synchronous solution method for the chaotic system tracking problem. (paper)
Optimal Interest-Rate Setting in a Dynamic IS/AS Model
DEFF Research Database (Denmark)
Jensen, Henrik
2011-01-01
This note deals with interest-rate setting in a simple dynamic macroeconomic setting. The purpose is to present some basic and central properties of an optimal interest-rate rule. The model framework predates the New-Keynesian paradigm of the late 1990s and onwards (it is accordingly dubbed “Old...
DEFF Research Database (Denmark)
Huang, Shaojun; Wu, Qiuwei; Cheng, Lin
2016-01-01
This paper presents an optimal reconfiguration-based dynamic tariff (DT) method for congestion management and line loss reduction in distribution networks with high penetration of electric vehicles. In the proposed DT concept, feeder reconfiguration (FR) is employed through mixed integer programm...
Alirezaei, M.; Kanarachos, S.A.; Scheepers, B.T.M.; Maurice, J.P.
2013-01-01
Development and experimentally evaluation of an optimal Vehicle Dynamic Control (VDC) strategy based on the State Dependent Riccati Equation (SDRE) control technique is presented. The proposed nonlinear controller is based on a nonlinear vehicle model with nonlinear tire characteristics. A novel
P.A.N. Bosman (Peter); J.A. La Poutré (Han); D. Thierens (Dirk)
2007-01-01
htmlabstractThe focus of this paper is on how to design evolutionary algorithms (EAs) for solving stochastic dynamic optimization problems online, i.e. as time goes by. For a proper design, the EA must not only be capable of tracking shifting optima, it must also take into account the future
The primary advantage of Dynamically Dimensioned Search algorithm (DDS) is that it outperforms many other optimization techniques in both convergence speed and the ability in searching for parameter sets that satisfy statistical guidelines while requiring only one algorithm parameter (perturbation f...
Optimal control landscape for the generation of unitary transformations with constrained dynamics
International Nuclear Information System (INIS)
Hsieh, Michael; Wu, Rebing; Rabitz, Herschel; Lidar, Daniel
2010-01-01
The reliable and precise generation of quantum unitary transformations is essential for the realization of a number of fundamental objectives, such as quantum control and quantum information processing. Prior work has explored the optimal control problem of generating such unitary transformations as a surface-optimization problem over the quantum control landscape, defined as a metric for realizing a desired unitary transformation as a function of the control variables. It was found that under the assumption of nondissipative and controllable dynamics, the landscape topology is trap free, which implies that any reasonable optimization heuristic should be able to identify globally optimal solutions. The present work is a control landscape analysis, which incorporates specific constraints in the Hamiltonian that correspond to certain dynamical symmetries in the underlying physical system. It is found that the presence of such symmetries does not destroy the trap-free topology. These findings expand the class of quantum dynamical systems on which control problems are intrinsically amenable to a solution by optimal control.
Improving the Dynamic Characteristics of Body-in-White Structure Using Structural Optimization
Directory of Open Access Journals (Sweden)
Aizzat S. Yahaya Rashid
2014-01-01
Full Text Available The dynamic behavior of a body-in-white (BIW structure has significant influence on the noise, vibration, and harshness (NVH and crashworthiness of a car. Therefore, by improving the dynamic characteristics of BIW, problems and failures associated with resonance and fatigue can be prevented. The design objectives attempt to improve the existing torsion and bending modes by using structural optimization subjected to dynamic load without compromising other factors such as mass and stiffness of the structure. The natural frequency of the design was modified by identifying and reinforcing the structure at critical locations. These crucial points are first identified by topology optimization using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size optimization step to find their target thickness of the structure. The thickness of affected regions of the components will be modified according to the analysis. The results of both optimization steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both optimization approaches is proposed to improve the design modification process.
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.
Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral
2016-09-20
In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors' batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information.
Optimization of rotor blades for combined structural, dynamic, and aerodynamic properties
He, Cheng-Jian; Peters, David A.
1990-01-01
Optimal helicopter blade design with computer-based mathematical programming has received more and more attention in recent years. Most of the research has focused on optimum dynamic characteristics of rotor blades to reduce vehicle vibration. There is also work on optimization of aerodynamic performance and on composite structural design. This research has greatly increased our understanding of helicopter optimum design in each of these aspects. Helicopter design is an inherently multidisciplinary process involving strong interactions among various disciplines which can appropriately include aerodynamics; dynamics, both flight dynamics and structural dynamics; aeroelasticity: vibrations and stability; and even acoustics. Therefore, the helicopter design process must satisfy manifold requirements related to the aforementioned diverse disciplines. In our present work, we attempt to combine several of these important effects in a unified manner. First, we design a blade with optimum aerodynamic performance by proper layout of blade planform and spanwise twist. Second, the blade is designed to have natural frequencies that are placed away from integer multiples of the rotor speed for a good dynamic characteristics. Third, the structure is made as light as possible with sufficient rotational inertia to allow for autorotational landing, with safe stress margins and flight fatigue life at each cross-section, and with aeroelastical stability and low vibrations. Finally, a unified optimization refines the solution.
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.
Quantum optimal control theory and dynamic coupling in the spin-boson model
International Nuclear Information System (INIS)
Jirari, H.; Poetz, W.
2006-01-01
A Markovian master equation describing the evolution of open quantum systems in the presence of a time-dependent external field is derived within the Bloch-Redfield formalism. It leads to a system-bath interaction which depends on the control field. Optimal control theory is used to select control fields which allow accelerated or decelerated system relaxation, or suppression of relaxation (dissipation) altogether, depending on the dynamics we impose on the quantum system. The control-dissipation correlation and the nonperturbative treatment of the control field are essential for reaching this goal. The optimal control problem is formulated within Pontryagin's minimum principle and the resulting optimal differential system is solved numerically. As an application, we study the dynamics of a spin-boson model in the strong coupling regime under the influence of an external control field. We show how trapping the system in unstable quantum states and transfer of population can be achieved by optimized control of the dissipative quantum system. We also used optimal control theory to find the driving field that generates the quantum Z gate. In several cases studied, we find that the selected optimal field which reduces the purity loss significantly is a multicomponent low-frequency field including higher harmonics, all of which lie below the phonon cutoff frequency. Finally, in the undriven case we present an analytic result for the Lamb shift at zero temperature
Welstead, Jason
2014-01-01
This research focused on incorporating stability and control into a multidisciplinary de- sign optimization on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design optimization was performed using the D8.2b transport air- craft concept. The con guration was optimized for minimum fuel burn using a design range of 3,000 nautical miles. Optimization cases were run using xed tail volume coecients, static trim constraints, and static trim and dynamic response constraints. A Cessna 182T model was used to test the various dynamic analysis components, ensuring the analysis was behaving as expected. Results of the optimizations show that including stability and con- trol in the design process drastically alters the optimal design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.
Optimization of multi-stage dynamic treatment regimes utilizing accumulated data.
Huang, Xuelin; Choi, Sangbum; Wang, Lu; Thall, Peter F
2015-11-20
In medical therapies involving multiple stages, a physician's choice of a subject's treatment at each stage depends on the subject's history of previous treatments and outcomes. The sequence of decisions is known as a dynamic treatment regime or treatment policy. We consider dynamic treatment regimes in settings where each subject's final outcome can be defined as the sum of longitudinally observed values, each corresponding to a stage of the regime. Q-learning, which is a backward induction method, is used to first optimize the last stage treatment then sequentially optimize each previous stage treatment until the first stage treatment is optimized. During this process, model-based expectations of outcomes of late stages are used in the optimization of earlier stages. When the outcome models are misspecified, bias can accumulate from stage to stage and become severe, especially when the number of treatment stages is large. We demonstrate that a modification of standard Q-learning can help reduce the accumulated bias. We provide a computational algorithm, estimators, and closed-form variance formulas. Simulation studies show that the modified Q-learning method has a higher probability of identifying the optimal treatment regime even in settings with misspecified models for outcomes. It is applied to identify optimal treatment regimes in a study for advanced prostate cancer and to estimate and compare the final mean rewards of all the possible discrete two-stage treatment sequences. Copyright © 2015 John Wiley & Sons, Ltd.
Yudin, V I; Taichenachev, A V; Basalaev, M Yu; Kovalenko, D V
2017-02-06
We theoretically investigate the dynamic regime of coherent population trapping (CPT) in the presence of frequency modulation (FM). We have formulated the criteria for quasi-stationary (adiabatic) and dynamic (non-adiabatic) responses of atomic system driven by this FM. Using the density matrix formalism for Λ system, the error signal is exactly calculated and optimized. It is shown that the optimal FM parameters correspond to the dynamic regime of atomic-field interaction, which significantly differs from conventional description of CPT resonances in the frame of quasi-stationary approach (under small modulation frequency). Obtained theoretical results are in good qualitative agreement with different experiments. Also we have found CPT-analogue of Pound-Driver-Hall regime of frequency stabilization.
Energy Technology Data Exchange (ETDEWEB)
Ilo, Albana [Siemens AG, Wien (Austria); Schaffer, Walter; Rieder, Thomas [Salzburg Netz GmbH, Salzburg (Austria); Dzafic, Izudin [Siemens AG, Nuernberg (Germany)
2012-07-01
A holistic approach of power system control that includes all voltage levels from highest to low voltage is provided. The power grid is conceived as a supply chain. The medium voltage grid represents the central link. The implemented automatic voltage control and the dynamic operation optimization are based on Distribution System State Estimator (DSSE) and Volt/Var Control (VVC) applications. The last one realizes the dynamic optimization of distribution network combining the reactive power of the decentralized generation, capacitors and voltage set points of on-line tap changers. Application of this method has shown, that by using the dynamic voltage control the grid can be stable operated near the low voltage limit. The conservation voltage reduction can be applied in real time. Furthermore the integration of the decentralized generation is facilitated with minimal costs. Until now in this regard required network expansion can be prevented or delayed. (orig.)
Zang, Thomas A.; Green, Lawrence L.
1999-01-01
A challenge for the fluid dynamics community is to adapt to and exploit the trend towards greater multidisciplinary focus in research and technology. The past decade has witnessed substantial growth in the research field of Multidisciplinary Design Optimization (MDO). MDO is a methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. As evidenced by the papers, which appear in the biannual AIAA/USAF/NASA/ISSMO Symposia on Multidisciplinary Analysis and Optimization, the MDO technical community focuses on vehicle and system design issues. This paper provides an overview of the MDO technology field from a fluid dynamics perspective, giving emphasis to suggestions of specific applications of recent MDO technologies that can enhance fluid dynamics research itself across the spectrum, from basic flow physics to full configuration aerodynamics.
Emergent dynamic structures and statistical law in spherical lattice gas automata
Yao, Zhenwei
2017-12-01
Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.
Spatio-temporal correlations in models of collective motion ruled by different dynamical laws.
Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas S; Melillo, Stefania; Viale, Massimiliano
2016-11-15
Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.
How Reflected Wave Fronts Dynamically Establish Hooke's Law in a Spring
Fahy, Stephen; O'Riordan, John; O'Sullivan, Colm; Twomey, Patrick
2012-01-01
A simple benchtop experiment in which a moving cart collides with a fixed spring is described. Force-time and force-distance data recorded during the collision display the transit of compression wave fronts through the spring following impact. These data can be used by students to develop a computational model of the dynamics of this simple…
Temperature dynamics and velocity scaling laws for interchange driven, warm ion plasma filaments
DEFF Research Database (Denmark)
Olsen, Jeppe Miki Busk; Madsen, Jens; Nielsen, Anders Henry
2016-01-01
The influence of electron and ion temperature dynamics on the radial convection of isolated structures in magnetically confined plasmas is investigated by means of numerical simulations. It is demonstrated that the maximum radial velocity of these plasma blobs roughly follows the inertial velocity...
Emergent dynamic structures and statistical law in spherical lattice gas automata.
Yao, Zhenwei
2017-12-01
Various lattice gas automata have been proposed in the past decades to simulate physics and address a host of problems on collective dynamics arising in diverse fields. In this work, we employ the lattice gas model defined on the sphere to investigate the curvature-driven dynamic structures and analyze the statistical behaviors in equilibrium. Under the simple propagation and collision rules, we show that the uniform collective movement of the particles on the sphere is geometrically frustrated, leading to several nonequilibrium dynamic structures not found in the planar lattice, such as the emergent bubble and vortex structures. With the accumulation of the collision effect, the system ultimately reaches equilibrium in the sense that the distribution of the coarse-grained speed approaches the two-dimensional Maxwell-Boltzmann distribution despite the population fluctuations in the coarse-grained cells. The emergent regularity in the statistical behavior of the system is rationalized by mapping our system to a generalized random walk model. This work demonstrates the capability of the spherical lattice gas automaton in revealing the lattice-guided dynamic structures and simulating the equilibrium physics. It suggests the promising possibility of using lattice gas automata defined on various curved surfaces to explore geometrically driven nonequilibrium physics.
Flux decay during thermonuclear X-ray bursts analysed with the dynamic power-law index method
Kuuttila, J.; Kajava, J. J. E.; Nättilä, J.; Motta, S. E.; Sánchez-Fernández, C.; Kuulkers, E.; Cumming, A.; Poutanen, J.
2017-08-01
The cooling of type-I X-ray bursts can be used to probe the nuclear burning conditions in neutron star envelopes. The flux decay of the bursts has been traditionally modelled with an exponential, even if theoretical considerations predict power-law-like decays. We have analysed a total of 540 type-I X-ray bursts from five low-mass X-ray binaries observed with the Rossi X-ray Timing Explorer. We grouped the bursts according to the source spectral state during which they were observed (hard or soft), flagging those bursts that showed signs of photospheric radius expansion (PRE). The decay phase of all the bursts were then fitted with a dynamic power-law index method. This method provides a new way of probing the chemical composition of the accreted material. Our results show that in the hydrogen-rich sources the power-law decay index is variable during the burst tails and that simple cooling models qualitatively describe the cooling of presumably helium-rich sources 4U 1728-34 and 3A 1820-303. The cooling in the hydrogen-rich sources 4U 1608-52, 4U 1636-536, and GS 1826-24, instead, is clearly different and depends on the spectral states and whether PRE occurred or not. Especially the hard state bursts behave differently than the models predict, exhibiting a peculiar rise in the cooling index at low burst fluxes, which suggests that the cooling in the tail is much faster than expected. Our results indicate that the drivers of the bursting behaviour are not only the accretion rate and chemical composition of the accreted material, but also the cooling that is somehow linked to the spectral states. The latter suggests that the properties of the burning layers deep in the neutron star envelope might be impacted differently depending on the spectral state.
Totz, Sonja; Eliseev, Alexey V.; Petri, Stefan; Flechsig, Michael; Caesar, Levke; Petoukhov, Vladimir; Coumou, Dim
2018-02-01
We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower
Optimal control of dissipative nonlinear dynamical systems with triggers of coupled singularities
International Nuclear Information System (INIS)
Hedrih, K
2008-01-01
This paper analyses the controllability of motion of nonconservative nonlinear dynamical systems in which triggers of coupled singularities exist or appear. It is shown that the phase plane method is useful for the analysis of nonlinear dynamics of nonconservative systems with one degree of freedom of control strategies and also shows the way it can be used for controlling the relative motion in rheonomic systems having equivalent scleronomic conservative or nonconservative system For the system with one generalized coordinate described by nonlinear differential equation of nonlinear dynamics with trigger of coupled singularities, the functions of system potential energy and conservative force must satisfy some conditions defined by a Theorem on the existence of a trigger of coupled singularities and the separatrix in the form of 'an open a spiral form' of number eight. Task of the defined dynamical nonconservative system optimal control is: by using controlling force acting to the system, transfer initial state of the nonlinear dynamics of the system into the final state of the nonlinear dynamics in the minimal time for that optimal control task
Optimal control of dissipative nonlinear dynamical systems with triggers of coupled singularities
Stevanović Hedrih, K.
2008-02-01
This paper analyses the controllability of motion of nonconservative nonlinear dynamical systems in which triggers of coupled singularities exist or appear. It is shown that the phase plane method is useful for the analysis of nonlinear dynamics of nonconservative systems with one degree of freedom of control strategies and also shows the way it can be used for controlling the relative motion in rheonomic systems having equivalent scleronomic conservative or nonconservative system For the system with one generalized coordinate described by nonlinear differential equation of nonlinear dynamics with trigger of coupled singularities, the functions of system potential energy and conservative force must satisfy some conditions defined by a Theorem on the existence of a trigger of coupled singularities and the separatrix in the form of "an open a spiral form" of number eight. Task of the defined dynamical nonconservative system optimal control is: by using controlling force acting to the system, transfer initial state of the nonlinear dynamics of the system into the final state of the nonlinear dynamics in the minimal time for that optimal control task
Directory of Open Access Journals (Sweden)
Ahmed M. Othman
2017-06-01
Full Text Available This paper presents a design of microgrid (MG with enhanced dynamic performance. Distributed energy resources (DER are widely used in MGs to match the various load types and profiles. DERs include solar PV cells, wind energy sources, fuel cells, batteries, micro gas-engines and storage elements. MG will include AC/DC circuits, developed power electronics devices, inverters and power electronic controllers. A novel modulated power filters (MPF device will be applied in MG design. Enhanced bacterial foraging optimization (EBFO will be proposed to optimize and set the MPF parameters to enhance and tune the MG dynamic response. Recent dynamic control is applied to minimize the harmonic reference content. EBFO will adapt the gains of MPF dynamic control. The present research achieves an enhancement of MG dynamic performance, in addition to ensuring improvements in the power factor, bus voltage profile and power quality. MG operation will be evaluated by the dynamic response to be fine-tuned by MPF based on EBFO. Digital simulations have validated the results to show the effectiveness and efficient improvement by the proposed strategy.
Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing
Directory of Open Access Journals (Sweden)
Muhammad Babar Rasheed
2016-07-01
Full Text Available In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.
International Nuclear Information System (INIS)
Zhao Hongsheng; Li Baojiu; Bienayme, Olivier
2010-01-01
We derive a simple analytical expression for the two-body force in a subclass of modified Newtonian dynamics (MOND) theories and make testable predictions in the modification to the two-body orbital period, shape, precession rate, escape speed, etc. We demonstrate the applications of the modified Kepler's law in the timing of satellite orbits around the Milky Way, and checking the feasibility of MOND in the orbit of the large Magellanic cloud, the M31 galaxy, and the merging bullet clusters. MOND appears to be consistent with satellite orbits although with a tight margin. Our results on two-bodies are also generalized to restricted three-body, many-body problems, rings, and shells.
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.
Vitanov, Nikolay K
2016-01-01
This book deals with methods to evaluate scientific productivity. In the book statistical methods, deterministic and stochastic models and numerous indexes are discussed that will help the reader to understand the nonlinear science dynamics and to be able to develop or construct systems for appropriate evaluation of research productivity and management of research groups and organizations. The dynamics of science structures and systems is complex, and the evaluation of research productivity requires a combination of qualitative and quantitative methods and measures. The book has three parts. The first part is devoted to mathematical models describing the importance of science for economic growth and systems for the evaluation of research organizations of different size. The second part contains descriptions and discussions of numerous indexes for the evaluation of the productivity of researchers and groups of researchers of different size (up to the comparison of research productivities of research communiti...
A power law of order 1/4 for critical mean field Swendsen-Wang dynamics
Long, Yun; Ning, Weiyang; Peres, Yuval
2014-01-01
The Swendsen-Wang dynamics is a Markov chain widely used by physicists to sample from the Boltzmann-Gibbs distribution of the Ising model. Cooper, Dyer, Frieze and Rue proved that on the complete graph K_n the mixing time of the chain is at most O(\\sqrt{n}) for all non-critical temperatures. In this paper the authors show that the mixing time is \\Theta(1) in high temperatures, \\Theta(\\log n) in low temperatures and \\Theta(n^{1/4}) at criticality. They also provide an upper bound of O(\\log n) for Swendsen-Wang dynamics for the q-state ferromagnetic Potts model on any tree of n vertices.
Designing a hand rest tremor dynamic vibration absorber using H{sub 2} optimization method
Energy Technology Data Exchange (ETDEWEB)
Rahnavard, Mostafa; Dizaji, Ahmad F. [Tehran University, Tehran (Iran, Islamic Republic of); Hashemi, Mojtaba [Amirkabir University, Tehran (Iran, Islamic Republic of); Faramand, Farzam [Sharif University, Tehran (Iran, Islamic Republic of)
2014-05-15
An optimal single DOF dynamic absorber is presented. A tremor has a random nature and then the system is subjected to a random excitation instead of a sinusoidal one; so the H{sub 2} optimization criterion is probably more desirable than the popular H{sub ∞} optimization method and was implemented in this research. The objective of H{sub 2} optimization criterion is to reduce the total vibration energy of the system for overall frequencies. An objective function, considering the elbow joint angle, θ {sub 2}, tremor suppression as the main goal, was selected. The optimization was done by minimization of this objective function. The optimal system, including the absorber, performance was analyzed in both time and frequency domains. Implementing the optimal absorber, the frequency response amplitude of θ{sub 2} was reduced by more than 98% and 80% at the first and second natural frequencies of the primary system, respectively. A reduction of more than 94% and 78%, was observed for the shoulder joint angle, θ{sub 1}. The objective function also decreased by more than 46%. Then, two types of random inputs were considered. For the first type, θ{sub 1} and θ {sub 2} revealed 60% and 39% reduction in their rms values, whereas for the second type, 33% and 50% decrease was observed.
Designing a hand rest tremor dynamic vibration absorber using H2 optimization method
International Nuclear Information System (INIS)
Rahnavard, Mostafa; Dizaji, Ahmad F.; Hashemi, Mojtaba; Faramand, Farzam
2014-01-01
An optimal single DOF dynamic absorber is presented. A tremor has a random nature and then the system is subjected to a random excitation instead of a sinusoidal one; so the H 2 optimization criterion is probably more desirable than the popular H ∞ optimization method and was implemented in this research. The objective of H 2 optimization criterion is to reduce the total vibration energy of the system for overall frequencies. An objective function, considering the elbow joint angle, θ 2 , tremor suppression as the main goal, was selected. The optimization was done by minimization of this objective function. The optimal system, including the absorber, performance was analyzed in both time and frequency domains. Implementing the optimal absorber, the frequency response amplitude of θ 2 was reduced by more than 98% and 80% at the first and second natural frequencies of the primary system, respectively. A reduction of more than 94% and 78%, was observed for the shoulder joint angle, θ 1 . The objective function also decreased by more than 46%. Then, two types of random inputs were considered. For the first type, θ 1 and θ 2 revealed 60% and 39% reduction in their rms values, whereas for the second type, 33% and 50% decrease was observed.
Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing
2017-07-19
Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.
A Dynamic Optimization Method of Indoor Fire Evacuation Route Based on Real-time Situation Awareness
Directory of Open Access Journals (Sweden)
DING Yulin
2016-12-01
Full Text Available How to provide safe and effective evacuation routes is an important safeguard to correctly guide evacuation and reduce the casualties during the fire situation rapidly evolving in complex indoor environment. The traditional static path finding method is difficult to adjust the path adaptively according to the changing fire situation, which lead to the evacuation decision-making blindness and hysteresis. This paper proposes a dynamic method which can dynamically optimize the indoor evacuation routes based on the real-time situation awareness. According to the real-time perception of fire situation parameters and the changing indoor environment information, the evacuation route is optimized dynamically. The integrated representation of multisource indoor fire monitoring sensor observations oriented fire emergency evacuation is presented at first, real-time fire threat situation information inside building is then extracted from the observation data of multi-source sensors, which is used to constrain the dynamical optimization of the topology of the evacuation route. Finally, the simulation experiments prove that this method can improve the accuracy and efficiency of indoor evacuation routing.
Nonlinear Dynamic in an Ecological System with Impulsive Effect and Optimal Foraging
Directory of Open Access Journals (Sweden)
Min Zhao
2014-01-01
Full Text Available The population dynamics of a three-species ecological system with impulsive effect are investigated. Using the theories of impulsive equations and small-amplitude perturbation scales, the conditions for the system to be permanent when the number of predators released is less than some critical value can be obtained. Furthermore, because the predator in the system follows the predictions of optimal foraging theory, it follows that optimal foraging promotes species coexistence. In particular, the less beneficial prey can support the predator alone when the more beneficial prey goes extinct. Moreover, the influences of the impulsive effect and optimal foraging on inherent oscillations are studied using simulation, which reveals rich dynamic behaviors such as period-halving bifurcations, a chaotic band, a periodic window, and chaotic crises. In addition, the largest Lyapunov exponent and the power spectra of the strange attractor, which can help analyze the chaotic dynamic behavior of the model, are investigated. This information will be useful for studying the dynamic complexity of ecosystems.
TH-EF-BRB-02: Feasibility of Optimization for Dynamic Trajectory Radiotherapy
Energy Technology Data Exchange (ETDEWEB)
Fix, MK; Frei, D; Volken, W; Terribilini, D; Aebersold, DM; Manser, P [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Berne (Switzerland)
2016-06-15
Purpose: Over the last years, volumetric modulated arc therapy (VMAT) has been widely introduced into clinical routine using a coplanar delivery technique. However, VMAT might be improved by including dynamic couch and collimator rotations, leading to dynamic trajectory radiotherapy (DTRT). In this work the feasibility and the potential benefit of DTRT was investigated. Methods: A general framework for the optimization was developed using the Eclipse Scripting Research Application Programming Interface (ESRAPI). Based on contoured target and organs at risk (OARs), the structures are extracted using the ESRAPI. Sampling potential beam directions, regularly distributed on a sphere using a Fibanocci-lattice, the fractional volume-overlap of each OAR and the target is determined and used to establish dynamic gantry-couch movements. Then, for each gantry-couch track the most suitable collimator angle is determined for each control point by optimizing the area between the MLC leaves and the target contour. The resulting dynamic trajectories are used as input to perform the optimization using a research version of the VMAT optimization algorithm and the ESRAPI. The feasibility of this procedure was tested for a clinically motivated head and neck case. Resulting dose distributions for the VMAT plan and for the dynamic trajectory treatment plan were compared based on DVH-parameters. Results: While the DVH for the target is virtually preserved, improvements in maximum dose for the DTRT plan were achieved for all OARs except for the inner-ear, where maximum dose remains the same. The major improvements in maximum dose were 6.5% of the prescribed dose (66 Gy) for the parotid and 5.5% for the myelon and the eye. Conclusion: The result of this work suggests that DTRT has a great potential to reduce dose to OARs with similar target coverage when compared to conventional VMAT treatment plans. This work was supported by Varian Medical Systems. This work was supported by Varian
Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing
Ono, Masahiro; Kuwata, Yoshiaki
2013-01-01
A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.
Directory of Open Access Journals (Sweden)
R. Bartolini
2012-03-01
Full Text Available Linac driven free electron lasers (FELs operating in the x-ray region require a high brightness electron beam in order to reach saturation within a reasonable distance in the undulator train or to enable sophisticated seeding schemes using external lasers. The beam dynamics optimization is usually a time consuming process in which many parameters of the accelerator and the compression system have to be controlled simultaneously. The requirements on the electron beam quality may also vary significantly with the particular application. For example, the beam dynamics optimization strategy for self-amplified spontaneous emission operation and seeded operation are rather different: seeded operation requires a more careful control of the beam uniformity over a relatively large portion of the longitudinal current distribution of the electron bunch and is therefore more challenging from an accelerator physics point of view. Multiobjective genetic algorithms are particularly well suited when the optimization of many parameters is targeting several objectives simultaneously, often with conflicting requirements. In this paper we propose a novel optimization strategy based on a combination of multiobjective optimization with a fast computation of the FEL performance. The application to the proposed UK’s New Light Source is reported and the benefits of this method are highlighted.
Effects of upper body parameters on biped walking efficiency studied by dynamic optimization
Directory of Open Access Journals (Sweden)
Kang An
2016-12-01
Full Text Available Walking efficiency is one of the considerations for designing biped robots. This article uses the dynamic optimization method to study the effects of upper body parameters, including upper body length and mass, on walking efficiency. Two minimal actuations, hip joint torque and push-off impulse, are used in the walking model, and minimal constraints are set in a free search using the dynamic optimization. Results show that there is an optimal solution of upper body length for the efficient walking within a range of walking speed and step length. For short step length, walking with a lighter upper body mass is found to be more efficient and vice versa. It is also found that for higher speed locomotion, the increase of the upper body length and mass can make the walking gait optimal rather than other kind of gaits. In addition, the typical strategy of an optimal walking gait is that just actuating the swing leg at the beginning of the step.
Directory of Open Access Journals (Sweden)
Farzad Amirkhani
2017-03-01
The proposed method is implemented on classical job-shop problems with objective of makespan and results are compared with mixed integer programming model. Moreover, the appropriate dispatching priorities are achieved for dynamic job-shop problem minimizing a multi-objective criteria. The results show that simulation-based optimization are highly capable to capture the main characteristics of the shop and produce optimal/near-optimal solutions with highly credibility degree.
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)
Optimal placement of excitations and sensors for verification of large dynamical systems
Salama, M.; Rose, T.; Garba, J.
1987-01-01
The computationally difficult problem of the optimal placement of excitations and sensors to maximize the observed measurements is studied within the framework of combinatorial optimization, and is solved numerically using a variation of the simulated annealing heuristic algorithm. Results of numerical experiments including a square plate and a 960 degrees-of-freedom Control of Flexible Structure (COFS) truss structure, are presented. Though the algorithm produces suboptimal solutions, its generality and simplicity allow the treatment of complex dynamical systems which would otherwise be difficult to handle.
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1993-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1991-01-01
The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contributions of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...
Power-law scaling of extreme dynamics near higher-order exceptional points
Zhong, Q.; Christodoulides, D. N.; Khajavikhan, M.; Makris, K. G.; El-Ganainy, R.
2018-02-01
We investigate the extreme dynamics of non-Hermitian systems near higher-order exceptional points in photonic networks constructed using the bosonic algebra method. We show that strong power oscillations for certain initial conditions can occur as a result of the peculiar eigenspace geometry and its dimensionality collapse near these singularities. By using complementary numerical and analytical approaches, we show that, in the parity-time (PT ) phase near exceptional points, the logarithm of the maximum optical power amplification scales linearly with the order of the exceptional point. We focus in our discussion on photonic systems, but we note that our results apply to other physical systems as well.
Optimal Acceleration-Velocity-Bounded Trajectory Planning in Dynamic Crowd Simulation
Directory of Open Access Journals (Sweden)
Fu Yue-wen
2014-01-01
Full Text Available Creating complex and realistic crowd behaviors, such as pedestrian navigation behavior with dynamic obstacles, is a difficult and time consuming task. In this paper, we study one special type of crowd which is composed of urgent individuals, normal individuals, and normal groups. We use three steps to construct the crowd simulation in dynamic environment. The first one is that the urgent individuals move forward along a given path around dynamic obstacles and other crowd members. An optimal acceleration-velocity-bounded trajectory planning method is utilized to model their behaviors, which ensures that the durations of the generated trajectories are minimal and the urgent individuals are collision-free with dynamic obstacles (e.g., dynamic vehicles. In the second step, a pushing model is adopted to simulate the interactions between urgent members and normal ones, which ensures that the computational cost of the optimal trajectory planning is acceptable. The third step is obligated to imitate the interactions among normal members using collision avoidance behavior and flocking behavior. Various simulation results demonstrate that these three steps give realistic crowd phenomenon just like the real world.
Directory of Open Access Journals (Sweden)
Nicholas J. Sammut
2007-08-01
Full Text Available A superconducting particle accelerator like the LHC (Large Hadron Collider at CERN, can only be controlled well if the effects of the magnetic field multipoles on the beam are compensated. The demands on a control system solely based on beam feedback may be too high for the requirements to be reached at the specified bandwidth and accuracy. Therefore, we designed a suitable field description for the LHC (FIDEL as part of the machine control baseline to act as a feed-forward magnetic field prediction system. FIDEL consists of a physical and empirical parametric field model based on magnetic measurements at warm and in cryogenic conditions. The performance of FIDEL is particularly critical at injection when the field decays, and in the initial part of the acceleration when the field snaps back. These dynamic components are both current and time dependent and are not reproducible from cycle to cycle since they also depend on the magnet powering history. In this paper a qualitative and quantitative description of the dynamic field behavior substantiated by a set of scaling laws is presented.
Trombetti, Tomaso
This thesis presents an Experimental/Analytical approach to modeling and calibrating shaking tables for structural dynamic applications. This approach was successfully applied to the shaking table recently built in the structural laboratory of the Civil Engineering Department at Rice University. This shaking table is capable of reproducing model earthquake ground motions with a peak acceleration of 6 g's, a peak velocity of 40 inches per second, and a peak displacement of 3 inches, for a maximum payload of 1500 pounds. It has a frequency bandwidth of approximately 70 Hz and is designed to test structural specimens up to 1/5 scale. The rail/table system is mounted on a reaction mass of about 70,000 pounds consisting of three 12 ft x 12 ft x 1 ft reinforced concrete slabs, post-tensioned together and connected to the strong laboratory floor. The slip table is driven by a hydraulic actuator governed by a 407 MTS controller which employs a proportional-integral-derivative-feedforward-differential pressure algorithm to control the actuator displacement. Feedback signals are provided by two LVDT's (monitoring the slip table relative displacement and the servovalve main stage spool position) and by one differential pressure transducer (monitoring the actuator force). The dynamic actuator-foundation-specimen system is modeled and analyzed by combining linear control theory and linear structural dynamics. The analytical model developed accounts for the effects of actuator oil compressibility, oil leakage in the actuator, time delay in the response of the servovalve spool to a given electrical signal, foundation flexibility, and dynamic characteristics of multi-degree-of-freedom specimens. In order to study the actual dynamic behavior of the shaking table, the transfer function between target and actual table accelerations were identified using experimental results and spectral estimation techniques. The power spectral density of the system input and the cross power spectral
Optimization of Measurements on Dynamically Sensitive Structures Using a Reliability Approach
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
Design of a measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of a measuring program. Design variab...... variables are the numbers of measuring points, the locations of these points and the required number of sample records. An example with a simply supported plane, vibrating beam is considered and tentative results are presented.......Design of a measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of a measuring program. Design...
Optimization of Measurements on Dynamically Sensitive Structures Using a Reliability Approach
DEFF Research Database (Denmark)
Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune
1990-01-01
Design of measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of masuring program. Design variables a...... are the numbers of measuring points, the locations of these points and the required number of sample records. An example with a simply supported plane, vibrating beam is considered and tentative results are presented.......Design of measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of masuring program. Design variables...
Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics
Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.
2018-02-01
Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.
Directory of Open Access Journals (Sweden)
S. I. Suskov
2011-01-01
Full Text Available The basic variants of cytokines reactions defining type of organ dysfunctions are revealed in the course of car- diopulmonary bypass and in the early postoperative period. Their character and expression, depends on gravity preoperative an immunodeficiency and initial degree of heart insufficiency. Diphasic dynamics of development of system inflammatory reaction is confirmed after cardiopulmonary bypass: increase of levels proinflammatory cytokines is in the first phase and anti-inflammatory cytokines with development immunodepression and cellular anergy in is the second phase. Also, key role IL-1Ra is revealed in restraint of hyperactivation of system inflam- matory reaction. Blood whey levels IL-6, IL-8, G-CSF, TNF-α and IL-1Ra should be defined to cardiopulmonary bypass, in 10–12 hours, 24 hours and 3 days after cardiopulmonary bypass and may be used as prognostic criteria of development of postoperative complications.
International Nuclear Information System (INIS)
Sklarz, Shlomo E.; Tannor, David J.; Khaneja, Navin
2004-01-01
We study the problem of optimal control of dissipative quantum dynamics. Although under most circumstances dissipation leads to an increase in entropy (or a decrease in purity) of the system, there is an important class of problems for which dissipation with external control can decrease the entropy (or increase the purity) of the system. An important example is laser cooling. In such systems, there is an interplay of the Hamiltonian part of the dynamics, which is controllable, and the dissipative part of the dynamics, which is uncontrollable. The strategy is to control the Hamiltonian portion of the evolution in such a way that the dissipation causes the purity of the system to increase rather than decrease. The goal of this paper is to find the strategy that leads to maximal purity at the final time. Under the assumption that Hamiltonian control is complete and arbitrarily fast, we provide a general framework by which to calculate optimal cooling strategies. These assumptions lead to a great simplification, in which the control problem can be reformulated in terms of the spectrum of eigenvalues of ρ, rather than ρ itself. By combining this formulation with the Hamilton-Jacobi-Bellman theorem we are able to obtain an equation for the globally optimal cooling strategy in terms of the spectrum of the density matrix. For the three-level Λ system, we provide a complete analytic solution for the optimal cooling strategy. For this system it is found that the optimal strategy does not exploit system coherences and is a 'greedy' strategy, in which the purity is increased maximally at each instant
Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.
2015-05-01
The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.
Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC
Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.
2014-10-01
The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.
Petrović, Jelena; Ibrić, Svetlana; Betz, Gabriele; Đurić, Zorica
2012-05-30
The main objective of the study was to develop artificial intelligence methods for optimization of drug release from matrix tablets regardless of the matrix type. Static and dynamic artificial neural networks of the same topology were developed to model dissolution profiles of different matrix tablets types (hydrophilic/lipid) using formulation composition, compression force used for tableting and tablets porosity and tensile strength as input data. Potential application of decision trees in discovering knowledge from experimental data was also investigated. Polyethylene oxide polymer and glyceryl palmitostearate were used as matrix forming materials for hydrophilic and lipid matrix tablets, respectively whereas selected model drugs were diclofenac sodium and caffeine. Matrix tablets were prepared by direct compression method and tested for in vitro dissolution profiles. Optimization of static and dynamic neural networks used for modeling of drug release was performed using Monte Carlo simulations or genetic algorithms optimizer. Decision trees were constructed following discretization of data. Calculated difference (f(1)) and similarity (f(2)) factors for predicted and experimentally obtained dissolution profiles of test matrix tablets formulations indicate that Elman dynamic neural networks as well as decision trees are capable of accurate predictions of both hydrophilic and lipid matrix tablets dissolution profiles. Elman neural networks were compared to most frequently used static network, Multi-layered perceptron, and superiority of Elman networks have been demonstrated. Developed methods allow simple, yet very precise way of drug release predictions for both hydrophilic and lipid matrix tablets having controlled drug release. Copyright © 2012 Elsevier B.V. All rights reserved.
Dynamic modeling and optimal joint torque coordination of advanced robotic systems
Kang, Hee-Jun
The development is documented of an efficient dynamic modeling algorithm and the subsequent optimal joint input load coordination of advanced robotic systems for industrial application. A closed-form dynamic modeling algorithm for the general closed-chain robotic linkage systems is presented. The algorithm is based on the transfer of system dependence from a set of open chain Lagrangian coordinates to any desired system generalized coordinate set of the closed-chain. Three different techniques for evaluation of the kinematic closed chain constraints allow the representation of the dynamic modeling parameters in terms of system generalized coordinates and have no restriction with regard to kinematic redundancy. The total computational requirement of the closed-chain system model is largely dependent on the computation required for the dynamic model of an open kinematic chain. In order to improve computational efficiency, modification of an existing open-chain KIC based dynamic formulation is made by the introduction of the generalized augmented body concept. This algorithm allows a 44 pct. computational saving over the current optimized one (O(N4), 5995 when N = 6). As means of resolving redundancies in advanced robotic systems, local joint torque optimization is applied for effectively using actuator power while avoiding joint torque limits. The stability problem in local joint torque optimization schemes is eliminated by using fictitious dissipating forces which act in the necessary null space. The performance index representing the global torque norm is shown to be satisfactory. In addition, the resulting joint motion trajectory becomes conservative, after a transient stage, for repetitive cyclic end-effector trajectories. The effectiveness of the null space damping method is shown. The modular robot, which is built of well defined structural modules from a finite-size inventory and is controlled by one general computer system, is another class of evolving
A new logistic dynamic particle swarm optimization algorithm based on random topology.
Ni, Qingjian; Deng, Jianming
2013-01-01
Population topology of particle swarm optimization (PSO) will directly affect the dissemination of optimal information during the evolutionary process and will have a significant impact on the performance of PSO. Classic static population topologies are usually used in PSO, such as fully connected topology, ring topology, star topology, and square topology. In this paper, the performance of PSO with the proposed random topologies is analyzed, and the relationship between population topology and the performance of PSO is also explored from the perspective of graph theory characteristics in population topologies. Further, in a relatively new PSO variant which named logistic dynamic particle optimization, an extensive simulation study is presented to discuss the effectiveness of the random topology and the design strategies of population topology. Finally, the experimental data are analyzed and discussed. And about the design and use of population topology on PSO, some useful conclusions are proposed which can provide a basis for further discussion and research.
A dynamic lattice searching method with rotation operation for optimization of large clusters
International Nuclear Information System (INIS)
Wu Xia; Cai Wensheng; Shao Xueguang
2009-01-01
Global optimization of large clusters has been a difficult task, though much effort has been paid and many efficient methods have been proposed. During our works, a rotation operation (RO) is designed to realize the structural transformation from decahedra to icosahedra for the optimization of large clusters, by rotating the atoms below the center atom with a definite degree around the fivefold axis. Based on the RO, a development of the previous dynamic lattice searching with constructed core (DLSc), named as DLSc-RO, is presented. With an investigation of the method for the optimization of Lennard-Jones (LJ) clusters, i.e., LJ 500 , LJ 561 , LJ 600 , LJ 665-667 , LJ 670 , LJ 685 , and LJ 923 , Morse clusters, silver clusters by Gupta potential, and aluminum clusters by NP-B potential, it was found that both the global minima with icosahedral and decahedral motifs can be obtained, and the method is proved to be efficient and universal.
Distributed Optimization based Dynamic Tariff for Congestion Management in Distribution Networks
DEFF Research Database (Denmark)
Huang, Shaojun; Wu, Qiuwei; Zhao, Haoran
2017-01-01
This paper proposes a distributed optimization based dynamic tariff (DDT) method for congestion management in distribution networks with high penetration of electric vehicles (EVs) and heat pumps (HPs). The DDT method employs a decomposition based optimization method to have aggregators explicitly...... is able to minimize the overall energy consumption cost and line loss cost, which is different from previous decomposition-based methods such as multiagent system methods. In addition, a reconditioning method and an integral controller are introduced to improve convergence of the distributed optimization...... where challenges arise due to multiple congestion points, multiple types of flexible demands and network constraints. The case studies demonstrate the efficacy of the DDT method for congestion management in distribution networks....
Optimization of structures subjected to dynamic load: deterministic and probabilistic methods
Directory of Open Access Journals (Sweden)
Élcio Cassimiro Alves
Full Text Available Abstract This paper deals with the deterministic and probabilistic optimization of structures against bending when submitted to dynamic loads. The deterministic optimization problem considers the plate submitted to a time varying load while the probabilistic one takes into account a random loading defined by a power spectral density function. The correlation between the two problems is made by one Fourier Transformed. The finite element method is used to model the structures. The sensitivity analysis is performed through the analytical method and the optimization problem is dealt with by the method of interior points. A comparison between the deterministic optimisation and the probabilistic one with a power spectral density function compatible with the time varying load shows very good results.
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...... the width of the channels in the gas distributor and the area in front of the parallel channels. The flow of the optimized design is found to have a flow uniformity index value of 0.978. The effects of deviations from the assumptions used in the modelling (isothermal and non-reacting flow) are evaluated...... and it is found that a temperature gradient along the parallel channels does not affect the flow uniformity, whereas a temperature difference between the channels does. The impact of the flow distribution on the maximum obtainable conversion during operation is also investigated and the obtainable overall...
Four-bar linkage-based automatic tool changer: Dynamic modeling and torque optimization
Energy Technology Data Exchange (ETDEWEB)
Lee, Sangho; Seo, TaeWon [Yeungnam University, Gyeongsan (Korea, Republic of); Kim, Jong-Won; Kim, Jongwon [Seoul National University, Seoul (Korea, Republic of)
2017-05-15
An Automatic tool changer (ATC) is a device used in a tapping machine to reduce process time. This paper presents the optimization of a Peak torque reduction mechanism (PTRM) for an ATC. It is necessary to reduce the fatigue load and energy consumed, which is related to the peak torque. The PTRM uses a torsion spring to reduce the peak torque and was applied to a novel ATC mechanism, which was modeled using inverse dynamics. Optimization of the PTRM is required to minimize the peak torque. The design parameters are the initial angle and stiffness of the torsion spring, and the objective function is the peak torque of the input link. The torque was simulated, and the peak torque was decreased by 10 %. The energy consumed was reduced by the optimization.
Four-bar linkage-based automatic tool changer: Dynamic modeling and torque optimization
International Nuclear Information System (INIS)
Lee, Sangho; Seo, TaeWon; Kim, Jong-Won; Kim, Jongwon
2017-01-01
An Automatic tool changer (ATC) is a device used in a tapping machine to reduce process time. This paper presents the optimization of a Peak torque reduction mechanism (PTRM) for an ATC. It is necessary to reduce the fatigue load and energy consumed, which is related to the peak torque. The PTRM uses a torsion spring to reduce the peak torque and was applied to a novel ATC mechanism, which was modeled using inverse dynamics. Optimization of the PTRM is required to minimize the peak torque. The design parameters are the initial angle and stiffness of the torsion spring, and the objective function is the peak torque of the input link. The torque was simulated, and the peak torque was decreased by 10 %. The energy consumed was reduced by the optimization.
DEFF Research Database (Denmark)
Davidsen, Claus; Liu, Suxia; Mo, Xingguo
2015-01-01
Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth......-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water...... quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen...
Directory of Open Access Journals (Sweden)
Hongling Ye
2015-01-01
Full Text Available The dynamic topology optimization of three-dimensional continuum structures subject to frequency constraints is investigated using Independent Continuous Mapping (ICM design variable fields. The composite exponential function (CEF is selected to be a filter function which recognizes the design variables and to implement the changing process of design variables from “discrete” to “continuous” and back to “discrete.” Explicit formulations of frequency constraints are given based on filter functions, first-order Taylor series expansion. And an improved optimal model is formulated using CEF and the explicit frequency constraints. Dual sequential quadratic programming (DSQP algorithm is used to solve the optimal model. The program is developed on the platform of MSC Patran & Nastran. Finally, numerical examples are given to demonstrate the validity and applicability of the proposed method.
Dynamic Optimal Energy Flow in the Integrated Natural Gas and Electrical Power Systems
DEFF Research Database (Denmark)
Fang, Jiakun; Zeng, Qing; Ai, Xiaomeng
2018-01-01
. Simulation on the test case illustrates the success of the modelling and the beneficial roles of the power-to-gas are analyzed. The proposed model can be used in the decision support for both planning and operation of the coordinated natural gas and electrical power systems.......This work focuses on the optimal operation of the integrated gas and electrical power system with bi-directional energy conversion. Considering the different response times of the gas and power systems, the transient gas flow and steady- state power flow are combined to formulate the dynamic...... optimal energy flow in the integrated gas and power systems. With proper assumptions and simplifications, the problem is transformed into a single stage linear programming. And only a single stage linear programming is needed to obtain the optimal operation strategy for both gas and power systems...
Stochastic optimal control in infinite dimension dynamic programming and HJB equations
Fabbri, Giorgio; Święch, Andrzej
2017-01-01
Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite ...
Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.
Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L
2017-10-01
The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.
Lali, Mehdi
2009-03-01
A comprehensive computer program is designed in MATLAB to analyze, design and optimize the propulsion, dynamics, thermodynamics, and kinematics of any serial multi-staging rocket for a set of given data. The program is quite user-friendly. It comprises two main sections: "analysis and design" and "optimization." Each section has a GUI (Graphical User Interface) in which the rocket's data are entered by the user and by which the program is run. The first section analyzes the performance of the rocket that is previously devised by the user. Numerous plots and subplots are provided to display the performance of the rocket. The second section of the program finds the "optimum trajectory" via billions of iterations and computations which are done through sophisticated algorithms using numerical methods and incremental integrations. Innovative techniques are applied to calculate the optimal parameters for the engine and designing the "optimal pitch program." This computer program is stand-alone in such a way that it calculates almost every design parameter in regards to rocket propulsion and dynamics. It is meant to be used for actual launch operations as well as educational and research purposes.
Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement
Liu, Dalong; Xu, Lijuan
2018-01-01
In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.
Dynamic Feedforward Control of a Diesel Engine Based on Optimal Transient Compensation Maps
Directory of Open Access Journals (Sweden)
Giorgio Mancini
2014-08-01
Full Text Available To satisfy the increasingly stringent emission regulations and a demand for an ever lower fuel consumption, diesel engines have become complex systems with many interacting actuators. As a consequence, these requirements are pushing control and calibration to their limits. The calibration procedure nowadays is still based mainly on engineering experience, which results in a highly iterative process to derive a complete engine calibration. Moreover, automatic tools are available only for stationary operation, to obtain control maps that are optimal with respect to some predefined objective function. Therefore, the exploitation of any leftover potential during transient operation is crucial. This paper proposes an approach to derive a transient feedforward (FF control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. A partially physics-based model is thereby used to replace the engine. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient. These maps complement the static control maps by accounting for the dynamic behavior of the engine. The procedure is implemented on a real engine and experimental results are presented along with the development of the methodology.
Helbing, Dirk; Schönhof, Martin; Kern, Daniel
2002-06-01
The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.
Grafton, R. Quentin; Chu, Hoang Long; Stewardson, Michael; Kompas, Tom
2011-12-01
A key challenge in managing semiarid basins, such as in the Murray-Darling in Australia, is to balance the trade-offs between the net benefits of allocating water for irrigated agriculture, and other uses, versus the costs of reduced surface flows for the environment. Typically, water planners do not have the tools to optimally and dynamically allocate water among competing uses. We address this problem by developing a general stochastic, dynamic programming model with four state variables (the drought status, the current weather, weather correlation, and current storage) and two controls (environmental release and irrigation allocation) to optimally allocate water between extractions and in situ uses. The model is calibrated to Australia's Murray River that generates: (1) a robust qualitative result that "pulse" or artificial flood events are an optimal way to deliver environmental flows over and above conveyance of base flows; (2) from 2001 to 2009 a water reallocation that would have given less to irrigated agriculture and more to environmental flows would have generated between half a billion and over 3 billion U.S. dollars in overall economic benefits; and (3) water markets increase optimal environmental releases by reducing the losses associated with reduced water diversions.
International Nuclear Information System (INIS)
Culver, T.B.
1991-01-01
Several modifications of the linear-quadratic regulator (LQR) optimization algorithm are developed, and the computational efficiency of each algorithm with respect to groundwater remediation is evaluated. In each case, the optimization model is combined with a finite element groundwater flow and transport simulation model to determine the optimal time-varying pump-and-treat policy. The first modification of the LQR algorithm incorporated management periods, which are groups of simulation time steps during which the pumping policy remains constant. Management periods reduced the total computational demand, as measured by the CPU time, by as much as 85% compared to the time needed for the LQR solution without management periods. Complexity analysis revealed that computational savings of equal or greater magnitude can be expected in general for groundwater remediation applications and for many other applications of dynamic control. The LQR algorithm with management periods was further modified by assuming steady-state hydraulics within a management period (SSLQR), which simplifies the derivatives of the transition equation. A quasi-Newton differential dynamic programming (QNDDP) was formulated by approximating the complicated second derivatives of the transition equation using a Broyden rank-one approximation. QNDDP converged to the optimal policy for the test problem significantly faster than the LQR algorithm, requiring approximately half the computational time. With the test problem expanded to include the capacity of the treatment facility as a state variable, QNDDP with management periods can determine the optimal treatment facility capacity. With many management periods, the addition of the capital costs of the treatment facility changed the optimal policy so that the required treatment facility capacity was reduced
On Revenue-Optimal Dynamic Auctions for Bidders with Interdependent Values
Constantin, Florin; Parkes, David C.
In a dynamic market, being able to update one's value based on information available to other bidders currently in the market can be critical to having profitable transactions. This is nicely captured by the model of interdependent values (IDV): a bidder's value can explicitly depend on the private information of other bidders. In this paper we present preliminary results about the revenue properties of dynamic auctions for IDV bidders. We adopt a computational approach to design single-item revenue-optimal dynamic auctions with known arrivals and departures but (private) signals that arrive online. In leveraging a characterization of truthful auctions, we present a mixed-integer programming formulation of the design problem. Although a discretization is imposed on bidder signals the solution is a mechanism applicable to continuous signals. The formulation size grows exponentially in the dependence of bidders' values on other bidders' signals. We highlight general properties of revenue-optimal dynamic auctions in a simple parametrized example and study the sensitivity of prices and revenue to model parameters.
Dynamic Material Removal Rate and Tool Replacement Optimization with Calculus of Variations
Lan, Tian-Syung; Lo, Chih-Yao; Chiu, Min-Chie; Yeh, Long-Jyi
This study mathematically presents an optimum material removal control model, where the Material Removal Rate (MRR) is comprehensively introduced, to accomplish the dynamic machining control and tool life determination of a cutting tool under an expected machining quantity. To resolve the incessant cutting-rate control problem, Calculus of Variations is implemented for the optimum solution. Additionally, the decision criteria for selecting the dynamic solution are suggested and the sensitivity analyses for key variables in the optimal solution are fully discussed. The versatility of this study is furthermore exemplified through a numerical illustration from the real-world industry with BORLAND C++ BUILDER. It is shown that the theoretical and simulated results are in good agreement. This study absolutely explores the very promising solution to dynamically organize the MRR in minimizing the machining cost of a cutting tool for the contemporary machining industry.
Estimation of dynamic reactivity using an H∞ optimal filter with a nonlinear term
International Nuclear Information System (INIS)
Suzuki, Katsuo; Watanabe, Koiti
1996-01-01
A method of nonlinear filtering is applied to the problem of estimating the dynamic reactivity of a nonlinear reactor system. The nonlinear filtering algorithm developed is a simple modification of a linear H ∞ optimal filter with a nonlinear feedback loop added. The linear filter is designed on the basis of a linearized dynamical system model that consists of linearized point reactor kinetic equations and a reactivity state equation driven by a fictitious signal. The latter is artificially introduced to deal with the reactivity as a state variable. The results of the computer simulation show that the nonlinear filtering algorithm can be applied to estimate the dynamic reactivity of the nonlinear reactor system, even under relatively large reactivity disturbances
Game theory and extremal optimization for community detection in complex dynamic networks.
Lung, Rodica Ioana; Chira, Camelia; Andreica, Anca
2014-01-01
The detection of evolving communities in dynamic complex networks is a challenging problem that recently received attention from the research community. Dynamics clearly add another complexity dimension to the difficult task of community detection. Methods should be able to detect changes in the network structure and produce a set of community structures corresponding to different timestamps and reflecting the evolution in time of network data. We propose a novel approach based on game theory elements and extremal optimization to address dynamic communities detection. Thus, the problem is formulated as a mathematical game in which nodes take the role of players that seek to choose a community that maximizes their profit viewed as a fitness function. Numerical results obtained for both synthetic and real-world networks illustrate the competitive performance of this game theoretical approach.
Optimization Scheduling Model for Wind-thermal Power System Considering the Dynamic penalty factor
PENG, Siyu; LUO, Jianchun; WANG, Yunyu; YANG, Jun; RAN, Hong; PENG, Xiaodong; HUANG, Ming; LIU, Wanyu
2018-03-01
In this paper, a new dynamic economic dispatch model for power system is presented.Objective function of the proposed model presents a major novelty in the dynamic economic dispatch including wind farm: introduced the “Dynamic penalty factor”, This factor could be computed by using fuzzy logic considering both the variable nature of active wind power and power demand, and it could change the wind curtailment cost according to the different state of the power system. Case studies were carried out on the IEEE30 system. Results show that the proposed optimization model could mitigate the wind curtailment and the total cost effectively, demonstrate the validity and effectiveness of the proposed model.
Dynamic optimization of CELSS crop photosynthetic rate by computer-assisted feedback control
Chun, C.; Mitchell, C. A.
1997-01-01
A procedure for dynamic optimization of net photosynthetic rate (Pn) for crop production in Controlled Ecological Life-Support Systems (CELSS) was developed using leaf lettuce as a model crop. Canopy Pn was measured in real time and fed back for environmental control. Setpoints of photosynthetic photon flux (PPF) and CO_2 concentration for each hour of the crop-growth cycle were decided by computer to reach a targeted Pn each day. Decision making was based on empirical mathematical models combined with rule sets developed from recent experimental data. Comparisons showed that dynamic control resulted in better yield per unit energy input to the growth system than did static control. With comparable productivity parameters and potential for significant energy savings, dynamic control strategies will contribute greatly to the sustainability of space-deployed CELSS.
Directory of Open Access Journals (Sweden)
Tashkova Katerina
2011-10-01
Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of
Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo
2011-10-11
We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and
Chandrakanth, Balaji; Venkatesan, G; Prakash Kumar, L. S. S; Jalihal, Purnima; Iniyan, S
2018-03-01
The present work discusses the design and selection of a shell and tube condenser used in Low Temperature Thermal Desalination (LTTD). To optimize the key geometrical and process parameters of the condenser with multiple parameters and levels, a design of an experiment approach using Taguchi method was chosen. An orthogonal array (OA) of 25 designs was selected for this study. The condenser was designed, analysed using HTRI software and the heat transfer area with respective tube side pressure drop were computed using the same, as these two objective functions determine the capital and running cost of the condenser. There was a complex trade off between the heat transfer area and pressure drop in the analysis, however second law analysis was worked out for determining the optimal heat transfer area vs pressure drop for condensing the required heat load.
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Juan C. Chimal-Eguía
2012-12-01
Full Text Available This work shows the power of the variational approach for studying the efficiency of thermal engines in the context of the Finite Time Thermodynamics (FTT. Using an endoreversible Curzon–Ahlborn (CA heat engine as a model for actual thermal engines, three different criteria for thermal efficiency were analyzed: maximum power output, ecological function, and maximum power density. By means of this procedure, the performance of the CA heat engine with a nonlinear heat transfer law (the Stefan–Boltzmann law was studied to describe the heat exchanges between the working substance and its thermal reservoirs. The specific case of the Müser engine for all the criteria was analyzed. The results confirmed some previous findings using other procedures and additionally new results for the Müser engine performance were obtained.
International Nuclear Information System (INIS)
Bender, B.; Sparwasser, R.
1988-01-01
Environmental law is discussed exhaustively in this book. Legal and scientific fundamentals are taken into account, a systematic orientation is given, and hints for further information are presented. The book covers general environmental law, plan approval procedures, protection against nuisances, atomic law and radiation protection law, water protection law, waste management law, laws on chemical substances, conservation law. (HSCH) [de
Research on the Method of Traffic Organization and Optimization Based on Dynamic Traffic Flow Model
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Shu-bin Li
2017-01-01
Full Text Available The modern transportation system is becoming sluggish by traffic jams, so much so that it can harm the economic and society in our country. One of the reasons is the surging vehicles day by day. Another reason is the shortage of the traffic supply seriously. But the most important reason is that the traffic organization and optimization hardly met the conditions of modern transport development. In this paper, the practical method of the traffic organization and optimization used in regional area is explored by the dynamic traffic network analysis method. Firstly, the operational states of the regional traffic network are obtained by simulation method based on the self-developed traffic simulation software DynaCHINA, in which the improved traffic flow simulation model was proposed in order to be more suitable for actual domestic urban transport situation. Then the appropriated optimization model and algorithm were proposed according to different optimized content and organization goals, and the traffic simulation processes more suitable to regional optimization were designed exactly. Finally, a regional network in Tai’an city was selected as an example. The simulation results show that the proposed method is effective and feasible. It can provide strong scientific and technological support for the traffic management department.
Optimal Reference Strain Structure for Studying Dynamic Responses of Flexible Rockets
Tsushima, Natsuki; Su, Weihua; Wolf, Michael G.; Griffin, Edwin D.; Dumoulin, Marie P.
2017-01-01
In the proposed paper, the optimal design of reference strain structures (RSS) will be performed targeting for the accurate observation of the dynamic bending and torsion deformation of a flexible rocket. It will provide the detailed description of the finite-element (FE) model of a notional flexible rocket created in MSC.Patran. The RSS will be attached longitudinally along the side of the rocket and to track the deformation of the thin-walled structure under external loads. An integrated surrogate-based multi-objective optimization approach will be developed to find the optimal design of the RSS using the FE model. The Kriging method will be used to construct the surrogate model. For the data sampling and the performance evaluation, static/transient analyses will be performed with MSC.Natran/Patran. The multi-objective optimization will be solved with NSGA-II to minimize the difference between the strains of the launch vehicle and RSS. Finally, the performance of the optimal RSS will be evaluated by checking its strain-tracking capability in different numerical simulations of the flexible rocket.
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
Babbitt, Gregory A; Coppola, Erin E; Mortensen, Jamie S; Ekeren, Patrick X; Viola, Cosmo; Goldblatt, Dallan; Hudson, André O
2018-02-01
Since the elucidation of the genetic code almost 50 years ago, many nonrandom aspects of its codon organization remain only partly resolved. Here, we investigate the recent hypothesis of 'dual-use' codons which proposes that in addition to allowing adjustment of codon optimization to tRNA abundance, the degeneracy in the triplet-based genetic code also multiplexes information regarding DNA's helical shape and protein-binding dynamics while avoiding interference with other protein-level characteristics determined by amino acid properties. How such structural optimization of the code within eukaryotic chromatin could have arisen from an RNA world is a mystery, but would imply some preadaptation in an RNA context. We analyzed synonymous (protein-silent) and nonsynonymous (protein-altering) mutational impacts on molecular dynamics in 13823 identically degenerate alternative codon reorganizations, defined by codon transitions in 7680 GPU-accelerated molecular dynamic simulations of implicitly and explicitly solvated double-stranded aRNA and bDNA structures. When compared to all possible alternative codon assignments, the standard genetic code minimized the impact of synonymous mutations on the random atomic fluctuations and correlations of carbon backbone vector trajectories while facilitating the specific movements that contribute to DNA polymer flexibility. This trend was notably stronger in the context of RNA supporting the idea that dual-use codon optimization and informational multiplexing in DNA resulted from the preadaptation of the RNA duplex to resist changes to thermostability. The nonrandom and divergent molecular dynamics of synonymous mutations also imply that the triplet-based code may have resulted from adaptive functional expansion enabling a primordial doublet code to multiplex gene regulatory information via the shape and charge of the minor groove.
Study of optimal exposure windows using 320-Detector rows dynamic volume CT
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Gang Sun
2010-12-01
Full Text Available Gang Sun1, Min Li1, Li Li1, Guo-ying Li1, Zhi-wei Jing21Departments of Medical Imaging, 2Medical Statistics, Jinan Military General Hospital, Shandong Province, ChinaAbstract: The purpose of this study was to determine the optimal electrocardiographic (ECG pulsing windows and evaluate the effect on reduced dose and accuracy using 320-detector rows dynamic volume computed tomography (DVCT. A total of 170 patients were prospectively studied. The optimal reconstruction windows were analyzed in 76 patients scanned using retrospective ECG gating. Forty-seven patients were scanned by the predicted triggering windows. The optimal positions of exposure intervals according to different heart rates were evaluated. Optimal image quality, radiation dose, and diagnostic accuracy were then investigated by applying optimal triggering windows. The optimal ECG pulsing windows were determined as follows: when heart rate was <70 beats per minute, the exposure windows should be preset at 60%–80%; for a heart rate 70–90 beats per minute at 70%–90%; and for a heart rate ≥90 beats per minute at 30%–50%. The radiation dose for patients scanned with prospective ECG gating was significantly lower (5.9 versus 12.9 mSv, P < 0.001. However, because two or three heart beats were needed when heart rate was >70 beats per minute, the radiation dose increased with increasing heart rate for both retrospective and prospective ECG gating (r = 0.64, P < 0.001 and r = 0.59, P < 0.001, respectively. On the basis of a per segment analysis, overall sensitivity was 98.0% (49/50, specificity was 99.2% (602/607, the positive predictive value was 90.7% (49/54, and the negative predictive value was 99.8% (602/603. In conclusion, DVCT has the potential to provide high image quality across a wide range of heart rates using an optimized ECG pulsing window. However, it is recommended to control heart rate below 70 beats per minute, if possible, to decrease the radiation dose
Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.
2015-08-01
We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.
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.
Rigatelli, Gianluca; Dell'Avvocata, Fabio; Zuin, Marco; Giatti, Sara; Duong, Khanh; Pham, Trung; Tuan, Nguyen Si; Vassiliev, Dobrin; Daggubati, Ramesh; Nguyen, Thach
2017-12-01
Provisional and culotte are the most commonly used techniques in left main (LM) stenting. The impact of different post-dilation techniques on fluid dynamic of LM bifurcation has not been yet investigated. The aim of this study is to evaluate, by means of computational fluid dynamic analysis (CFD), the impact of different post-dilation techniques including proximal optimization technique (POT), kissing balloon (KB), POT-Side-POT and POT-KB-POT, 2-steps Kissing (2SK) and Snuggle Kissing balloon (SKB) on flow dynamic profile after LM provisional or culotte stenting. We considered an LM-LCA-LCX bifurcation reconstructed after reviewing 100 consecutive patients (mean age 71.4 ± 9.3 years, 49 males) with LM distal disease. The diameters of LAD and LCX were modelled according to the Finnet's law as following: LM 4.5 mm, LAD 3.5 mm, LCX 2.75 mm, with bifurcation angle set up at 55°. Xience third-generation stent (Abbot Inc., USA) was reconstructed and virtually implanted in provisional/cross-over and culotte fashion. POT, KB, POT-side-POT, POT-KB-POT, 2SK and SKB were virtually applied and analyzed in terms of the wall shear stress (WSS). Analyzing the provisional stenting, the 2SK and KB techniques had a statistically significant lower impact on the WSS at the carina, while POT seemed to obtain a neutral effect. In the wall opposite to the carina, the more physiological profile has been obtained by KB and POT with higher WSS value and smaller surface area of the lower WSS. In culotte stenting, at the carina, POT-KB-POT and 2SK had a very physiological profile; while at the wall opposite to the carina, 2SK and POT-KB-POT decreased significantly the surface area of the lower WSS compared to the other techniques. From the fluid dynamic point of view in LM provisional stenting, POT, 2SK and KB showed a similar beneficial impact on the bifurcation rheology, while in LM culotte stenting, POT-KB-POT and 2SK performed slightly better than the other techniques, probably
Welstead, Jason; Crouse, Gilbert L., Jr.
2014-01-01
Empirical sizing guidelines such as tail volume coefficients have long been used in the early aircraft design phases for sizing stabilizers, resulting in conservatively stable aircraft. While successful, this results in increased empty weight, reduced performance, and greater procurement and operational cost relative to an aircraft with optimally sized surfaces. Including flight dynamics in the conceptual design process allows the design to move away from empirical methods while implementing modern control techniques. A challenge of flight dynamics and control is the numerous design variables, which are changing fluidly throughout the conceptual design process, required to evaluate the system response to some disturbance. This research focuses on addressing that challenge not by implementing higher order tools, such as computational fluid dynamics, but instead by linking the lower order tools typically used within the conceptual design process so each discipline feeds into the other. In thisresearch, flight dynamics and control was incorporated into the conceptual design process along with the traditional disciplines of vehicle sizing, weight estimation, aerodynamics, and performance. For the controller, a linear quadratic regulator structure with constant gains has been specified to reduce the user input. Coupling all the disciplines in the conceptual design phase allows the aircraft designer to explore larger design spaces where stabilizers are sized according to dynamic response constraints rather than historical static margin and volume coefficient guidelines.
The Patch-Levy-Based Bees Algorithm Applied to Dynamic Optimization Problems
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Wasim A. Hussein
2017-01-01
Full Text Available Many real-world optimization problems are actually of dynamic nature. These problems change over time in terms of the objective function, decision variables, constraints, and so forth. Therefore, it is very important to study the performance of a metaheuristic algorithm in dynamic environments to assess the robustness of the algorithm to deal with real-word problems. In addition, it is important to adapt the existing metaheuristic algorithms to perform well in dynamic environments. This paper investigates a recently proposed version of Bees Algorithm, which is called Patch-Levy-based Bees Algorithm (PLBA, on solving dynamic problems, and adapts it to deal with such problems. The performance of the PLBA is compared with other BA versions and other state-of-the-art algorithms on a set of dynamic multimodal benchmark problems of different degrees of difficulties. The results of the experiments show that PLBA achieves better results than the other BA variants. The obtained results also indicate that PLBA significantly outperforms some of the other state-of-the-art algorithms and is competitive with others.
International Nuclear Information System (INIS)
Arkani-Hamed, Nima; Cheng, Hsin-Chia; Luty, Markus; Thaler, Jesse
2005-01-01
We study the universal low-energy dynamics associated with the spontaneous breaking of Lorentz invariance down to spatial rotations. The effective lagrangian for the associated Goldstone field can be uniquely determined by the non-linear realization of a broken time diffeomorphism symmetry, up to some overall mass scales. It has previously been shown that this symmetry breaking pattern gives rise to a Higgs phase of gravity, in which gravity is modified in the infrared. In this paper, we study the effects of direct couplings between the Goldstone boson and standard model fermions, which necessarily accompany Lorentz-violating terms in the theory. The leading interaction is the coupling to the axial vector current, which reduces to spin in the non-relativistic limit. A spin moving relative to the 'ether' rest frame will emit Goldstone Cerenkov radiation. The Goldstone also induces a long-range inverse-square law force between spin sources with a striking angular dependence, reflecting the underlying Goldstone shockwaves and providing a smoking gun for this theory. We discuss the regime of validity of the effective theory describing these phenomena, and the possibility of probing Lorentz violations through Goldstone boson signals in a way that is complementary to direct tests in some regions of parameter space
International Nuclear Information System (INIS)
Zhnag, Y.Z.; Mahajan, S.M.
1994-01-01
On basis of equal-time correlation theory (a non-perturbative approach) inviscid power laws of 2D isotropic plasma turbulences with one Lagrangian inviscid constant of motion are unambiguously solved by determining the dynamical characteristics. Two distinct types of induced transport according to the divergence of the inverse correlation length in the inviscid limit are revealed. This analysis also suggests a physically reasonable closure. The self-consistent system (a set of integral equations) for plasma filaments is investigated in detail, and is found to be a nonlinear differential eigenvalue problem for diffusion coefficient D, whereon the Dyson-like (integral) equation plays a role of boundary condition. This new type of transport is non-Bohm-like, and is very much like the quasilinear formula even in the strong turbulence regime. Physically, it arises from synchronization of shrinking squared correlation length with decorrelation time, for which the ''mixing-length'' breaks down. The shrinkage of correlation length is a characteristic pertaining to the new type of turbulence; its relationship with the turbulence observed in supershot regime on TFTR is commented on. (author). 12 refs, 2 figs
Fast optimization of binary clusters using a novel dynamic lattice searching method
International Nuclear Information System (INIS)
Wu, Xia; Cheng, Wen
2014-01-01
Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd) 79 clusters with DFT-fit parameters of Gupta potential
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Dayan Adionel Guimarães
2016-09-01
Full Text Available In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information.
Multi objective optimization of foam-filled circular tubes for quasi-static and dynamic responses
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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.
Distributed Optimal Consensus Control for Nonlinear Multiagent System With Unknown Dynamic.
Zhang, Jilie; Zhang, Huaguang; Feng, Tao
2017-08-01
This paper focuses on the distributed optimal cooperative control for continuous-time nonlinear multiagent systems (MASs) with completely unknown dynamics via adaptive dynamic programming (ADP) technology. By introducing predesigned extra compensators, the augmented neighborhood error systems are derived, which successfully circumvents the system knowledge requirement for ADP. It is revealed that the optimal consensus protocols actually work as the solutions of the MAS differential game. Policy iteration algorithm is adopted, and it is theoretically proved that the iterative value function sequence strictly converges to the solution of the coupled Hamilton-Jacobi-Bellman equation. Based on this point, a novel online iterative scheme is proposed, which runs based on the data sampled from the augmented system and the gradient of the value function. Neural networks are employed to implement the algorithm and the weights are updated, in the least-square sense, to the ideal value, which yields approximated optimal consensus protocols. Finally, a numerical example is given to illustrate the effectiveness of the proposed scheme.
A Dynamic Optimization Strategy for the Operation of Large Scale Seawater Reverses Osmosis System
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Aipeng Jiang
2014-01-01
Full Text Available In this work, an efficient strategy was proposed for efficient solution of the dynamic model of SWRO system. Since the dynamic model is formulated by a set of differential-algebraic equations, simultaneous strategies based on collocations on finite element were used to transform the DAOP into large scale nonlinear programming problem named Opt2. Then, simulation of RO process and storage tanks was carried element by element and step by step with fixed control variables. All the obtained values of these variables then were used as the initial value for the optimal solution of SWRO system. Finally, in order to accelerate the computing efficiency and at the same time to keep enough accuracy for the solution of Opt2, a simple but efficient finite element refinement rule was used to reduce the scale of Opt2. The proposed strategy was applied to a large scale SWRO system with 8 RO plants and 4 storage tanks as case study. Computing result shows that the proposed strategy is quite effective for optimal operation of the large scale SWRO system; the optimal problem can be successfully solved within decades of iterations and several minutes when load and other operating parameters fluctuate.
AbouEisha, Hassan M.; Moshkov, Mikhail; Calo, Victor M.; Paszynski, Maciej; Goik, Damian; Jopek, Konrad
2014-01-01
In this paper we present a dynamic programming algorithm for finding optimal elimination trees for computational grids refined towards point or edge singularities. The elimination tree is utilized to guide the multi-frontal direct solver algorithm
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Xiangyong Chen
2014-01-01
hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.
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Mir Hamid Reza Ghoreishy
2013-06-01
Full Text Available A high performance passenger tire tread compound was optimized for its mechanical, dynamical and thermal properties. A reference compound was based on a blend of SBR and BR, sulfur and other ingredients without accelerator, carbon black and aromatic oil. The effects of CBS/TMTD and TBBS/TMTD as accelerator systems were studied with different quantities and the best accelerator system was chosen. Then, the blends of N330 and N550 carbon blacks were added in different quantities and the properties of these samples were studied to determine the best carbon black blend. Finally, the effect of different quantities of aromatic oil was investigated and the optimized quantity of aromatic oil and the final properties of tire tread compound were defined. The mechanical and dynamical tests were carried out on appropriate samples to determine tensile strength, elongation-at-break, fatigue-to-failure, abrasion resistance, hardness, resilience, dynamical-mechanical properties and temperature rise due to the heat build-up. The results showed that the compound containing 0.8 phr CBS, 0.7 phr TMTD, 40 phr N330,20 phr N550 and 15 phr aromatic oils demonstrated the best properties.
International Nuclear Information System (INIS)
Li, Y.F.; Peng, R.
2014-01-01
Most studies on multi-state series–parallel systems focus on the static type of system architecture. However, it is insufficient to model many complex industrial systems having several operation phases and each requires a subset of the subsystems combined together to perform certain tasks. To bridge this gap, this study takes into account this type of dynamic behavior in the multi-state series–parallel system and proposes an analytical approach to calculate the system availability and the operation cost. In this approach, Markov process is used to model the dynamics of system phase changing and component state changing, Markov reward model is used to calculate the operation cost associated with the dynamics, and universal generating function (UGF) is used to build system availability function from the system phase model and the component models. Based upon these models, an optimization problem is formulated to minimize the total system cost with the constraint that system availability is greater than a desired level. The genetic algorithm is then applied to solve the optimization problem. The proposed modeling and solution procedures are illustrated on a system design problem modified from a real-world maritime oil transportation system
Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data.
Kehl, Catherine; Simms, Andrew M; Toofanny, Rudesh D; Daggett, Valerie
2008-06-01
The Dynameomics project is our effort to characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations, as described by Beck et al. (in Protein Eng. Des. Select., the first paper in this series). The data produced by these simulations are highly multidimensional in structure and multi-terabytes in size. Both of these features present significant challenges for storage, retrieval and analysis. For optimal data modeling and flexibility, we needed a platform that supported both multidimensional indices and hierarchical relationships between related types of data and that could be integrated within our data warehouse, as described in the accompanying paper directly preceding this one. For these reasons, we have chosen On-line Analytical Processing (OLAP), a multi-dimensional analysis optimized database, as an analytical platform for these data. OLAP is a mature technology in the financial sector, but it has not been used extensively for scientific analysis. Our project is further more unusual for its focus on the multidimensional and analytical capabilities of OLAP rather than its aggregation capacities. The dimensional data model and hierarchies are very flexible. The query language is concise for complex analysis and rapid data retrieval. OLAP shows great promise for the dynamic protein analysis for bioengineering and biomedical applications. In addition, OLAP may have similar potential for other scientific and engineering applications involving large and complex datasets.
Dynamic imperfections and optimized feedback design in the Compact Linear Collider main linac
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Peder Eliasson
2008-05-01
Full Text Available The Compact Linear Collider (CLIC main linac is sensitive to dynamic imperfections such as element jitter, injected beam jitter, and ground motion. These effects cause emittance growth that, in case of ground motion, has to be counteracted by a trajectory feedback system. The feedback system itself will, due to jitter effects and imperfect beam position monitors (BPMs, indirectly cause emittance growth. Fast and accurate simulations of both the direct and indirect effects are desirable, but due to the many elements of the CLIC main linac, simulations may become very time consuming. In this paper, an efficient way of simulating linear (or nearly linear dynamic effects is described. The method is also shown to facilitate the analytic determination of emittance growth caused by the different dynamic imperfections while using a trajectory feedback system. Emittance growth expressions are derived for quadrupole, accelerating structure, and beam jitter, for ground motion, and for noise in the feedback BPMs. Finally, it is shown how the method can be used to design a feedback system that is optimized for the optics of the machine and the ground motion spectrum of the particular site. This feedback system gives an emittance growth rate that is approximately 10 times lower than that of traditional trajectory feedbacks. The robustness of the optimized feedback system is studied for a number of additional imperfections, e.g., dipole corrector imperfections and faulty knowledge about the machine optics, with promising results.
Dynamic imperfections and optimized feedback design in the Compact Linear Collider main linac
Eliasson, Peder
2008-05-01
The Compact Linear Collider (CLIC) main linac is sensitive to dynamic imperfections such as element jitter, injected beam jitter, and ground motion. These effects cause emittance growth that, in case of ground motion, has to be counteracted by a trajectory feedback system. The feedback system itself will, due to jitter effects and imperfect beam position monitors (BPMs), indirectly cause emittance growth. Fast and accurate simulations of both the direct and indirect effects are desirable, but due to the many elements of the CLIC main linac, simulations may become very time consuming. In this paper, an efficient way of simulating linear (or nearly linear) dynamic effects is described. The method is also shown to facilitate the analytic determination of emittance growth caused by the different dynamic imperfections while using a trajectory feedback system. Emittance growth expressions are derived for quadrupole, accelerating structure, and beam jitter, for ground motion, and for noise in the feedback BPMs. Finally, it is shown how the method can be used to design a feedback system that is optimized for the optics of the machine and the ground motion spectrum of the particular site. This feedback system gives an emittance growth rate that is approximately 10 times lower than that of traditional trajectory feedbacks. The robustness of the optimized feedback system is studied for a number of additional imperfections, e.g., dipole corrector imperfections and faulty knowledge about the machine optics, with promising results.
Dynamic Value Engineering Method Optimizing the Risk on Real Time Operating System
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Prashant Kumar Patra
2014-04-01
Full Text Available The value engineering is the umbrella of the many more sub-system like quality assurance, quality control, quality function design and development for manufacturability. The system engineering & value engineering is two part of the coin. The value engineering is the high level of technology management for every aspect of engineering fields. The value engineering is the high utilization of System Product (i.e. Processor, Memory & Encryption key, Services, Business and Resources at minimal cost. The high end operating system providing highest services at optimal cost & time. The value engineering provides the maximum performance, accountability, reliability, integrity and availability of processor, memory, encryption key and other inter dependency sub-components. The value engineering is the ratio of the maximum functionality of individual components to the optimal cost. VE=k [(P, M, E, C, A]/optimal cost. Where k is the proportionality constant. The VE is directly proportional to performance of individual components and inversely proportional to the minimal cost. The VE is directly proportional to the risk assessment. The VE maximize the business throughput & decision process mean while minimize the risk and down time. We have to develop the dynamic value engineering model & mechanism for risk optimization over a complex real time operating system This proposed composition model definite will be resolve our objective at top high level. Product
Optimal Elbow Angle for Extracting sEMG Signals During Fatiguing Dynamic Contraction
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Mohamed R. Al-Mulla
2015-09-01
Full Text Available Surface electromyographic (sEMG activity of the biceps muscle was recorded from 13 subjects. Data was recorded while subjects performed dynamic contraction until fatigue and the signals were segmented into two parts (Non-Fatigue and Fatigue. An evolutionary algorithm was used to determine the elbow angles that best separate (using Davies-Bouldin Index, DBI both Non-Fatigue and Fatigue segments of the sEMG signal. Establishing the optimal elbow angle for feature extraction used in the evolutionary process was based on 70% of the conducted sEMG trials. After completing 26 independent evolution runs, the best run containing the optimal elbow angles for separation (Non-Fatigue and Fatigue was selected and then tested on the remaining 30% of the data to measure the classification performance. Testing the performance of the optimal angle was undertaken on nine features extracted from each of the two classes (Non-Fatigue and Fatigue to quantify the performance. Results showed that the optimal elbow angles can be used for fatigue classification, showing 87.90% highest correct classification for one of the features and on average of all eight features (including worst performing features giving 78.45%.
International Nuclear Information System (INIS)
Zhang Xiaobing; Fan Ying; Wei Yiming
2009-01-01
China's Strategic Petroleum Reserve (SPR) is currently being prepared. But how large the optimal stockpile size for China should be, what the best acquisition strategies are, how to release the reserve if a disruption occurs, and other related issues still need to be studied in detail. In this paper, we develop a stochastic dynamic programming model based on a total potential cost function of establishing SPRs to evaluate the optimal SPR policy for China. Using this model, empirical results are presented for the optimal size of China's SPR and the best acquisition and drawdown strategies for a few specific cases. The results show that with comprehensive consideration, the optimal SPR size for China is around 320 million barrels. This size is equivalent to about 90 days of net oil import amount in 2006 and should be reached in the year 2017, three years earlier than the national goal, which implies that the need for China to fill the SPR is probably more pressing; the best stockpile release action in a disruption is related to the disruption levels and expected continuation probabilities. The information provided by the results will be useful for decision makers.
International Nuclear Information System (INIS)
Eisa, Fabian; Brauweiler, Robert; Peetz, Alexander; Hupfer, Martin; Nowak, Tristan; Kalender, Willi A
2012-01-01
One of the biggest challenges in dynamic contrast-enhanced CT is the optimal synchronization of scan start and duration with contrast medium administration in order to optimize image contrast and to reduce the amount of contrast medium. We present a new optically based approach, which was developed to investigate and optimize bolus timing and shape. The time-concentration curve of an intravenously injected test bolus of a dye is measured in peripheral vessels with an optical sensor prior to the diagnostic CT scan. The curves can be used to assess bolus shapes as a function of injection protocols and to determine contrast medium arrival times. Preliminary results for phantom and animal experiments showed the expected linear behavior between dye concentration and absorption. The kinetics of the dye was compared to iodinated contrast medium and was found to be in good agreement. The contrast enhancement curves were reliably detected in three mice with individual bolus shapes and delay times of 2.1, 3.5 and 6.1 s, respectively. The optical sensor appears to be a promising approach to optimize injection protocols and contrast enhancement timing and is applicable to all modalities without implying any additional radiation dose. Clinical tests are still necessary. (note)
Directory of Open Access Journals (Sweden)
Jadwiga Zaród
2011-01-01
Full Text Available The farms of Western Pomerania province possess a large surplus of manpower. The dynamic optimization models with random constraints served the investigation of the possibilities of implementation of the unused man-hours. Those models regarded four successive years 2003-2006. The solution proceeded in two steps. The first step let us construct the assumption of the surplus or the deficiency of production factors. In the next step additional variables regarding the lease of arable grounds were introduced while the unused man-hours were implemented with various probability. The optimal solutions indicated the area of particular crops, the quantity of livestock and the farm income dependent on the use of the existing employment. This study aims at the presentation of the possibility of implementation of unused man-hours in farms dealing solely with the crop production and also the production of crop and livestock.
Analysis of Population Diversity of Dynamic Probabilistic Particle Swarm Optimization Algorithms
Directory of Open Access Journals (Sweden)
Qingjian Ni
2014-01-01
Full Text Available In evolutionary algorithm, population diversity is an important factor for solving performance. In this paper, combined with some population diversity analysis methods in other evolutionary algorithms, three indicators are introduced to be measures of population diversity in PSO algorithms, which are standard deviation of population fitness values, population entropy, and Manhattan norm of standard deviation in population positions. The three measures are used to analyze the population diversity in a relatively new PSO variant—Dynamic Probabilistic Particle Swarm Optimization (DPPSO. The results show that the three measure methods can fully reflect the evolution of population diversity in DPPSO algorithms from different angles, and we also discuss the impact of population diversity on the DPPSO variants. The relevant conclusions of the population diversity on DPPSO can be used to analyze, design, and improve the DPPSO algorithms, thus improving optimization performance, which could also be beneficial to understand the working mechanism of DPPSO theoretically.
Dynamic Programming Optimization of Multi-rate Multicast Video-Streaming Services
Directory of Open Access Journals (Sweden)
Nestor Michael Caños Tiglao
2010-06-01
Full Text Available In large scale IP Television (IPTV and Mobile TV distributions, the video signal is typically encoded and transmitted using several quality streams, over IP Multicast channels, to several groups of receivers, which are classified in terms of their reception rate. As the number of video streams is usually constrained by both the number of TV channels and the maximum capacity of the content distribution network, it is necessary to find the selection of video stream transmission rates that maximizes the overall user satisfaction. In order to efficiently solve this problem, this paper proposes the Dynamic Programming Multi-rate Optimization (DPMO algorithm. The latter was comparatively evaluated considering several user distributions, featuring different access rate patterns. The experimental results reveal that DPMO is significantly more efficient than exhaustive search, while presenting slightly higher execution times than the non-optimal Multi-rate Step Search (MSS algorithm.
Energy Technology Data Exchange (ETDEWEB)
Sriyanyong, P. [King Mongkut' s Univ. of Technology, Bangkok (Thailand). Dept. of Teacher Training in Electrical Engineering
2008-07-01
This paper described the use of an enhanced particle swarm optimization (PSO) model to address the problem of dynamic economic dispatch (DED). A modified heuristic search method was incorporated into the PSO model. Both smooth and non-smooth cost functions were considered. The enhanced PSO model not only utilized the basic PSO algorithm in order to seek the optimal solution for the DED problem, but it also used a modified heuristic method to deal with constraints and increase the possibility of finding a feasible solution. In order to validate the enhanced PSO model, it was used and tested on 10-unit systems considering both smooth and non-smooth cost functions characteristics. The experimental results were also compared to other methods. The proposed technique was found to be better than other approaches. The enhanced PSO model outperformed others with respect to quality, stability and reliability. 23 refs., 1 tab., 8 figs.